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judge scores evaluate public trace quality and failure modes. They are never used as proper-score reward; resolved CRPS/Brier-style scores remain the training objective."},"traceQuality":[{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.spm-child-poverty-2025.2026-06-08T00-00-00-02-00.b57b807c86133e64","runId":"run.spm-child-poverty-2025.2026-06-08T00-00-00-02-00.b57b807c86133e64","predictionId":"spm-child-poverty-2025","specId":"spec.spm-child-poverty-2025","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.54,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["This is deliberately near-term: Census typically releases annual income, poverty, health insurance, and SPM estimates in September for the prior calendar year. The 2025 SPM child poverty rate should therefore resolve in September 2026, making it a useful early calibration target.","PolicyEngine baseline"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Near-term Census target","This is deliberately near-term: Census typically releases annual income, poverty, health insurance, and SPM estimates in September for the prior calendar year. The 2025 SPM child poverty rate should therefore resolve in September 2026, making it a useful early calibration target."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["This is deliberately near-term: Census typically releases annual income, poverty, health insurance, and SPM estimates in September for the prior calendar year. The 2025 SPM child poverty rate should therefore resolve in September 2026, making it a useful early calibration target."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.4, distribution present, forecast step count 1.","evidence":["The 2025 law and macro environment look much closer to 2022-2024 than to the 2021 expanded-CTC year. The point estimate sits slightly below 2024 because employment and real earnings improved, while the upper tail keeps room for housing and medical expense pressure in the SPM resource calculation.","Forecast: point 13.1, 80% interval [12, 14.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 13.0, ci80: [12.1, 14.1], drivers: [\"ctc_refundability\", \"earnings\", \"housing_costs\"] }","The 2025 law and macro environment look much closer to 2022-2024 than to the 2021 expanded-CTC year. The point estimate sits slightly below 2024 because employment and real earnings improved, while the upper tail keeps room for housing and medical expense pressure in the SPM resource calculation."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 13.0, ci80: [12.1, 14.1], drivers: [\"ctc_refundability\", \"earnings\", \"housing_costs\"] }","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: spm-child-poverty-2025\nrunLabel: Headline\nresolutionDate: 2026-09-15\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.spm-child-poverty-2025.2026-06-27T13-51-22Z.spm-child-poverty-2025-thesis-analyst-fast-2026-06-27t13-51-22z.aadcaf6e309465bf","runId":"run.spm-child-poverty-2025.2026-06-27T13-51-22Z.spm-child-poverty-2025-thesis-analyst-fast-2026-06-27t13-51-22z.aadcaf6e309465bf","predictionId":"spm-child-poverty-2025","specId":"spec.spm-child-poverty-2025","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base-rate/reference-class anchor: after the temporary 2021 child tax credit expansion ended, the child SPM rate returned to a high-12 to high-13 percent range. The three post-expansion observations, 2022 through 2024, average 13.3 percent, while the latest two average 13.75 percent.","Model prior: the forecast uses a persistence/post-2021 mean blend rather than a formal time-series model because the relevant post-policy regime has only three annual observations, and the 2021 expanded-child-tax-credit year is not exchangeable with 2022-2025."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Forecast of the 2025 Census child Supplemental Poverty Measure rate","The resolver is the Census Bureau's first printed Supplemental Poverty Measure poverty rate for people under age 18 for calendar year 2025, reported in the annual Income, Poverty and Health Insurance Coverage release package or the associated SPM tables. Later revised tables are out of scope."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is the Census Bureau's first printed Supplemental Poverty Measure poverty rate for people under age 18 for calendar year 2025, reported in the annual Income, Poverty and Health Insurance Coverage release package or the associated SPM tables. Later revised tables are out of scope.","Tool call: Checked the Census Bureau release calendar for the annual Income, Poverty and Health Insurance Coverage release covering calendar year 2025."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3.7, distribution present, forecast step count 1.","evidence":["Counter-consideration: upside risk is meaningful if CPS ASEC measured earnings for low-income families disappoint, housing and child care expenses push more families below SPM thresholds, or benefit participation/resource measurement weakens. Downside risk comes from stronger low-wage earnings, lower inflation thresholds, and larger refundable-credit effects than expected.","Post-expansion mean = (12.4 + 13.7 + 13.8) / 3 = 13.3. Latest-year anchor = 13.8. Blend gives roughly 0.6 * 13.8 + 0.4 * 13.3 = 13.6, then apply a small -0.2 percentage point judgmental improvement for no recessionary shock and some normalization from the 2022 inflation spike: point = 13.4. Recent annual changes were +7.2, +1.3, and +0.1 percentage points, but the +7.2 was the policy-regime break; within the post-break regime, a 1.3 point move occurred. I use about 1.3 points for annual volatility plus about 0.4 points for sampling/SPM component uncertainty and add slight upside skew for expense and benefit-measurement risk, producing an 80 percent central interval of 11.7 to 15.4."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Model prior: the forecast uses a persistence/post-2021 mean blend rather than a formal time-series model because the relevant post-policy regime has only three annual observations, and the 2021 expanded-child-tax-credit year is not exchangeable with 2022-2025.","Level effect: the 2024 first print is the best starting point because the federal child cash-benefit regime for calendar 2025 was much closer to 2024 than to 2021. This argues for an anchor near 13.8 percent rather than the 2021 low."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-consideration: upside risk is meaningful if CPS ASEC measured earnings for low-income families disappoint, housing and child care expenses push more families below SPM thresholds, or benefit participation/resource measurement weakens. Downside risk comes from stronger low-wage earnings, lower inflation thresholds, and larger refundable-credit effects than expected.","Post-expansion mean = (12.4 + 13.7 + 13.8) / 3 = 13.3. Latest-year anchor = 13.8. Blend gives roughly 0.6 * 13.8 + 0.4 * 13.3 = 13.6, then apply a small -0.2 percentage point judgmental improvement for no recessionary shock and some normalization from the 2022 inflation spike: point = 13.4. Recent annual changes were +7.2, +1.3, and +0.1 percentage points, but the +7.2 was the policy-regime break; within the post-break regime, a 1.3 point move occurred. I use about 1.3 points for annual volatility plus about 0.4 points for sampling/SPM component uncertainty and add slight upside skew for expense and benefit-measurement risk, producing an 80 percent central interval of 11.7 to 15.4."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast of the 2025 Census child Supplemental Poverty Measure rate","Tool call: Fetched recent Census SPM child poverty reference points from the official SPM publication/table series."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: spm-child-poverty-2025\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-09-15\ntraceLineCount: 20\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.official-poverty-rate-2025.2026-06-08T00-00-00-02-00.7055b1b9641cd525","runId":"run.official-poverty-rate-2025.2026-06-08T00-00-00-02-00.7055b1b9641cd525","predictionId":"official-poverty-rate-2025","specId":"spec.official-poverty-rate-2025","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.05,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["The official poverty measure excludes taxes, refundable credits, and noncash benefits, so it is a cleaner near-term read on cash-income and labor-market strength than SPM.","Tool call: census.lookup({ report: \"Poverty in the United States\", series: \"official_poverty_rate\", years: [2021, 2024] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.3, distribution present, forecast step count 1.","evidence":["The central path continues the 2023-2024 improvement but slows it. A recession would have shown more clearly in the 2025 labor market by now, so the upper tail is moderate rather than extreme.","Forecast: point 10.4, 80% interval [9.8, 11.1]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 10.5, ci80: [9.9, 11.0], drivers: [\"earnings\", \"social_security_income\", \"threshold_indexation\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The central path continues the 2023-2024 improvement but slows it. A recession would have shown more clearly in the 2025 labor market by now, so the upper tail is moderate rather than extreme."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 10.5, ci80: [9.9, 11.0], drivers: [\"earnings\", \"social_security_income\", \"threshold_indexation\"] }","Forecast"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: official-poverty-rate-2025\nrunLabel: Headline\nresolutionDate: 2026-09-15\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.official-poverty-rate-2025.2026-06-14T22-10-00Z.official-poverty-control-no-packs.9d0e091bc2e8b413","runId":"run.official-poverty-rate-2025.2026-06-14T22-10-00Z.official-poverty-control-no-packs.9d0e091bc2e8b413","predictionId":"official-poverty-rate-2025","specId":"spec.official-poverty-rate-2025","runLabel":"Control · cash trend","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.32,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["Without packs, this run extrapolates the 2021-2024 official poverty trend and checks whether labor-market deterioration is large enough to reverse the decline.","Tool call: census.lookup({ report: \"Poverty in the United States\", series: \"official_poverty_rate\", years: [2021, 2024] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The interval is wider because the control does not model cash-income composition or ASEC release noise explicitly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.7, distribution present, forecast step count 1.","evidence":["The interval is wider because the control does not model cash-income composition or ASEC release noise explicitly.","Forecast: point 10.6, 80% interval [9.7, 11.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The interval is wider because the control does not model cash-income composition or ASEC release noise explicitly."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Control trend holds the 2024 rate at 10.6 with a mild downward labor-income adjustment offset by threshold growth."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The interval is wider because the control does not model cash-income composition or ASEC release noise explicitly.","Forecast: point 10.6, 80% interval [9.7, 11.4]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: official-poverty-rate-2025\nrunLabel: Control · cash trend\nresolutionDate: 2026-09-15\ntraceLineCount: 7\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.official-poverty-rate-2025.2026-06-14T22-16-00Z.official-poverty-census-packs.4d9545e2f9b3b363","runId":"run.official-poverty-rate-2025.2026-06-14T22-16-00Z.official-poverty-census-packs.4d9545e2f9b3b363","predictionId":"official-poverty-rate-2025","specId":"spec.official-poverty-rate-2025","runLabel":"Brier-1 · Census cash-income packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"cash-income-bridge@0.1.0\", \"asec-release-calibration@0.1.0\"], target: \"census.official_poverty_rate.2025\" })","Packed estimate = 10.6 base rate - 0.2pp labor-income improvement - 0.1pp cash-income bridge adjustment = 10.3."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"cash-income-bridge@0.1.0\", \"asec-release-calibration@0.1.0\"], target: \"census.official_poverty_rate.2025\" })","Tool call: policyengine.simulate({ policy: \"current_law\", year: 2025, output: \"official_poverty_rate\", map_to: \"person\", income_definition: \"cash_income\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"cash-income-bridge@0.1.0\", \"asec-release-calibration@0.1.0\"], target: \"census.official_poverty_rate.2025\" })","Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"reference_class\", \"cash_income_bridge\", \"asec_release_error\"] }"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.3, distribution present, forecast step count 1.","evidence":["Forecast: point 10.3, 80% interval [9.7, 11]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 10.5, ci80: [9.9, 11.0], drivers: [\"earnings\", \"social_security_income\", \"threshold_indexation\"] }","The packs pull the center slightly below the no-pack trend and narrow the high side because the official measure excludes noncash benefit volatility."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 10.5, ci80: [9.9, 11.0], drivers: [\"earnings\", \"social_security_income\", \"threshold_indexation\"] }","Forecast: point 10.3, 80% interval [9.7, 11]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: official-poverty-rate-2025\nrunLabel: Brier-1 · Census cash-income packs\nresolutionDate: 2026-09-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.official-poverty-rate-2025.2026-06-27T14-15-02Z.official-poverty-rate-2025-thesis-analyst-fast-2026-06-27t14-15-02z.91ba75006607e4a6","runId":"run.official-poverty-rate-2025.2026-06-27T14-15-02Z.official-poverty-rate-2025-thesis-analyst-fast-2026-06-27t14-15-02z.91ba75006607e4a6","predictionId":"official-poverty-rate-2025","specId":"spec.official-poverty-rate-2025","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Reference class/base rate: the last three first-print official poverty rates are 11.5, 11.1, and 10.6 percent. A simple recent average is 11.07 percent, while the latest level is 10.6 percent. The explicit model prior is persistence blended with the recent mean and realized one-year changes, not a richer time-series model, because only a short recent first-print official series was fetched in this fast run.","Counter-consideration: a downside-to-poverty scenario is that cash earnings and Social Security income keep pretax cash income ahead of thresholds, leaving the rate near 10.5. An upside poverty scenario is that weak hiring, reduced hours, and CPS sampling produce a sharper reversal to 11.7 or more. Outside the interval would likely require either a surprisingly broad cash-income gain below the median or a much worse late-2025 labor shock than the annual averages imply."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Forecast for the 2025 U.S. official poverty rate first print","The resolver is the Census Bureau official poverty measure for calendar year 2025, reported as the percentage of people in poverty in the first Poverty in the United States: 2025 release/Table A-1 from CPS ASEC. This is not the SPM: taxes, refundable credits, SNAP, housing-cost adjustments, work expenses, medical expenses, and geographic threshold adjustments do not define this official-poverty target."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast for the 2025 U.S. official poverty rate first print","The resolver is the Census Bureau official poverty measure for calendar year 2025, reported as the percentage of people in poverty in the first Poverty in the United States: 2025 release/Table A-1 from CPS ASEC. This is not the SPM: taxes, refundable credits, SNAP, housing-cost adjustments, work expenses, medical expenses, and geographic threshold adjustments do not define this official-poverty target."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.5, distribution present, forecast step count 1.","evidence":["Level and momentum: 2024 was already low, so further large declines are harder. The cited labor-market evidence points to some upward risk from 10.6, but the update is kept moderate because the draft did not fetch a full cited table for 2025 earnings, inflation, or transfer-income offsets.","Counter-consideration: a downside-to-poverty scenario is that cash earnings and Social Security income keep pretax cash income ahead of thresholds, leaving the rate near 10.5. An upside poverty scenario is that weak hiring, reduced hours, and CPS sampling produce a sharper reversal to 11.7 or more. Outside the interval would likely require either a surprisingly broad cash-income gain below the median or a much worse late-2025 labor shock than the annual averages imply."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Reference class/base rate: the last three first-print official poverty rates are 11.5, 11.1, and 10.6 percent. A simple recent average is 11.07 percent, while the latest level is 10.6 percent. The explicit model prior is persistence blended with the recent mean and realized one-year changes, not a richer time-series model, because only a short recent first-print official series was fetched in this fast run.","Level and momentum: 2024 was already low, so further large declines are harder. The cited labor-market evidence points to some upward risk from 10.6, but the update is kept moderate because the draft did not fetch a full cited table for 2025 earnings, inflation, or transfer-income offsets."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level and momentum: 2024 was already low, so further large declines are harder. The cited labor-market evidence points to some upward risk from 10.6, but the update is kept moderate because the draft did not fetch a full cited table for 2025 earnings, inflation, or transfer-income offsets.","Recent mean = (10.6 + 11.1 + 11.5) / 3 = 11.07. Recent year-to-year first-print changes were -0.4 and -0.5 percentage points, and the three-year level range is 0.9 points. Start from the 2024 level of 10.6 and apply a +0.4 point labor-market and mean-reversion update, giving 10.6 + 0.4 = 11.0. The 80 percent interval uses about +/-0.75 points: roughly 0.5 points for recent annual movement plus several tenths for CPS sampling, income-composition, and release uncertainty, rounded to 10.3 to 11.8."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for the 2025 U.S. official poverty rate first print","Tool result: Fetched 2024 official poverty rate 10.6 percent, 35.9 million people in poverty, 0.4 percentage point decrease from 2023, SPM 12.9 percent, Social Security moved 28.7 million people out of SPM poverty, report date 2025-09-09."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: official-poverty-rate-2025\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-09-15\ntraceLineCount: 19\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.median-household-income-2025.2026-06-08T00-00-00-02-00.61b2afb03587f0e2","runId":"run.median-household-income-2025.2026-06-08T00-00-00-02-00.61b2afb03587f0e2","predictionId":"median-household-income-2025","specId":"spec.median-household-income-2025","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.54,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Median household income is one of the fastest-resolving economic well-being targets in the catalog. The 2025 ASEC release gives a near-term check on the income side of the poverty forecasts.","Tool call: census.lookup({ report: \"Income in the United States\", series: \"real_median_household_income\", years: [2021, 2024] })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: census.lookup({ report: \"Income in the United States\", series: \"real_median_household_income\", years: [2021, 2024] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Median household income is one of the fastest-resolving economic well-being targets in the catalog. The 2025 ASEC release gives a near-term check on the income side of the poverty forecasts.","The central estimate is nearly flat versus 2024: real wage gains help, but household composition and ASEC sampling noise can move the published median by more than the underlying economic trend."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4300, distribution present, forecast step count 1.","evidence":["Forecast: point 80600, 80% interval [78600, 82900]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 80700, ci80: [78900, 82700], drivers: [\"real_wages\", \"employment\", \"household_composition\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["The central estimate is nearly flat versus 2024: real wage gains help, but household composition and ASEC sampling noise can move the published median by more than the underlying economic trend."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Median household income is one of the fastest-resolving economic well-being targets in the catalog. The 2025 ASEC release gives a near-term check on the income side of the poverty forecasts.","Tool result: { point: 80700, ci80: [78900, 82700], drivers: [\"real_wages\", \"employment\", \"household_composition\"] }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: median-household-income-2025\nrunLabel: Headline\nresolutionDate: 2026-09-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.median-household-income-2025.2026-06-14T22-22-00Z.median-income-control-no-packs.2f2b7fc62bd3b756","runId":"run.median-household-income-2025.2026-06-14T22-22-00Z.median-income-control-no-packs.2f2b7fc62bd3b756","predictionId":"median-household-income-2025","specId":"spec.median-household-income-2025","runLabel":"Control · trend nowcast","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and implicit outside-view language.","evidence":["Tool call: census.lookup({ report: \"Income in the United States\", series: \"real_median_household_income\", years: [2021, 2024] })","Control estimate = 2024 estimated median 80,100 plus near-zero real median wage drift after composition noise."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["Tool call: census.lookup({ report: \"Income in the United States\", series: \"real_median_household_income\", years: [2021, 2024] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The control holds close to the 2024 estimate and applies a light wage-growth update, but does not explicitly model household-composition or ASEC release noise.","The interval is wide because the control treats ASEC sampling error as a generic residual rather than a release-specific calibration."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5800, distribution present, forecast step count 1.","evidence":["The interval is wide because the control treats ASEC sampling error as a generic residual rather than a release-specific calibration.","Forecast: point 80100, 80% interval [77500, 83300]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The interval is wide because the control treats ASEC sampling error as a generic residual rather than a release-specific calibration."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The control holds close to the 2024 estimate and applies a light wage-growth update, but does not explicitly model household-composition or ASEC release noise."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The interval is wide because the control treats ASEC sampling error as a generic residual rather than a release-specific calibration.","Forecast: point 80100, 80% interval [77500, 83300]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: median-household-income-2025\nrunLabel: Control · trend nowcast\nresolutionDate: 2026-09-15\ntraceLineCount: 7\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.median-household-income-2025.2026-06-14T22-28-00Z.median-income-asec-packs.0cbf1d3e99414241","runId":"run.median-household-income-2025.2026-06-14T22-28-00Z.median-income-asec-packs.0cbf1d3e99414241","predictionId":"median-household-income-2025","specId":"spec.median-household-income-2025","runLabel":"Brier-1 · ASEC income packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"asec-income-nowcast@0.1.0\", \"asec-release-calibration@0.1.0\"], target: \"census.asec.median_household_income.2025\" })","Tool call: policyengine.simulate({ scenario: \"baseline_macro\", year: 2025, output: \"median_household_income_real\", source: \"asec\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"asec-income-nowcast@0.1.0\", \"asec-release-calibration@0.1.0\"], target: \"census.asec.median_household_income.2025\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"asec-income-nowcast@0.1.0\", \"asec-release-calibration@0.1.0\"], target: \"census.asec.median_household_income.2025\" })","Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"reference_class\", \"income_nowcast\", \"asec_release_error\"] }"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4000, distribution present, forecast step count 1.","evidence":["The ASEC packs move the center modestly above the control and tighten the lower tail by separating true income growth from release noise.","Forecast: point 80800, 80% interval [78900, 82900]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 80700, ci80: [78900, 82700], drivers: [\"real_wages\", \"employment\", \"household_composition\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 80700, ci80: [78900, 82700], drivers: [\"real_wages\", \"employment\", \"household_composition\"] }","Forecast: point 80800, 80% interval [78900, 82900]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: median-household-income-2025\nrunLabel: Brier-1 · ASEC income packs\nresolutionDate: 2026-09-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.spm-child-poverty-2027.2026-06-08T00-00-00-02-00.d6c1a6efa375333f","runId":"run.spm-child-poverty-2027.2026-06-08T00-00-00-02-00.d6c1a6efa375333f","predictionId":"spm-child-poverty-2027","specId":"spec.spm-child-poverty-2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.41,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool result: { baseline: 4.2%, range: [3.8%, 4.7%] }","Labor-market path is close to neutral for child poverty at this baseline — the 4.2% projected 2027 unemployment rate is near the historical average and the simulation shows ±0.3pp on child poverty over the [3.8%, 4.7%] band."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool result: { point: 13.1, ci80: [12.2, 14.0], drivers: [\"CTC reverts to $1,000 / child\", \"EITC expansions sunset\", \"CTC phase-in unchanged\"] }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The SPM child poverty rate for 2027 is dominated by the configuration of refundable credits under whatever tax regime is in force, plus the labor market. The CTC is the single largest policy lever — it directly raised the CTC sensitivity of SPM child poverty by roughly 4 percentage points during the 2021 expansion. The 2027 reading depends critically on how TCJA-extension legislation resolves."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.9, distribution present, forecast step count 1.","evidence":["Forecast: point 11.8, 80% interval [10.5, 13.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 13.1, ci80: [12.2, 14.0], drivers: [\"CTC reverts to $1,000 / child\", \"EITC expansions sunset\", \"CTC phase-in unchanged\"] }","Tool result: { point: 11.4, ci80: [10.5, 12.4], drivers: [\"CTC remains $2,000 / child\", \"$1,700 refundable portion preserved\", \"EITC parameters unchanged\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["House passed a TCJA extension package in March. Senate markup is expected Q3. Conditional on the Senate moving a vehicle, full extension is the modal outcome but partial scaling (especially on CTC refundability) is a live possibility. Weighting:"]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The SPM child poverty rate for 2027 is dominated by the configuration of refundable credits under whatever tax regime is in force, plus the labor market. The CTC is the single largest policy lever — it directly raised the CTC sensitivity of SPM child poverty by roughly 4 percentage points during the 2021 expansion. The 2027 reading depends critically on how TCJA-extension legislation resolves.","Tool result: { point: 13.1, ci80: [12.2, 14.0], drivers: [\"CTC reverts to $1,000 / child\", \"EITC expansions sunset\", \"CTC phase-in unchanged\"] }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: spm-child-poverty-2027\nrunLabel: Headline\nresolutionDate: 2028-09-15\ntraceLineCount: 19\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.spm-child-poverty-2027.2026-06-27T14-18-09Z.spm-child-poverty-2027-thesis-analyst-fast-2026-06-27t14-18-09z.bb741ac6e75227e5","runId":"run.spm-child-poverty-2027.2026-06-27T14-18-09Z.spm-child-poverty-2027-thesis-analyst-fast-2026-06-27t14-18-09z.bb741ac6e75227e5","predictionId":"spm-child-poverty-2027","specId":"spec.spm-child-poverty-2027","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool call: Checked Census historical SPM table/report context for pre-pandemic and pandemic-policy anchor points.","Base-rate/reference-class anchor: absent a new 2021-scale refundable-credit expansion, the most relevant outside-view level is the post-expiration 2022-2024 range of 12.4 to 13.8 percent, with more weight on 2023-2024 because SPM thresholds, rent, medical expenses, and benefit take-up had mostly normalized after the pandemic emergency period."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["The resolver is the Census Bureau's first published SPM poverty rate for people under age 18 for calendar year 2027. This is not the official poverty measure: SPM resources add taxes, refundable credits, and noncash transfers, and subtract necessary expenses including medical and work expenses, with thresholds adjusted for housing tenure and geography.","Tool call: Checked Census annual income, poverty, and health insurance release pages and CPS ASEC SPM table B-2 for the recent child SPM reference class."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is the Census Bureau's first published SPM poverty rate for people under age 18 for calendar year 2027. This is not the official poverty measure: SPM resources add taxes, refundable credits, and noncash transfers, and subtract necessary expenses including medical and work expenses, with thresholds adjusted for housing tenure and geography.","Tool call: Checked Census annual income, poverty, and health insurance release pages and CPS ASEC SPM table B-2 for the recent child SPM reference class."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5.9, distribution present, forecast step count 1.","evidence":["Point calculation: start from a weighted recent baseline of 13.7 percent using 2022-2024 values, add +0.3 for loss of residual pandemic-era supports and higher SPM expense pressure by 2027, add +0.2 for recession/policy asymmetry because downside poverty risks are larger than upside income surprises, giving 14.2 percent. Interval: using the non-2021-reversal post-expiration evidence, 2022 to 2023 was +1.3 pp and 2023 to 2024 was +0.1 pp, while 2019 to 2024 was +1.2 pp; I treat roughly +/-2.5 pp as normal 80 percent uncertainty around 14.2, then widen and right-skew judgmentally for tax-credit, benefit, and labor-market tail risk to 11.5 to 17.4.","Review disposition: accepted the resolution-date critique by no longer presenting 2028-09-12 as verified and by making the rule bind to the actual first Census print, with 2028-09-30 used only as an operational resolution deadline because the official 2028 calendar entry was not available. Accepted the interval critique by making the volatility basis and judgmental widening explicit; accepted the table-numbering and numeric-tail clarifications."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base-rate/reference-class anchor: absent a new 2021-scale refundable-credit expansion, the most relevant outside-view level is the post-expiration 2022-2024 range of 12.4 to 13.8 percent, with more weight on 2023-2024 because SPM thresholds, rent, medical expenses, and benefit take-up had mostly normalized after the pandemic emergency period.","Level and momentum: the recent level is already slightly above the 2019 pre-pandemic rate of 12.6 percent, and the 2023 to 2024 movement was essentially flat at +0.1 percentage point. That argues against extrapolating a large trend increase from the 2021-to-2022 jump, because that jump mostly reflected policy expiration rather than ordinary poverty momentum."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Point calculation: start from a weighted recent baseline of 13.7 percent using 2022-2024 values, add +0.3 for loss of residual pandemic-era supports and higher SPM expense pressure by 2027, add +0.2 for recession/policy asymmetry because downside poverty risks are larger than upside income surprises, giving 14.2 percent. Interval: using the non-2021-reversal post-expiration evidence, 2022 to 2023 was +1.3 pp and 2023 to 2024 was +0.1 pp, while 2019 to 2024 was +1.2 pp; I treat roughly +/-2.5 pp as normal 80 percent uncertainty around 14.2, then widen and right-skew judgmentally for tax-credit, benefit, and labor-market tail risk to 11.5 to 17.4."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for calendar-year 2027 child Supplemental Poverty Measure poverty rate","Tool call: Checked Census historical SPM table/report context for pre-pandemic and pandemic-policy anchor points."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: spm-child-poverty-2027\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2028-09-15\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.unemployment-dec-2026.2026-06-08T00-00-00-02-00.3a8ae14a5dbb7bfc","runId":"run.unemployment-dec-2026.2026-06-08T00-00-00-02-00.3a8ae14a5dbb7bfc","predictionId":"unemployment-dec-2026","specId":"spec.unemployment-dec-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.51,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Single-month U-3 print, first release. Historically the median absolute monthly change in U-3 is roughly 0.1pp; six-month windows have a median absolute change of 0.3pp. The interesting dispersion is whether 2026 ends in a normal late-cycle drift (4.2 → 4.4) or whether there is enough labor-demand softening to push past 4.6.","Tool call: policyengine.simulate({ scenario: \"baseline_macro\", year: 2026, output: \"unemployment_rate_monthly\", month: 12, model: \"structural_var\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["The FOMC SEP median, CBO projection, and the brier structural-VAR all cluster between 4.27 and 4.40 for full-year 2026. December prints tend to run very slightly below the annual mean in expansions due to seasonal adjustment behavior in the household survey."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Single-month U-3 print, first release. Historically the median absolute monthly change in U-3 is roughly 0.1pp; six-month windows have a median absolute change of 0.3pp. The interesting dispersion is whether 2026 ends in a normal late-cycle drift (4.2 → 4.4) or whether there is enough labor-demand softening to push past 4.6."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.9, distribution present, forecast step count 1.","evidence":["Risk distribution","Upside-risk asymmetry is real: cycle endings tend to look like normal drift right up until a discontinuity. The 80% CI should be slightly wider on the high side to reflect that."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Risk distribution","Upside-risk asymmetry is real: cycle endings tend to look like normal drift right up until a discontinuity. The 80% CI should be slightly wider on the high side to reflect that."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 4.31, ci80: [3.92, 4.74] }","Tool result: { point: 4.27, ci80: [3.95, 4.61] }"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: unemployment-dec-2026\nrunLabel: Headline\nresolutionDate: 2027-01-09\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.cpi-u-annual-2026.2026-06-08T00-00-00-02-00.f96d6a8371381e07","runId":"run.cpi-u-annual-2026.2026-06-08T00-00-00-02-00.f96d6a8371381e07","predictionId":"cpi-u-annual-2026","specId":"spec.cpi-u-annual-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: policyengine.simulate({ scenario: \"baseline_macro\", year: 2026, output: \"cpi_components\", decomposition: true })","Tool call: fed.lookup({ source: \"SEP_dec_2025\", variable: \"core_pce_inflation\", year: 2026, statistic: \"median\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: fed.lookup({ source: \"consensus_blue_chip\", variable: \"cpi_u_yoy\", year: 2026 })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.1, distribution present, forecast step count 1.","evidence":["CPI-U typically runs 0.2-0.4pp above core PCE due to shelter weights. A 2.4 core-PCE median translates to roughly 2.7 CPI-U headline before tariff effects. Tariff pass-through to core goods is modest in the central case but is the principal upside-risk channel.","Distribution is mildly right-skewed: more upside risk from tariff escalation and energy shocks than downside risk from a sudden disinflationary collapse. CI reflects this."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["CPI-U typically runs 0.2-0.4pp above core PCE due to shelter weights. A 2.4 core-PCE median translates to roughly 2.7 CPI-U headline before tariff effects. Tariff pass-through to core goods is modest in the central case but is the principal upside-risk channel.","Distribution is mildly right-skewed: more upside risk from tariff escalation and energy shocks than downside risk from a sudden disinflationary collapse. CI reflects this."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 2.63, ci80: [2.18, 3.15] }","Tool result: { point: 2.6, dispersion_iqr: [2.4, 2.8] }"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: cpi-u-annual-2026\nrunLabel: Headline\nresolutionDate: 2027-01-15\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: resolution clarity (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.cpi-u-annual-2026.2026-06-14T21-50-00Z.control-no-packs.5c2ef840d6a09339","runId":"run.cpi-u-annual-2026.2026-06-14T21-50-00Z.control-no-packs.5c2ef840d6a09339","predictionId":"cpi-u-annual-2026","specId":"spec.cpi-u-annual-2026","runLabel":"Control · no packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.08,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["Tool call: bls.lookup({ series: \"CUUR0000SA0\", window: \"2017-2025\", transform: \"annual_average_yoy\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.4, distribution present, forecast step count 1.","evidence":["The interval is wider than the headline run because this ablation lacks component-level shelter, goods, tariff, and policy context. It would miss high if energy or tariffs reaccelerate, and miss low if shelter disinflation arrives faster than the aggregate history implies.","Forecast: point 2.5, 80% interval [1.9, 3.3]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The interval is wider than the headline run because this ablation lacks component-level shelter, goods, tariff, and policy context. It would miss high if energy or tariffs reaccelerate, and miss low if shelter disinflation arrives faster than the aggregate history implies."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The interval is wider than the headline run because this ablation lacks component-level shelter, goods, tariff, and policy context. It would miss high if energy or tariffs reaccelerate, and miss low if shelter disinflation arrives faster than the aggregate history implies.","Forecast: point 2.5, 80% interval [1.9, 3.3]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: cpi-u-annual-2026\nrunLabel: Control · no packs\nresolutionDate: 2027-01-15\ntraceLineCount: 7\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.cpi-u-annual-2026.2026-06-12T20-30-00Z.with-cpi-packs-jun-12.cf472f5478128669","runId":"run.cpi-u-annual-2026.2026-06-12T20-30-00Z.with-cpi-packs-jun-12.cf472f5478128669","predictionId":"cpi-u-annual-2026","specId":"spec.cpi-u-annual-2026","runLabel":"Brier-1 · CPI packs · Jun 12","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.3,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"cpi-component-decomposition@0.1.0\", \"tariff-pass-through@0.1.0\"], target: \"bls.cpi.u.annual_pct_change.2026\" })","Packed estimate before refresh = base-rate 2.55 + tariff tail 0.08 - energy mean reversion 0.03 = 2.6."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"cpi-component-decomposition@0.1.0\", \"tariff-pass-through@0.1.0\"], target: \"bls.cpi.u.annual_pct_change.2026\" })","Tool call: bls.lookup({ series: \"CUUR0000SA0\", window: \"2022-2026ytd\", asOf: \"2026-06-12\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"cpi-component-decomposition@0.1.0\", \"tariff-pass-through@0.1.0\"], target: \"bls.cpi.u.annual_pct_change.2026\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.4, distribution present, forecast step count 1.","evidence":["Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"reference_class\", \"component_recombine\", \"right_tail_stress\"] }","Packed estimate before refresh = base-rate 2.55 + tariff tail 0.08 - energy mean reversion 0.03 = 2.6."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: { annual_average_yoy: { 2022: 8.0, 2023: 4.1, 2024: 2.9, 2025: 2.7 }, ytd_pressure: 2.5, latest_monthly_pressure: \"mixed\" }","The interval remains broad because the annual-average measure still has late-year goods and energy risk. It would miss high if tariff pass-through or energy shocks dominate, and miss low if shelter disinflation accelerates."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The interval remains broad because the annual-average measure still has late-year goods and energy risk. It would miss high if tariff pass-through or energy shocks dominate, and miss low if shelter disinflation accelerates."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The interval remains broad because the annual-average measure still has late-year goods and energy risk. It would miss high if tariff pass-through or energy shocks dominate, and miss low if shelter disinflation accelerates.","Forecast: point 2.6, 80% interval [2, 3.4]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: cpi-u-annual-2026\nrunLabel: Brier-1 · CPI packs · Jun 12\nresolutionDate: 2027-01-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.cpi-u-annual-2026.2026-06-14T21-50-00Z.with-cpi-packs.dbd096f26b206a77","runId":"run.cpi-u-annual-2026.2026-06-14T21-50-00Z.with-cpi-packs.dbd096f26b206a77","predictionId":"cpi-u-annual-2026","specId":"spec.cpi-u-annual-2026","runLabel":"Brier-1 · CPI packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"cpi-component-decomposition@0.1.0\", \"tariff-pass-through@0.1.0\"], target: \"bls.cpi.u.annual_pct_change.2026\" })","Tool call: fed.lookup({ source: \"FOMC SEP\", variable: \"core_pce_inflation\", year: 2026, statistic: \"median\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"cpi-component-decomposition@0.1.0\", \"tariff-pass-through@0.1.0\"], target: \"bls.cpi.u.annual_pct_change.2026\" })","Tool call: bls.lookup({ series: \"CUUR0000SA0\", window: \"2022-2026ytd\", transform: [\"annual_average_yoy\", \"component_pressure\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"cpi-component-decomposition@0.1.0\", \"tariff-pass-through@0.1.0\"], target: \"bls.cpi.u.annual_pct_change.2026\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.3, distribution present, forecast step count 1.","evidence":["Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"reference_class\", \"component_recombine\", \"right_tail_stress\"] }","Packed estimate = base-rate 2.6 + shelter/services persistence 0.05 + tariff right-tail mean shift 0.08 - energy mean reversion 0.03 = 2.7."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool call: bls.lookup({ series: \"CUUR0000SA0\", window: \"2022-2026ytd\", transform: [\"annual_average_yoy\", \"component_pressure\"] })","Tool result: { annual_average_yoy: { 2022: 8.0, 2023: 4.1, 2024: 2.9, 2025: 2.7 }, ytd_pressure: 2.6, component_pressure: { shelter: \"sticky\", core_goods: \"tariff_upside\", energy: \"two-sided\" } }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The packs move the center slightly up and narrow the low side versus the no-pack control. The run would land outside the interval if goods pass-through is much stronger than observed or if shelter disinflation breaks sharply below the component path.","Forecast: point 2.7, 80% interval [2.1, 3.4]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: cpi-u-annual-2026\nrunLabel: Brier-1 · CPI packs\nresolutionDate: 2027-01-15\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: resolution clarity (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.median-household-income-2026.2026-06-08T00-00-00-02-00.a19eef517211a0d1","runId":"run.median-household-income-2026.2026-06-08T00-00-00-02-00.a19eef517211a0d1","predictionId":"median-household-income-2026","specId":"spec.median-household-income-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.03,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Real median household income, ASEC measure. Tracks real labor earnings of the typical household closely. ASEC sample noise is meaningful at the median (standard error ~$700 historically).","Tool call: policyengine.simulate({ scenario: \"baseline_macro\", year: 2026, output: \"median_household_income_real\", source: \"asec\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Real per-capita disposable income growth in the CBO baseline maps to roughly 0.7–1.0% growth in real median household income (household composition trends are a slight drag). $80,600 base × ~1.0% growth → ~$81,400. The simulation result is consistent."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4300, distribution present, forecast step count 1.","evidence":["Forecast: point 81200, 80% interval [79100, 83400]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 81230, ci80: [79140, 83370] }","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: median-household-income-2026\nrunLabel: Headline\nresolutionDate: 2027-09-15\ntraceLineCount: 13\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.irs-individual-income-tax-fy2027.2026-06-08T00-00-00-02-00.fcc0f00ae687e355","runId":"run.irs-individual-income-tax-fy2027.2026-06-08T00-00-00-02-00.fcc0f00ae687e355","predictionId":"irs-individual-income-tax-fy2027","specId":"spec.irs-individual-income-tax-fy2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.92,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["P(TCJA extended fully retroactive to 2026) = 0.55 · P(extended w/ modifications) = 0.25 · P(expiration / partial) = 0.20","Realizations risk"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 330, distribution present, forecast step count 1.","evidence":["Realizations risk","Capital-gains realizations are the biggest residual variance — a sustained equity drawdown into 2026 would reduce nonwithheld revenue by $40-90bn. Reflected in the wider downside tail."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Realizations risk"]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 2810, ci80: [2640, 2980], note: \"assumes TCJA expires end-2025 → TY2026 under post-TCJA brackets\" }","Tool result: { point: 2680, ci80: [2520, 2840], note: \"TCJA-permanent brackets, $24K standard deduction, SALT cap\" }"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: irs-individual-income-tax-fy2027\nrunLabel: Headline\nresolutionDate: 2027-10-20\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.real-gdp-growth-2026.2026-06-08T00-00-00-02-00.bc4e60e6f26c3d5a","runId":"run.real-gdp-growth-2026.2026-06-08T00-00-00-02-00.bc4e60e6f26c3d5a","predictionId":"real-gdp-growth-2026","specId":"spec.real-gdp-growth-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.51,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: policyengine.simulate({ scenario: \"baseline_macro\", year: 2026, output: \"real_gdp_q4q4\", model: \"structural_neoclassical\" })","Tool call: policyengine.simulate({ scenario: \"baseline_macro\", year: 2026, output: \"real_gdp_q4q4\", model: \"bayesian_var\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Investment composition is unusual — AI-related capex is contributing roughly 0.5pp to real GDP growth on its own. That makes the upside tail wider than typical late-cycle distributions and the downside tail heavier (sudden capex pullback)."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Q4/Q4 is the standard FOMC and CBO horizon. Less noisy than single-quarter prints but still subject to substantial revision. Advance estimate is what resolves — the second and third releases come later."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.9, distribution present, forecast step count 1.","evidence":["Investment composition is unusual — AI-related capex is contributing roughly 0.5pp to real GDP growth on its own. That makes the upside tail wider than typical late-cycle distributions and the downside tail heavier (sudden capex pullback).","Forecast: point 1.9, 80% interval [0.9, 2.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Q4/Q4 is the standard FOMC and CBO horizon. Less noisy than single-quarter prints but still subject to substantial revision. Advance estimate is what resolves — the second and third releases come later.","Investment composition is unusual — AI-related capex is contributing roughly 0.5pp to real GDP growth on its own. That makes the upside tail wider than typical late-cycle distributions and the downside tail heavier (sudden capex pullback)."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 1.86, ci80: [1.05, 2.69] }","Tool result: { point: 1.92, ci80: [0.85, 2.99] }"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: real-gdp-growth-2026\nrunLabel: Headline\nresolutionDate: 2027-01-28\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.uninsured-rate-2026.2026-06-08T00-00-00-02-00.49a58a1ceb687d2d","runId":"run.uninsured-rate-2026.2026-06-08T00-00-00-02-00.49a58a1ceb687d2d","predictionId":"uninsured-rate-2026","specId":"spec.uninsured-rate-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool call: cbo.lookup({ table: \"health_insurance_baseline_2026\", series: \"uninsured_rate_under_65\", year: 2026, policy: \"ept_expire\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["2026 is the first full year after the scheduled expiration of the ACA enhanced premium tax credits (ARPA/IRA). The marketplace-coverage response is the dominant driver. Medicaid unwinding has largely run its course by 2026; ESI is fairly stable."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["2026 is the first full year after the scheduled expiration of the ACA enhanced premium tax credits (ARPA/IRA). The marketplace-coverage response is the dominant driver. Medicaid unwinding has largely run its course by 2026; ESI is fairly stable."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2, distribution present, forecast step count 1.","evidence":["Forecast: point 10.1, 80% interval [9.2, 11.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["2026 is the first full year after the scheduled expiration of the ACA enhanced premium tax credits (ARPA/IRA). The marketplace-coverage response is the dominant driver. Medicaid unwinding has largely run its course by 2026; ESI is fairly stable.","Tool result: { point: 10.4, ci80: [9.5, 11.4], drivers: [\"~3.8M coverage loss\", \"net of churn into ESI/Medicaid\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 10.4, ci80: [9.5, 11.4], drivers: [\"~3.8M coverage loss\", \"net of churn into ESI/Medicaid\"] }","Tool result: { point: 9.0, ci80: [8.2, 9.9] }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: uninsured-rate-2026\nrunLabel: Headline\nresolutionDate: 2027-09-15\ntraceLineCount: 13\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.labor-force-participation-dec-2026.2026-06-08T00-00-00-02-00.d43b93e7554d19c3","runId":"run.labor-force-participation-dec-2026.2026-06-08T00-00-00-02-00.d43b93e7554d19c3","predictionId":"labor-force-participation-dec-2026","specId":"spec.labor-force-participation-dec-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.86,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: policyengine.simulate({ scenario: \"baseline_demographics\", year: 2026, output: \"lfpr_decomposition_dec\" })","CBO baseline implies a small slip from 62.5 to 62.3. Our prime-age trajectory is slightly more optimistic — recent vintages of the BLS data show 25-54 LFPR holding above 83.5. Net: 62.4 is the central case for December."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["CBO baseline implies a small slip from 62.5 to 62.3. Our prime-age trajectory is slightly more optimistic — recent vintages of the BLS data show 25-54 LFPR holding above 83.5. Net: 62.4 is the central case for December."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.9, distribution present, forecast step count 1.","evidence":["Forecast: point 62.4, 80% interval [61.9, 62.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 62.4, 80% interval [61.9, 62.8]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: labor-force-participation-dec-2026\nrunLabel: Headline\nresolutionDate: 2027-01-09\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.ctc-monthly-max-ty2027.2026-06-08T00-00-00-02-00.cea7f3877965f5ab","runId":"run.ctc-monthly-max-ty2027.2026-06-08T00-00-00-02-00.cea7f3877965f5ab","predictionId":"ctc-monthly-max-ty2027","specId":"spec.ctc-monthly-max-ty2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 5 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 3 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":1,"rationale":"Score 1/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 167, distribution present, forecast step count 1.","evidence":["Bimodal in spirit — mass at $1,000 (revert) and $2,000 (extend), with thin tails. Single-number CI obscures this; the 80% CI is wide to reflect the bimodality.","Forecast: point 183, 80% interval [83, 250]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Distribution shape"]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Maximum is the headline parameter — refundability and phase-in are separate forecast cells. Current law: $2,000/child through TY2025, reverting to $1,000/child in TY2026 absent legislation. Any TCJA extension would lock at $2,000 (= $167/mo) or higher.","Forecast: point 183, 80% interval [83, 250]"]}],"flags":["weak_resolution_clarity","no_ledger_target"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: ctc-monthly-max-ty2027\nrunLabel: Headline\nresolutionDate: 2027-04-15\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: resolution clarity (1/4). Flags: weak_resolution_clarity, no_ledger_target."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.ctc-expansion-cost-ty2026.2026-06-08T00-00-00-02-00.9dac525a48caf143","runId":"run.ctc-expansion-cost-ty2026.2026-06-08T00-00-00-02-00.9dac525a48caf143","predictionId":"ctc-expansion-cost-ty2026","specId":"spec.ctc-expansion-cost-ty2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.27,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Tool call: policyengine.economy({ policy: 29093, baseline: 2, region: \"us\", time_period: 2026 })","Tool result: { policy: \"$3,000 Fully Refundable Child Tax Credit\", baseline: \"Current law\", status: \"computing\", raw_budget_impact_billions: null }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["This cell asks for the official-score cost of a concrete CTC design, not just PolicyEngine's raw microsimulation output. The forecast starts from PolicyEngine because it encodes the law and the population model, then adjusts that result toward the target that will actually resolve.","Tool result: { policy: \"$3,000 Fully Refundable Child Tax Credit\", baseline: \"Current law\", status: \"computing\", raw_budget_impact_billions: null }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":1,"rationale":"Score 1/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 61.6, distribution present, forecast step count 1.","evidence":["Tool result: { raw_to_final_ratio: 1.04, additive_billions: 3.5, queued_uncertainty_multiplier: 1.4 }","Forecast: point 109.6, 80% interval [78.8, 140.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["This cell asks for the official-score cost of a concrete CTC design, not just PolicyEngine's raw microsimulation output. The forecast starts from PolicyEngine because it encodes the law and the population model, then adjusts that result toward the target that will actually resolve."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Tool result: { raw_to_final_ratio: 1.04, additive_billions: 3.5, queued_uncertainty_multiplier: 1.4 }"]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["This cell asks for the official-score cost of a concrete CTC design, not just PolicyEngine's raw microsimulation output. The forecast starts from PolicyEngine because it encodes the law and the population model, then adjusts that result toward the target that will actually resolve.","Forecast"]}],"flags":["weak_resolution_clarity","weak_counterarguments","no_ledger_target"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: ctc-expansion-cost-ty2026\nrunLabel: Headline\nresolutionDate: 2027-12-31\ntraceLineCount: 12\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: resolution clarity (1/4). Flags: weak_resolution_clarity, weak_counterarguments, no_ledger_target."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.ctc-current-law-outlays-ty2026.2026-06-08T00-00-00-02-00.dbd1758ab357ea54","runId":"run.ctc-current-law-outlays-ty2026.2026-06-08T00-00-00-02-00.dbd1758ab357ea54","predictionId":"ctc-current-law-outlays-ty2026","specId":"spec.ctc-current-law-outlays-ty2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and explicit outside-view language.","evidence":["This is the baseline CTC outlay cell the expansion-cost forecast compares against. It needs a tax-year measure, not a fiscal-year cash-flow proxy, because official outlay timing can shift refunds across fiscal years.","PolicyEngine baseline"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["This is the baseline CTC outlay cell the expansion-cost forecast compares against. It needs a tax-year measure, not a fiscal-year cash-flow proxy, because official outlay timing can shift refunds across fiscal years.","Tool call: policyengine.simulate({ policy: \"current_law\", year: 2026, output: \"ctc_outlays\", unit: \"billions\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":1,"rationale":"Score 1/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 18, distribution present, forecast step count 1.","evidence":["The raw model sits just below the public tax-expenditure trend. Calibration nudges the point estimate upward and keeps the interval wide enough for filing-year timing and SOI classification differences.","Forecast: point 60.5, 80% interval [52, 70]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["This is the baseline CTC outlay cell the expansion-cost forecast compares against. It needs a tax-year measure, not a fiscal-year cash-flow proxy, because official outlay timing can shift refunds across fiscal years.","Tool result: { point: 58.8, ci80: [54.0, 64.5], drivers: [\"eligible children\", \"refundability cap\", \"phase-in earnings\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["This is the baseline CTC outlay cell the expansion-cost forecast compares against. It needs a tax-year measure, not a fiscal-year cash-flow proxy, because official outlay timing can shift refunds across fiscal years.","Tool result: { point: 58.8, ci80: [54.0, 64.5], drivers: [\"eligible children\", \"refundability cap\", \"phase-in earnings\"] }"]}],"flags":["weak_resolution_clarity","weak_counterarguments","no_ledger_target"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: ctc-current-law-outlays-ty2026\nrunLabel: Headline\nresolutionDate: 2028-08-31\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_resolution_clarity, weak_counterarguments, no_ledger_target."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.eitc-outlays-ty2026.2026-06-08T00-00-00-02-00.fb4d887302e46e92","runId":"run.eitc-outlays-ty2026.2026-06-08T00-00-00-02-00.fb4d887302e46e92","predictionId":"eitc-outlays-ty2026","specId":"spec.eitc-outlays-ty2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.27,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: irs.lookup({ table: \"soi_historical_refundable_credits\", credit: \"eitc\", years: [2021, 2024] })","Tool result: { trend: \"nominal growth with stable recipient count\", model_gap_prior: \"+1.5B\" }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: policyengine.simulate({ policy: \"current_law\", year: 2026, output: \"eitc_outlays\", unit: \"billions\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":1,"rationale":"Score 1/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 19, distribution present, forecast step count 1.","evidence":["Forecast: point 74, 80% interval [65, 84]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["EITC outlays are a high-signal calibration target for PolicyEngine because the law is mechanical but eligibility, earnings reporting, and family composition create persistent model error.","Tool result: { point: 72.5, ci80: [66.4, 80.1], drivers: [\"wage distribution\", \"children by tax unit\", \"phase-in earnings\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["EITC outlays are a high-signal calibration target for PolicyEngine because the law is mechanical but eligibility, earnings reporting, and family composition create persistent model error.","Tool result: { point: 72.5, ci80: [66.4, 80.1], drivers: [\"wage distribution\", \"children by tax unit\", \"phase-in earnings\"] }"]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 72.5, ci80: [66.4, 80.1], drivers: [\"wage distribution\", \"children by tax unit\", \"phase-in earnings\"] }","forecast = PolicyEngine baseline + historical SOI calibration = $72.5B + $1.5B = $74.0B"]}],"flags":["weak_resolution_clarity","weak_counterarguments","no_ledger_target"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: eitc-outlays-ty2026\nrunLabel: Headline\nresolutionDate: 2028-08-31\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: resolution clarity (1/4). Flags: weak_resolution_clarity, weak_counterarguments, no_ledger_target."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.salt-40k-cap-revenue-cost-ty2027.2026-06-08T00-00-00-02-00.8a0f39c0733efb62","runId":"run.salt-40k-cap-revenue-cost-ty2027.2026-06-08T00-00-00-02-00.8a0f39c0733efb62","predictionId":"salt-40k-cap-revenue-cost-ty2027","specId":"spec.salt-40k-cap-revenue-cost-ty2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.08,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: policyengine.simulate({ reform: \"salt_cap_40k_joint\", baseline: \"salt_cap_10k_joint\", year: 2027, output: \"iit_revenue_delta\", unit: \"billions\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: policyengine.simulate({ reform: \"salt_cap_40k_joint\", baseline: \"salt_cap_10k_joint\", year: 2027, output: \"iit_revenue_delta\", unit: \"billions\" })","Tool call: jct.lookup({ topic: \"salt_cap_options\", cap_joint: 40000, year: 2027 })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":1,"rationale":"Score 1/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 30, distribution present, forecast step count 1.","evidence":["Tool result: { anchor_range_billions: [34, 44], note: \"static score before behavioral uncertainty\" }","The final forecast takes the magnitude of the PolicyEngine revenue delta, anchors to public score ranges, and widens the upper tail for state-tax behavior and capital-gains sensitivity."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: -36.5, ci80: [-49.0, -25.5], drivers: [\"AGI distribution\", \"itemization share\", \"state tax growth\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool result: { point: -36.5, ci80: [-49.0, -25.5], drivers: [\"AGI distribution\", \"itemization share\", \"state tax growth\"] }","Tool result: { anchor_range_billions: [34, 44], note: \"static score before behavioral uncertainty\" }"]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: -36.5, ci80: [-49.0, -25.5], drivers: [\"AGI distribution\", \"itemization share\", \"state tax growth\"] }","Forecast"]}],"flags":["weak_resolution_clarity","no_ledger_target"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: salt-40k-cap-revenue-cost-ty2027\nrunLabel: Headline\nresolutionDate: 2028-12-31\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: resolution clarity (1/4). Flags: weak_resolution_clarity, no_ledger_target."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.federal-minimum-wage-jan-2027.2026-06-08T00-00-00-02-00.7a09bbfe7a23ba18","runId":"run.federal-minimum-wage-jan-2027.2026-06-08T00-00-00-02-00.7a09bbfe7a23ba18","predictionId":"federal-minimum-wage-jan-2027","specId":"spec.federal-minimum-wage-jan-2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 3 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":1,"rationale":"Score 1/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.25, distribution present, forecast step count 1.","evidence":["Strongly right-skewed: 82% probability of exact status quo. Reporting the modal value as the point estimate is more honest than the mean given the discrete nature of the legislative outcome. CI reflects the small but non-trivial right tail.","Forecast: point 7.25, 80% interval [7.25, 9.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["HR.42 passed the House but Senate vote-count is well short of 60. Filibuster reform is conceivable but not in this Congress's calendar. Path to enactment requires either a bipartisan compromise version (lower number, possibly indexed, longer phase-in) or Senate procedural change.","Distribution and forecast"]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Distribution and forecast","Strongly right-skewed: 82% probability of exact status quo. Reporting the modal value as the point estimate is more honest than the mean given the discrete nature of the legislative outcome. CI reflects the small but non-trivial right tail."]}],"flags":["weak_resolution_clarity","no_ledger_target"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: federal-minimum-wage-jan-2027\nrunLabel: Headline\nresolutionDate: 2027-01-01\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: resolution clarity (1/4). Flags: weak_resolution_clarity, no_ledger_target."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.standard-deduction-joint-ty2027.2026-06-08T00-00-00-02-00.bcc729ca75823364","runId":"run.standard-deduction-joint-ty2027.2026-06-08T00-00-00-02-00.bcc729ca75823364","predictionId":"standard-deduction-joint-ty2027","specId":"spec.standard-deduction-joint-ty2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.54,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":1,"rationale":"Score 1/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 19000, distribution present, forecast step count 1.","evidence":["This is a policy-state forecast: whether the post-TCJA higher standard deduction remains in force dominates the interval, with inflation indexing determining the exact value if extended.","The modal outcome is extension of the higher deduction. The lower interval endpoint preserves the real reversion scenario because it remains a discrete legislative branch."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The modal outcome is extension of the higher deduction. The lower interval endpoint preserves the real reversion scenario because it remains a discrete legislative branch."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["This is a policy-state forecast: whether the post-TCJA higher standard deduction remains in force dominates the interval, with inflation indexing determining the exact value if extended.","The modal outcome is extension of the higher deduction. The lower interval endpoint preserves the real reversion scenario because it remains a discrete legislative branch."]}],"flags":["weak_resolution_clarity","weak_counterarguments","no_ledger_target"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: standard-deduction-joint-ty2027\nrunLabel: Headline\nresolutionDate: 2027-12-31\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_resolution_clarity, weak_counterarguments, no_ledger_target."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.top-marginal-income-tax-rate-ty2027.2026-06-08T00-00-00-02-00.e0930b35d6ead2fd","runId":"run.top-marginal-income-tax-rate-ty2027.2026-06-08T00-00-00-02-00.e0930b35d6ead2fd","predictionId":"top-marginal-income-tax-rate-ty2027","specId":"spec.top-marginal-income-tax-rate-ty2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and explicit outside-view language.","evidence":["This is a discrete statutory forecast. Current post-sunset law points to 39.6%, but the political baseline for a broader tax package strongly favors retaining the 37% top rate or replacing rate increases with narrower base broadeners."]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":1,"rationale":"Score 1/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.6, distribution present, forecast step count 1.","evidence":["The point estimate reports the modal statutory rate rather than the mean because resolution is categorical in practice. The 80% interval spans the two dominant statutory branches.","Forecast: point 37, 80% interval [37, 39.6]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The point estimate reports the modal statutory rate rather than the mean because resolution is categorical in practice. The 80% interval spans the two dominant statutory branches."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["This is a discrete statutory forecast. Current post-sunset law points to 39.6%, but the political baseline for a broader tax package strongly favors retaining the 37% top rate or replacing rate increases with narrower base broadeners."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["This is a discrete statutory forecast. Current post-sunset law points to 39.6%, but the political baseline for a broader tax package strongly favors retaining the 37% top rate or replacing rate increases with narrower base broadeners.","The point estimate reports the modal statutory rate rather than the mean because resolution is categorical in practice. The 80% interval spans the two dominant statutory branches."]}],"flags":["weak_resolution_clarity","weak_counterarguments","no_ledger_target"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: top-marginal-income-tax-rate-ty2027\nrunLabel: Headline\nresolutionDate: 2027-12-31\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: resolution clarity (1/4). Flags: weak_resolution_clarity, weak_counterarguments, no_ledger_target."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.salt-cap-ty2027.2026-06-08T00-00-00-02-00.893a0d6b1393fd9b","runId":"run.salt-cap-ty2027.2026-06-08T00-00-00-02-00.893a0d6b1393fd9b","predictionId":"salt-cap-ty2027","specId":"spec.salt-cap-ty2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["SALT cap is the highest-leverage knob in the TCJA-extension negotiation because the affected constituencies are concentrated in House districts with thin majorities. The TCJA cap sunsets after TY2025; current-law TY2026+ means no cap. Any extension package must affirmatively reimpose or modify the cap.","Tool call: policyengine.simulate({ scenario: \"salt_cap_22k_joint\", year: 2027, output: \"iit_revenue_delta_vs_no_cap_billions\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":1,"rationale":"Score 1/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 70000, distribution present, forecast step count 1.","evidence":["Multi-modal distribution; the point estimate is the expected value but the modal value is $20k. Use the CI as a range, not a posterior interval.","Forecast: point 22000, 80% interval [10000, 80000]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["SALT cap is the highest-leverage knob in the TCJA-extension negotiation because the affected constituencies are concentrated in House districts with thin majorities. The TCJA cap sunsets after TY2025; current-law TY2026+ means no cap. Any extension package must affirmatively reimpose or modify the cap."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Distribution caveat","Multi-modal distribution; the point estimate is the expected value but the modal value is $20k. Use the CI as a range, not a posterior interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: -88, ci80: [-110, -68] }","Multi-modal distribution; the point estimate is the expected value but the modal value is $20k. Use the CI as a range, not a posterior interval."]}],"flags":["weak_resolution_clarity","weak_counterarguments","no_ledger_target"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: salt-cap-ty2027\nrunLabel: Headline\nresolutionDate: 2027-12-31\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: resolution clarity (1/4). Flags: weak_resolution_clarity, weak_counterarguments, no_ledger_target."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-max-allotment-family-4-fy2027.2026-06-08T00-00-00-02-00.f5b0df69903f3e95","runId":"run.snap-max-allotment-family-4-fy2027.2026-06-08T00-00-00-02-00.f5b0df69903f3e95","predictionId":"snap-max-allotment-family-4-fy2027","specId":"spec.snap-max-allotment-family-4-fy2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.03,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 3 historical point(s) and explicit outside-view language.","evidence":["Under current law, the SNAP maximum is set as 100% of the Thrifty Food Plan for a 4-person household, indexed to June-of-prior-year food-at-home CPI. The 2021 USDA TFP reevaluation raised the base; the 2018 Farm Bill required additional reevaluation by 2027. Two paths: (1) routine annual inflation adjustment, or (2) discretionary TFP reset under FY2027 reauthorization.","Tool result: { change: \"freeze_tfp_at_2024_baseline\", projected_value: 975 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["House Ag Committee markup includes language that would constrain future TFP increases. Senate Ag chair has indicated unwillingness to advance any package that cuts SNAP benefits relative to current law. Standoff has lasted three Farm Bill cycles already."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":1,"rationale":"Score 1/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 70, distribution present, forecast step count 1.","evidence":["Forecast: point 1010, 80% interval [975, 1045]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 1010, ci80: [992, 1029] }","Forecast: point 1010, 80% interval [975, 1045]"]}],"flags":["weak_resolution_clarity","weak_counterarguments","no_ledger_target"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-max-allotment-family-4-fy2027\nrunLabel: Headline\nresolutionDate: 2026-10-01\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_resolution_clarity, weak_counterarguments, no_ledger_target."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-benefit-outlays-fy2027.2026-06-08T00-00-00-02-00.802ffa15ce23526e","runId":"run.snap-benefit-outlays-fy2027.2026-06-08T00-00-00-02-00.802ffa15ce23526e","predictionId":"snap-benefit-outlays-fy2027","specId":"spec.snap-benefit-outlays-fy2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.19,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 5 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: policyengine.simulate({ policy: \"snap_current_law\", year: 2027, output: \"snap_benefits_total\", unit: \"billions\" })","Tool result: { pandemic_peak_unwound: true, fy2026_run_rate_billions: 121, food_price_risk: \"upside\" }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 27, distribution present, forecast step count 1.","evidence":["Tool result: { pandemic_peak_unwound: true, fy2026_run_rate_billions: 121, food_price_risk: \"upside\" }","Forecast: point 128, 80% interval [116, 143]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["SNAP benefit outlays combine an eligibility/take-up model with a food-price-indexed benefit schedule. It is a good public-data cell because USDA and Treasury both publish outcome tables, but the forecast benefits from a PolicyEngine eligibility model.","Tool result: { point: 126.5, ci80: [117.0, 140.0], drivers: [\"TFP indexation\", \"caseload\", \"net income tests\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["SNAP benefit outlays combine an eligibility/take-up model with a food-price-indexed benefit schedule. It is a good public-data cell because USDA and Treasury both publish outcome tables, but the forecast benefits from a PolicyEngine eligibility model.","Tool result: { pandemic_peak_unwound: true, fy2026_run_rate_billions: 121, food_price_risk: \"upside\" }"]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["SNAP benefit outlays combine an eligibility/take-up model with a food-price-indexed benefit schedule. It is a good public-data cell because USDA and Treasury both publish outcome tables, but the forecast benefits from a PolicyEngine eligibility model.","Tool result: { point: 126.5, ci80: [117.0, 140.0], drivers: [\"TFP indexation\", \"caseload\", \"net income tests\"] }"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-benefit-outlays-fy2027\nrunLabel: Headline\nresolutionDate: 2027-11-30\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.aca-premium-tax-credit-outlays-fy2027.2026-06-08T00-00-00-02-00.84077a92eb5f4f35","runId":"run.aca-premium-tax-credit-outlays-fy2027.2026-06-08T00-00-00-02-00.84077a92eb5f4f35","predictionId":"aca-premium-tax-credit-outlays-fy2027","specId":"spec.aca-premium-tax-credit-outlays-fy2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.19,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: policyengine.simulate({ policy: \"enhanced_ptc_expire\", year: 2027, output: \"aca_premium_tax_credit_outlays\", unit: \"billions\" })","Tool call: policyengine.simulate({ policy: \"enhanced_ptc_extended\", year: 2027, output: \"aca_premium_tax_credit_outlays\", unit: \"billions\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 70, distribution present, forecast step count 1.","evidence":["The central forecast weights expiration as the modal path but leaves a large upper tail because a one- or two-year extension can be attached to a broader budget vehicle.","Forecast: point 94, 80% interval [62, 132]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 72, ci80: [58, 92], drivers: [\"lower enrollment\", \"original ACA subsidy schedule\"] }","Tool result: { point: 124, ci80: [101, 151], drivers: [\"higher enrollment\", \"zero-premium silver availability\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Premium tax credit outlays are a bridge between policy state and administrative behavior: the statutory subsidy schedule determines generosity, but enrollment and benchmark premiums determine the actual fiscal path.","The central forecast weights expiration as the modal path but leaves a large upper tail because a one- or two-year extension can be attached to a broader budget vehicle."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 72, ci80: [58, 92], drivers: [\"lower enrollment\", \"original ACA subsidy schedule\"] }","Tool result: { point: 124, ci80: [101, 151], drivers: [\"higher enrollment\", \"zero-premium silver availability\"] }"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: aca-premium-tax-credit-outlays-fy2027\nrunLabel: Headline\nresolutionDate: 2027-11-30\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-chip-enrollment-dec-2027.2026-06-08T00-00-00-02-00.86fe02161493e677","runId":"run.medicaid-chip-enrollment-dec-2027.2026-06-08T00-00-00-02-00.86fe02161493e677","predictionId":"medicaid-chip-enrollment-dec-2027","specId":"spec.medicaid-chip-enrollment-dec-2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.05,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: policyengine.simulate({ year: 2027, output: \"medicaid_chip_enrollment\", unit: \"millions\", renewal_churn: \"central\" })","Tool result: { peak_unwound: true, post_unwinding_floor_millions: 79, child_share_stabilizing: true }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 11, distribution present, forecast step count 1.","evidence":["The interval is asymmetric: downside is bounded by the post-unwinding floor, while upside comes from recession risk, state auto-renewal improvements, and marketplace affordability changes.","Forecast: point 82, 80% interval [77, 88]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 81.5, ci80: [77.8, 86.4], drivers: [\"income eligibility\", \"children retained\", \"redetermination churn\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The interval is asymmetric: downside is bounded by the post-unwinding floor, while upside comes from recession risk, state auto-renewal improvements, and marketplace affordability changes."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 81.5, ci80: [77.8, 86.4], drivers: [\"income eligibility\", \"children retained\", \"redetermination churn\"] }","Forecast"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-chip-enrollment-dec-2027\nrunLabel: Headline\nresolutionDate: 2028-06-30\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.spm-poverty-rate-2025.2026-06-08T00-00-00-02-00.a35b0a8b8772a28f","runId":"run.spm-poverty-rate-2025.2026-06-08T00-00-00-02-00.a35b0a8b8772a28f","predictionId":"spm-poverty-rate-2025","specId":"spec.spm-poverty-rate-2025","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.54,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Overall SPM poverty is less CTC-sensitive than child poverty but more exposed to housing, medical, SNAP, and labor-market inputs. This 2025 target resolves roughly a year earlier than the prior 2026 SPM cell, making it a better near-term calibration target.","PolicyEngine baseline"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Identifying the Census target","Tool call: census.lookup({ series: \"spm_poverty_rate\", years: [2021, 2024] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Overall SPM poverty is less CTC-sensitive than child poverty but more exposed to housing, medical, SNAP, and labor-market inputs. This 2025 target resolves roughly a year earlier than the prior 2026 SPM cell, making it a better near-term calibration target."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.5, distribution present, forecast step count 1.","evidence":["Forecast: point 12.7, 80% interval [12, 13.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 12.6, ci80: [12.0, 13.3], drivers: [\"tax credits\", \"housing costs\", \"medical expenses\"] }","The model stays close to the 2022-2024 post-expansion plateau. Improved employment and real earnings pull down slightly; shelter and medical expense pressure keep the rate near the 2024 level."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Overall SPM poverty is less CTC-sensitive than child poverty but more exposed to housing, medical, SNAP, and labor-market inputs. This 2025 target resolves roughly a year earlier than the prior 2026 SPM cell, making it a better near-term calibration target."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 12.6, ci80: [12.0, 13.3], drivers: [\"tax credits\", \"housing costs\", \"medical expenses\"] }","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: spm-poverty-rate-2025\nrunLabel: Headline\nresolutionDate: 2026-09-15\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.spm-poverty-rate-2025.2026-06-27T13-50-50Z.spm-poverty-rate-2025-thesis-analyst-fast-2026-06-27t13-50-50z.c3dc739d7cbffd1d","runId":"run.spm-poverty-rate-2025.2026-06-27T13-50-50Z.spm-poverty-rate-2025-thesis-analyst-fast-2026-06-27t13-50-50z.c3dc739d7cbffd1d","predictionId":"spm-poverty-rate-2025","specId":"spec.spm-poverty-rate-2025","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base-rate/reference-class anchor: the model prior is a simple persistence prior using the 2022-2024 post-pandemic-transfer-regime mean, about 12.7 percent, because the 2020 and 2021 pandemic-transfer years are poor comparators for 2025.","Upside scenario: a weaker 2025 CPS ASEC income print, higher necessary expenses, or reduced effective transfers puts the first print around 13.8 to 14.3. Downside scenario: stronger lower-wage real earnings and stable transfer receipt bring it near 11.5. Outside-the-interval downside would require a broader income surprise or policy effect not evident from the baseline."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The target is the Census Bureau first print for calendar-year 2025 all people under the Supplemental Poverty Measure, not a later revised table and not the official poverty measure.","Tool call: Checked the Census Bureau Event Calendar for the Income, Poverty, and Health Insurance release covering calendar-year 2025."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the Census Bureau first print for calendar-year 2025 all people under the Supplemental Poverty Measure, not a later revised table and not the official poverty measure.","Tool call: Checked the Census Bureau Event Calendar for the Income, Poverty, and Health Insurance release covering calendar-year 2025."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.2, distribution present, forecast step count 1.","evidence":["Point estimate: start from the 2022-2024 average (12.4+12.9+12.9)/3=12.73, apply only a small -0.1 persistence-plus-mild-income adjustment, and round to 12.6. For the 80% interval, recent non-pandemic-transfer year-to-year moves include 2022 to 2023 of +0.5 and 2023 to 2024 of 0.0, but SPM is sensitive to thresholds, expenses, survey measurement, and policy mechanics, so I use a subjective central interval of about -1.0/+1.2 percentage points around the point: 11.6 to 13.8.","Upside scenario: a weaker 2025 CPS ASEC income print, higher necessary expenses, or reduced effective transfers puts the first print around 13.8 to 14.3. Downside scenario: stronger lower-wage real earnings and stable transfer receipt bring it near 11.5. Outside-the-interval downside would require a broader income surprise or policy effect not evident from the baseline."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base-rate/reference-class anchor: the model prior is a simple persistence prior using the 2022-2024 post-pandemic-transfer-regime mean, about 12.7 percent, because the 2020 and 2021 pandemic-transfer years are poor comparators for 2025.","Level and momentum: because this run did not fetch a separate quantitative 2025 macro model, the inside-view update is deliberately small. I treat labor-market, inflation, shelter, medical-expense, and transfer assumptions as qualitative reasons for near-persistence rather than a strong directional override."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Point estimate: start from the 2022-2024 average (12.4+12.9+12.9)/3=12.73, apply only a small -0.1 persistence-plus-mild-income adjustment, and round to 12.6. For the 80% interval, recent non-pandemic-transfer year-to-year moves include 2022 to 2023 of +0.5 and 2023 to 2024 of 0.0, but SPM is sensitive to thresholds, expenses, survey measurement, and policy mechanics, so I use a subjective central interval of about -1.0/+1.2 percentage points around the point: 11.6 to 13.8.","Review disposition: accepted the reviewer requests to name the persistence model prior, reduce the inside-view adjustment to a mostly persistence forecast, state an interval basis tied to recent non-pandemic SPM movement plus subjective measurement/policy uncertainty, and make the Census event-calendar URL the auditable resolver source."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for 2025 all-people SPM poverty rate","Point estimate: start from the 2022-2024 average (12.4+12.9+12.9)/3=12.73, apply only a small -0.1 persistence-plus-mild-income adjustment, and round to 12.6. For the 80% interval, recent non-pandemic-transfer year-to-year moves include 2022 to 2023 of +0.5 and 2023 to 2024 of 0.0, but SPM is sensitive to thresholds, expenses, survey measurement, and policy mechanics, so I use a subjective central interval of about -1.0/+1.2 percentage points around the point: 11.6 to 13.8."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: spm-poverty-rate-2025\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-09-15\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.unemployment-insurance-outlays-fy2027.2026-06-08T00-00-00-02-00.136a0bbf8d8c7630","runId":"run.unemployment-insurance-outlays-fy2027.2026-06-08T00-00-00-02-00.136a0bbf8d8c7630","predictionId":"unemployment-insurance-outlays-fy2027","specId":"spec.unemployment-insurance-outlays-fy2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.22,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: policyengine.simulate({ scenario: \"baseline_labor_market\", year: 2027, output: \"ui_benefit_outlays\", unit: \"billions\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: bls.lookup({ series: [\"unemployment_rate\", \"insured_unemployment_rate\"], horizon: \"FY2027\" })","Tool call: policyengine.simulate({ scenario: \"baseline_labor_market\", year: 2027, output: \"ui_benefit_outlays\", unit: \"billions\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 46, distribution present, forecast step count 1.","evidence":["UI outlays are highly cyclical and right-skewed. The central case is a normal late-cycle claims path, but recession risk creates a much fatter upper tail than for most transfer programs.","Tool result: { unemployment_rate_mean: 4.5, insured_unemployment_rate_mean: 1.4, recession_tail_probability: 0.18 }"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 46, ci80: [34, 71], drivers: [\"claims duration\", \"weekly benefit\", \"covered employment\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["UI outlays are highly cyclical and right-skewed. The central case is a normal late-cycle claims path, but recession risk creates a much fatter upper tail than for most transfer programs."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 46, ci80: [34, 71], drivers: [\"claims duration\", \"weekly benefit\", \"covered employment\"] }","Forecast: point 49, 80% interval [32, 78]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: unemployment-insurance-outlays-fy2027\nrunLabel: Headline\nresolutionDate: 2027-11-30\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: resolution clarity (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.ssi-federal-payments-fy2027.2026-06-08T00-00-00-02-00.d9a12725fb2cfc8f","runId":"run.ssi-federal-payments-fy2027.2026-06-08T00-00-00-02-00.d9a12725fb2cfc8f","predictionId":"ssi-federal-payments-fy2027","specId":"spec.ssi-federal-payments-fy2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.95,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: policyengine.simulate({ policy: \"ssi_current_law\", year: 2027, output: \"ssi_federal_benefits\", unit: \"billions\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 16, distribution present, forecast step count 1.","evidence":["SSI federal payments are less cyclical than UI or SNAP; the main uncertainty is inflation indexing plus slow-moving recipient counts and redetermination outcomes.","The forecast stays close to the indexed current-law path; the upper interval mostly reflects higher COLA and reduced redetermination churn."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 74.2, ci80: [69.0, 82.0], drivers: [\"federal benefit rate\", \"countable income\", \"recipient count\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["SSI federal payments are less cyclical than UI or SNAP; the main uncertainty is inflation indexing plus slow-moving recipient counts and redetermination outcomes."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 74.2, ci80: [69.0, 82.0], drivers: [\"federal benefit rate\", \"countable income\", \"recipient count\"] }","The forecast stays close to the indexed current-law path; the upper interval mostly reflects higher COLA and reduced redetermination churn."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: ssi-federal-payments-fy2027\nrunLabel: Headline\nresolutionDate: 2027-11-30\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-federal-outlays-fy2027.2026-06-08T00-00-00-02-00.39eb3919ba1a28d2","runId":"run.medicaid-federal-outlays-fy2027.2026-06-08T00-00-00-02-00.39eb3919ba1a28d2","predictionId":"medicaid-federal-outlays-fy2027","specId":"spec.medicaid-federal-outlays-fy2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.19,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: policyengine.simulate({ policy: \"medicaid_current_law\", year: 2027, output: \"federal_medicaid_outlays\", unit: \"billions\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 120, distribution present, forecast step count 1.","evidence":["Federal Medicaid outlays combine enrollment, service intensity, FMAP, and state payment policy. It is a public finance cell where PolicyEngine-style eligibility modeling informs the caseload denominator, but medical cost growth drives much of the dollar risk.","Forecast: point 655, 80% interval [600, 720]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 648, ci80: [608, 704], drivers: [\"enrollment\", \"FMAP\", \"medical cost growth\"] }","The forecast centers slightly above the eligibility model because federal medical outlays have run hot relative to simple caseload forecasts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Federal Medicaid outlays combine enrollment, service intensity, FMAP, and state payment policy. It is a public finance cell where PolicyEngine-style eligibility modeling informs the caseload denominator, but medical cost growth drives much of the dollar risk."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 648, ci80: [608, 704], drivers: [\"enrollment\", \"FMAP\", \"medical cost growth\"] }","The forecast centers slightly above the eligibility model because federal medical outlays have run hot relative to simple caseload forecasts."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-federal-outlays-fy2027\nrunLabel: Headline\nresolutionDate: 2027-11-30\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.ctc-recipient-children-ty2026.2026-06-08T00-00-00-02-00.29f9764021253fba","runId":"run.ctc-recipient-children-ty2026.2026-06-08T00-00-00-02-00.29f9764021253fba","predictionId":"ctc-recipient-children-ty2026","specId":"spec.ctc-recipient-children-ty2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.19,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: policyengine.simulate({ policy: \"ctc_current_law\", year: 2026, output: \"ctc_qualifying_children\", unit: \"millions\" })","Tool result: { pre_expansion_anchor_millions: 48, expansion_outreach_peak_millions: 61 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6, distribution present, forecast step count 1.","evidence":["The interval keeps a small upside tail for outreach or refundability changes that pull non-filers into the tax system.","Forecast: point 48, 80% interval [45, 51]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["This cell forecasts a count, not dollars. It helps calibrate CTC outlay and poverty forecasts because model error often comes from who files and claims the credit, not just the statutory amount.","Tool result: { point: 47.6, ci80: [45.4, 50.2], drivers: [\"child population\", \"filing units\", \"eligibility tests\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["This cell forecasts a count, not dollars. It helps calibrate CTC outlay and poverty forecasts because model error often comes from who files and claims the credit, not just the statutory amount.","Tool result: { point: 47.6, ci80: [45.4, 50.2], drivers: [\"child population\", \"filing units\", \"eligibility tests\"] }"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: ctc-recipient-children-ty2026\nrunLabel: Headline\nresolutionDate: 2028-08-31\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.housing-choice-voucher-outlays-fy2027.2026-06-08T00-00-00-02-00.a362582e3601d027","runId":"run.housing-choice-voucher-outlays-fy2027.2026-06-08T00-00-00-02-00.a362582e3601d027","predictionId":"housing-choice-voucher-outlays-fy2027","specId":"spec.housing-choice-voucher-outlays-fy2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.19,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":["Tool call: hud.lookup({ table: \"tenant_based_rental_assistance_outlays\", years: [2021, 2026] })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Voucher outlays are constrained by appropriations but driven mechanically by rents, utilization, and tenant income. They matter for poverty forecasts because housing assistance is counted in SPM resources.","Tool call: policyengine.simulate({ policy: \"housing_assistance_current_law\", year: 2027, output: \"housing_choice_voucher_outlays\", unit: \"billions\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 10, distribution present, forecast step count 1.","evidence":["Tool result: { rent_growth_pressure: \"elevated\", utilization: \"high\", appropriation_risk: \"binding\" }","Forecast: point 36, 80% interval [32, 42]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Voucher outlays are constrained by appropriations but driven mechanically by rents, utilization, and tenant income. They matter for poverty forecasts because housing assistance is counted in SPM resources.","Tool result: { point: 35.4, ci80: [32.5, 40.2], drivers: [\"FMR growth\", \"utilization\", \"tenant income\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Voucher outlays are constrained by appropriations but driven mechanically by rents, utilization, and tenant income. They matter for poverty forecasts because housing assistance is counted in SPM resources.","Tool result: { rent_growth_pressure: \"elevated\", utilization: \"high\", appropriation_risk: \"binding\" }"]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Voucher outlays are constrained by appropriations but driven mechanically by rents, utilization, and tenant income. They matter for poverty forecasts because housing assistance is counted in SPM resources.","Tool result: { point: 35.4, ci80: [32.5, 40.2], drivers: [\"FMR growth\", \"utilization\", \"tenant income\"] }"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: housing-choice-voucher-outlays-fy2027\nrunLabel: Headline\nresolutionDate: 2027-11-30\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.payroll-tax-receipts-fy2027.2026-06-08T00-00-00-02-00.b478deea49c1e630","runId":"run.payroll-tax-receipts-fy2027.2026-06-08T00-00-00-02-00.b478deea49c1e630","predictionId":"payroll-tax-receipts-fy2027","specId":"spec.payroll-tax-receipts-fy2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":["PolicyEngine wage-tax base","The forecast sits slightly above the pure wage-base model because the taxable maximum and nominal wage growth tend to raise collections even with stable employment."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: policyengine.simulate({ policy: \"current_law\", year: 2027, output: \"payroll_tax_revenue\", unit: \"billions\" })","The forecast sits slightly above the pure wage-base model because the taxable maximum and nominal wage growth tend to raise collections even with stable employment."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 225, distribution present, forecast step count 1.","evidence":["Forecast: point 1860, 80% interval [1760, 1985]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 1850, ci80: [1775, 1960], drivers: [\"covered wages\", \"taxable maximum\", \"self-employment income\"] }","The forecast sits slightly above the pure wage-base model because the taxable maximum and nominal wage growth tend to raise collections even with stable employment."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Payroll tax receipts are a clean macro-policy bridge: the tax rate is stable, so the forecast mostly depends on covered wages, employment, and the Social Security taxable maximum.","Tool result: { point: 1850, ci80: [1775, 1960], drivers: [\"covered wages\", \"taxable maximum\", \"self-employment income\"] }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: payroll-tax-receipts-fy2027\nrunLabel: Headline\nresolutionDate: 2027-10-20\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oasdi-benefit-outlays-fy2027.2026-06-08T00-00-00-02-00.7f2cb51cc00e509d","runId":"run.oasdi-benefit-outlays-fy2027.2026-06-08T00-00-00-02-00.7f2cb51cc00e509d","predictionId":"oasdi-benefit-outlays-fy2027","specId":"spec.oasdi-benefit-outlays-fy2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.19,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool result: { beneficiary_growth: \"aging-driven\", cola_path: \"moderate\", point_billions: 1600 }","Tool call: policyengine.simulate({ year: 2027, output: \"social_security_benefits_total\", unit: \"billions\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 145, distribution present, forecast step count 1.","evidence":["OASDI benefit outlays are highly persistent. The main uncertainty is COLA inflation and beneficiary count growth, not legislative risk over this near-term horizon.","The interval is relatively tight because benefit formulas and beneficiary rolls evolve slowly; inflation is the primary residual risk."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 1608, ci80: [1548, 1678], drivers: [\"beneficiary count\", \"COLA\", \"claiming age mix\"] }","The interval is relatively tight because benefit formulas and beneficiary rolls evolve slowly; inflation is the primary residual risk."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["OASDI benefit outlays are highly persistent. The main uncertainty is COLA inflation and beneficiary count growth, not legislative risk over this near-term horizon.","The interval is relatively tight because benefit formulas and beneficiary rolls evolve slowly; inflation is the primary residual risk."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { beneficiary_growth: \"aging-driven\", cola_path: \"moderate\", point_billions: 1600 }","Tool result: { point: 1608, ci80: [1548, 1678], drivers: [\"beneficiary count\", \"COLA\", \"claiming age mix\"] }"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oasdi-benefit-outlays-fy2027\nrunLabel: Headline\nresolutionDate: 2027-11-30\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.aotc-refundable-outlays-ty2026.2026-06-08T00-00-00-02-00.cddcc00370ed0286","runId":"run.aotc-refundable-outlays-ty2026.2026-06-08T00-00-00-02-00.cddcc00370ed0286","predictionId":"aotc-refundable-outlays-ty2026","specId":"spec.aotc-refundable-outlays-ty2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.7,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: policyengine.simulate({ policy: \"current_law\", year: 2026, output: \"refundable_aotc\", unit: \"billions\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":1,"rationale":"Score 1/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3, distribution present, forecast step count 1.","evidence":["The forecast remains near the pre-2026 trend, with a wide enough interval for enrollment and tuition-cost variation.","Forecast: point 6.2, 80% interval [4.8, 7.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 6.1, ci80: [5.0, 7.4], drivers: [\"student count\", \"qualified expenses\", \"phase-outs\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The AOTC has a stable statutory design, so the forecast is mostly about enrollment and claiming behavior. This is a useful smaller-dollar calibration target for education-credit modeling.","Tool result: { point: 6.1, ci80: [5.0, 7.4], drivers: [\"student count\", \"qualified expenses\", \"phase-outs\"] }"]}],"flags":["weak_resolution_clarity","weak_counterarguments","no_ledger_target"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: aotc-refundable-outlays-ty2026\nrunLabel: Headline\nresolutionDate: 2028-08-31\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_resolution_clarity, weak_counterarguments, no_ledger_target."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.wic-average-monthly-participation-fy2027.2026-06-08T00-00-00-02-00.1bd5a566fbde6c41","runId":"run.wic-average-monthly-participation-fy2027.2026-06-08T00-00-00-02-00.1bd5a566fbde6c41","predictionId":"wic-average-monthly-participation-fy2027","specId":"spec.wic-average-monthly-participation-fy2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.05,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: policyengine.simulate({ policy: \"wic_current_law\", year: 2027, output: \"wic_participation\", unit: \"millions\" })","Tool result: { recent_trend: \"participation recovered after 2021\", official_source: \"FNS program data tables\" }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.3, distribution present, forecast step count 1.","evidence":["Forecast: point 6.9, 80% interval [6.3, 7.6]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 6.8, ci80: [6.4, 7.5], drivers: [\"eligible infants\", \"certification\", \"take-up\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The forecast keeps participation near recent elevated levels but allows downside if birth counts soften or certification churn rises."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 6.8, ci80: [6.4, 7.5], drivers: [\"eligible infants\", \"certification\", \"take-up\"] }","The forecast keeps participation near recent elevated levels but allows downside if birth counts soften or certification churn rises."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: wic-average-monthly-participation-fy2027\nrunLabel: Headline\nresolutionDate: 2028-03-31\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.national-school-lunch-participation-sy2026-27.2026-06-08T00-00-00-02-00.aac9c8a709fb5617","runId":"run.national-school-lunch-participation-sy2026-27.2026-06-08T00-00-00-02-00.aac9c8a709fb5617","predictionId":"national-school-lunch-participation-sy2026-27","specId":"spec.national-school-lunch-participation-sy2026-27","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool result: { post_universal_meals_baseline_millions: 29, state_universal_meals_tail: \"upside\" }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool result: { post_universal_meals_baseline_millions: 29, state_universal_meals_tail: \"upside\" }","Tool call: policyengine.simulate({ scenario: \"school_meals_current_law\", year: 2027, output: \"nslp_participation\", unit: \"millions\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["School lunch participation is a benefits participation forecast. It resolves to USDA FNS program data and is influenced by state policy, federal reimbursement, and school enrollment."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3.5, distribution present, forecast step count 1.","evidence":["Tool result: { post_universal_meals_baseline_millions: 29, state_universal_meals_tail: \"upside\" }","The upper tail reflects continued state universal-meals expansion and community eligibility take-up; the lower tail reflects enrollment softness and paid-meal price sensitivity."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 30.2, ci80: [28.9, 32.0], drivers: [\"free/reduced eligibility\", \"community eligibility\", \"state supplements\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["School lunch participation is a benefits participation forecast. It resolves to USDA FNS program data and is influenced by state policy, federal reimbursement, and school enrollment.","Tool result: { point: 30.2, ci80: [28.9, 32.0], drivers: [\"free/reduced eligibility\", \"community eligibility\", \"state supplements\"] }"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: national-school-lunch-participation-sy2026-27\nrunLabel: Headline\nresolutionDate: 2028-03-31\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.aca-exchange-plan-selections-oep-2027.2026-06-08T00-00-00-02-00.076a113433da7b5c","runId":"run.aca-exchange-plan-selections-oep-2027.2026-06-08T00-00-00-02-00.076a113433da7b5c","predictionId":"aca-exchange-plan-selections-oep-2027","specId":"spec.aca-exchange-plan-selections-oep-2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.84,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["The target is CMS plan selections during OEP, not effectuated enrollment later in the year. The 2027 value is highly sensitive to enhanced premium tax credit policy and premium increases visible before open enrollment.","Tool call: policyengine.simulate({ scenario: \"enhanced_ptc_expire\", year: 2027, output: \"exchange_plan_selections\", unit: \"millions\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 11, distribution present, forecast step count 1.","evidence":["Forecast: point 19.8, 80% interval [14, 25]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 16.2, ci80: [13.8, 19.8], drivers: [\"net premium shock\", \"reduced zero-premium plans\"] }","Tool result: { point: 24.0, ci80: [21.0, 26.5], drivers: [\"continued subsidy generosity\", \"auto-renewal\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 16.2, ci80: [13.8, 19.8], drivers: [\"net premium shock\", \"reduced zero-premium plans\"] }","Tool result: { point: 24.0, ci80: [21.0, 26.5], drivers: [\"continued subsidy generosity\", \"auto-renewal\"] }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: aca-exchange-plan-selections-oep-2027\nrunLabel: Headline\nresolutionDate: 2027-04-30\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicare-benefit-outlays-fy2027.2026-06-08T00-00-00-02-00.832f9ffb3cc4c5c1","runId":"run.medicare-benefit-outlays-fy2027.2026-06-08T00-00-00-02-00.832f9ffb3cc4c5c1","predictionId":"medicare-benefit-outlays-fy2027","specId":"spec.medicare-benefit-outlays-fy2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: cbo.lookup({ table: \"budget_baseline\", series: \"medicare\", year: \"FY2027\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: policyengine.simulate({ year: 2027, output: \"medicare_benefit_outlays\", unit: \"billions\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 175, distribution present, forecast step count 1.","evidence":["Medicare outlays are a large, persistent budget cell. Near-term uncertainty is dominated by payment updates, beneficiary mix, Medicare Advantage benchmarks, and prescription-drug spending.","Tool result: { trend: \"above nominal GDP growth\", residual_risk: \"payment updates and drug spending\" }"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 1102, ci80: [1048, 1192], drivers: [\"beneficiary count\", \"MA benchmarks\", \"Part D spending\"] }","The point estimate is slightly above the simple roll-forward because recent Medicare spending has run hot in Medicare Advantage and outpatient components."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Medicare outlays are a large, persistent budget cell. Near-term uncertainty is dominated by payment updates, beneficiary mix, Medicare Advantage benchmarks, and prescription-drug spending.","Tool result: { trend: \"above nominal GDP growth\", residual_risk: \"payment updates and drug spending\" }"]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 1102, ci80: [1048, 1192], drivers: [\"beneficiary count\", \"MA benchmarks\", \"Part D spending\"] }","The point estimate is slightly above the simple roll-forward because recent Medicare spending has run hot in Medicare Advantage and outpatient components."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicare-benefit-outlays-fy2027\nrunLabel: Headline\nresolutionDate: 2027-11-30\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: resolution clarity (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.tanf-federal-outlays-fy2027.2026-06-08T00-00-00-02-00.f17acbdd04eb14ff","runId":"run.tanf-federal-outlays-fy2027.2026-06-08T00-00-00-02-00.f17acbdd04eb14ff","predictionId":"tanf-federal-outlays-fy2027","specId":"spec.tanf-federal-outlays-fy2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.19,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: policyengine.simulate({ policy: \"tanf_current_law\", year: 2027, output: \"tanf_federal_outlays\", unit: \"billions\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.5, distribution present, forecast step count 1.","evidence":["TANF federal spending is relatively flat because the core block grant is nominally fixed. The main risk is reauthorization, contingency funding, and state transfer behavior rather than caseload alone.","Tool result: { block_grant_nominally_flat: true, transfers_to_ccdf: \"variable\", contingency_fund_risk: \"small\" }"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["TANF federal spending is relatively flat because the core block grant is nominally fixed. The main risk is reauthorization, contingency funding, and state transfer behavior rather than caseload alone.","Tool result: { point: 16.8, ci80: [15.4, 18.8], drivers: [\"block grant\", \"state transfers\", \"caseload\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["TANF federal spending is relatively flat because the core block grant is nominally fixed. The main risk is reauthorization, contingency funding, and state transfer behavior rather than caseload alone.","Tool result: { block_grant_nominally_flat: true, transfers_to_ccdf: \"variable\", contingency_fund_risk: \"small\" }"]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 16.8, ci80: [15.4, 18.8], drivers: [\"block grant\", \"state transfers\", \"caseload\"] }","The forecast stays near the nominal block-grant path, with a modest upper tail for reauthorization or contingency-fund use."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: tanf-federal-outlays-fy2027\nrunLabel: Headline\nresolutionDate: 2028-03-31\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.ccdf-outlays-fy2027.2026-06-08T00-00-00-02-00.98b32b8cca96f1b5","runId":"run.ccdf-outlays-fy2027.2026-06-08T00-00-00-02-00.98b32b8cca96f1b5","predictionId":"ccdf-outlays-fy2027","specId":"spec.ccdf-outlays-fy2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["CCDF is a program-finance cell where appropriations and state spending rules matter as much as eligible-family demand. ACF-696 expenditure data provide the resolution surface.","Tool call: policyengine.simulate({ policy: \"ccdf_current_law\", year: 2027, output: \"child_care_subsidy_outlays\", unit: \"billions\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 8, distribution present, forecast step count 1.","evidence":["The interval is wider than TANF because appropriations and state rate-setting can move subsidy spending more than the underlying eligible population.","Forecast: point 12.5, 80% interval [9, 17]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 12.1, ci80: [9.4, 16.2], drivers: [\"appropriations\", \"eligible children\", \"state copay policy\"] }","The interval is wider than TANF because appropriations and state rate-setting can move subsidy spending more than the underlying eligible population."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 12.1, ci80: [9.4, 16.2], drivers: [\"appropriations\", \"eligible children\", \"state copay policy\"] }","The interval is wider than TANF because appropriations and state rate-setting can move subsidy spending more than the underlying eligible population."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: ccdf-outlays-fy2027\nrunLabel: Headline\nresolutionDate: 2028-03-31\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.estate-gift-tax-receipts-fy2027.2026-06-08T00-00-00-02-00.8c0ea7c3c0df40cc","runId":"run.estate-gift-tax-receipts-fy2027.2026-06-08T00-00-00-02-00.8c0ea7c3c0df40cc","predictionId":"estate-gift-tax-receipts-fy2027","specId":"spec.estate-gift-tax-receipts-fy2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.95,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: policyengine.simulate({ policy: \"estate_tax_current_law\", year: 2027, output: \"estate_gift_tax_receipts\", unit: \"billions\" })","Tool call: policyengine.simulate({ policy: \"tcja_estate_exemption_extended\", year: 2027, output: \"estate_gift_tax_receipts\", unit: \"billions\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 44, distribution present, forecast step count 1.","evidence":["Forecast: point 45, 80% interval [28, 72]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 52, ci80: [35, 78], drivers: [\"exemption sunset\", \"asset values\", \"gift timing\"] }","Tool result: { point: 34, ci80: [24, 51], drivers: [\"high exemption retained\", \"planning behavior\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Estate and gift tax receipts are volatile and policy-sensitive. The scheduled exemption path and taxpayer planning around any TCJA-extension package dominate the 2027 distribution."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 52, ci80: [35, 78], drivers: [\"exemption sunset\", \"asset values\", \"gift timing\"] }","Tool result: { point: 34, ci80: [24, 51], drivers: [\"high exemption retained\", \"planning behavior\"] }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: estate-gift-tax-receipts-fy2027\nrunLabel: Headline\nresolutionDate: 2027-10-20\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.eitc-claimant-returns-ty2027.2026-06-08T00-00-00-02-00.53da4df5e51bb544","runId":"run.eitc-claimant-returns-ty2027.2026-06-08T00-00-00-02-00.53da4df5e51bb544","predictionId":"eitc-claimant-returns-ty2027","specId":"spec.eitc-claimant-returns-ty2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3.9, distribution present, forecast step count 1.","evidence":["Forecast: point 23.4, 80% interval [21.6, 25.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 23.5, ci80: [21.8, 25.3], drivers: [\"earnings distribution\", \"children\", \"filing take-up\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Tool result: { point: 23.5, ci80: [21.8, 25.3], drivers: [\"earnings distribution\", \"children\", \"filing take-up\"] }"]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["This cell forecasts returns claiming EITC, not dollars paid. It gives the EITC outlay forecast a separate take-up target that can be calibrated against IRS administrative data.","Tool result: { point: 23.5, ci80: [21.8, 25.3], drivers: [\"earnings distribution\", \"children\", \"filing take-up\"] }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: eitc-claimant-returns-ty2027\nrunLabel: Headline\nresolutionDate: 2029-12-31\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.corporate-income-tax-receipts-fy2027.2026-06-08T00-00-00-02-00.99cdeb1191372899","runId":"run.corporate-income-tax-receipts-fy2027.2026-06-08T00-00-00-02-00.99cdeb1191372899","predictionId":"corporate-income-tax-receipts-fy2027","specId":"spec.corporate-income-tax-receipts-fy2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.14,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and explicit outside-view language.","evidence":["Corporation income tax receipts are more volatile than wage-based receipts because profits, loss carryforwards, bonus depreciation, and estimated-payment timing all move the cash series.","Baseline receipts projection"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: policyengine.simulate({ scenario: \"business_tax_baseline_2027\", output: \"corporate_income_tax_receipts\", unit: \"billions\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 300, distribution present, forecast step count 1.","evidence":["Central case rounds the fiscal cash forecast to $570B with a wide profit-cycle interval.","Forecast: point 570, 80% interval [430, 730]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Corporation income tax receipts are more volatile than wage-based receipts because profits, loss carryforwards, bonus depreciation, and estimated-payment timing all move the cash series.","Tool result: { point: 565, ci80: [440, 710], drivers: [\"profits\", \"depreciation\", \"international minimum taxes\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 565, ci80: [440, 710], drivers: [\"profits\", \"depreciation\", \"international minimum taxes\"] }","Central case rounds the fiscal cash forecast to $570B with a wide profit-cycle interval."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: corporate-income-tax-receipts-fy2027\nrunLabel: Headline\nresolutionDate: 2027-10-20\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-average-monthly-participation-fy2027.2026-06-08T00-00-00-02-00.c058bab1e2486589","runId":"run.snap-average-monthly-participation-fy2027.2026-06-08T00-00-00-02-00.c058bab1e2486589","predictionId":"snap-average-monthly-participation-fy2027","specId":"spec.snap-average-monthly-participation-fy2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.84,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["This cell forecasts average monthly persons, not annual unique participants and not benefit dollars. It gives the outlay forecast a separate take-up and caseload calibration target.","Tool call: fns.lookup({ program: \"SNAP\", series: \"average_monthly_persons\", fiscal_years: [2021, 2024] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6.7, distribution present, forecast step count 1.","evidence":["Forecast: point 40.6, 80% interval [37.4, 44.1]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 40.4, ci80: [37.6, 43.7], drivers: [\"eligibility\", \"take-up\", \"recertification\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["This cell forecasts average monthly persons, not annual unique participants and not benefit dollars. It gives the outlay forecast a separate take-up and caseload calibration target.","Tool result: { point: 40.4, ci80: [37.6, 43.7], drivers: [\"eligibility\", \"take-up\", \"recertification\"] }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-average-monthly-participation-fy2027\nrunLabel: Headline\nresolutionDate: 2028-03-31\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.pell-grant-recipients-ay2027.2026-06-08T00-00-00-02-00.344554579b2f3219","runId":"run.pell-grant-recipients-ay2027.2026-06-08T00-00-00-02-00.344554579b2f3219","predictionId":"pell-grant-recipients-ay2027","specId":"spec.pell-grant-recipients-ay2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.84,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":["Base 6.8M + 0.25M simplification take-up + 0.15M enrollment drift ≈ 7.2M"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Pell recipients are an access target for low-income students. The 2027-28 value is driven by FAFSA simplification, enrollment, and whether appropriations maintain eligibility generosity."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.8, distribution present, forecast step count 1.","evidence":["Forecast: point 7.2, 80% interval [6.4, 8.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 7.15, ci80: [6.45, 8.05], drivers: [\"SAI formula\", \"enrollment\", \"completion rate\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 7.15, ci80: [6.45, 8.05], drivers: [\"SAI formula\", \"enrollment\", \"completion rate\"] }","Forecast: point 7.2, 80% interval [6.4, 8.2]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: pell-grant-recipients-ay2027\nrunLabel: Headline\nresolutionDate: 2029-02-28\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.head-start-funded-enrollment-fy2027.2026-06-08T00-00-00-02-00.32fb6d585302f20b","runId":"run.head-start-funded-enrollment-fy2027.2026-06-08T00-00-00-02-00.32fb6d585302f20b","predictionId":"head-start-funded-enrollment-fy2027","specId":"spec.head-start-funded-enrollment-fy2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.14,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: policyengine.simulate({ program: \"head_start\", year: 2027, output: \"funded_slots\", budget: \"appropriations_baseline\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: policyengine.simulate({ program: \"head_start\", year: 2027, output: \"funded_slots\", budget: \"appropriations_baseline\" })","Tool result: { point: 0.82, ci80: [0.75, 0.89], drivers: [\"appropriations\", \"cost per slot\", \"workforce\"] }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.16, distribution present, forecast step count 1.","evidence":["Forecast: point 0.82, 80% interval [0.74, 0.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Funded enrollment measures capacity rather than actual attendance. It is a clean public resolution target for early-childhood benefit access because ACF reports it through Head Start program data.","Tool result: { point: 0.82, ci80: [0.75, 0.89], drivers: [\"appropriations\", \"cost per slot\", \"workforce\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 0.82, ci80: [0.75, 0.89], drivers: [\"appropriations\", \"cost per slot\", \"workforce\"] }","Forecast: point 0.82, 80% interval [0.74, 0.9]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: head-start-funded-enrollment-fy2027\nrunLabel: Headline\nresolutionDate: 2028-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.tanf-average-monthly-families-fy2027.2026-06-08T00-00-00-02-00.944ea7c0ee14e144","runId":"run.tanf-average-monthly-families-fy2027.2026-06-08T00-00-00-02-00.944ea7c0ee14e144","predictionId":"tanf-average-monthly-families-fy2027","specId":"spec.tanf-average-monthly-families-fy2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.22,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool result: { point: 0.71, ci80: [0.63, 0.83], drivers: [\"state diversion\", \"sanctions\", \"need\"] }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["TANF outlays can stay roughly flat even while cash-assistance caseloads change, because states can move funds into work supports, child care, or other allowable activities. This cell resolves the family cash-assistance caseload directly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.23, distribution present, forecast step count 1.","evidence":["Trend case holds the FY2024 plateau with a mild recession tail: central case 0.72M families.","Forecast: point 0.72, 80% interval [0.62, 0.85]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["TANF outlays can stay roughly flat even while cash-assistance caseloads change, because states can move funds into work supports, child care, or other allowable activities. This cell resolves the family cash-assistance caseload directly.","Tool result: { point: 0.71, ci80: [0.63, 0.83], drivers: [\"state diversion\", \"sanctions\", \"need\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 0.71, ci80: [0.63, 0.83], drivers: [\"state diversion\", \"sanctions\", \"need\"] }","Forecast: point 0.72, 80% interval [0.62, 0.85]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: tanf-average-monthly-families-fy2027\nrunLabel: Headline\nresolutionDate: 2028-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.ccdf-average-monthly-children-served-fy2027.2026-06-08T00-00-00-02-00.e00143acced0ea6f","runId":"run.ccdf-average-monthly-children-served-fy2027.2026-06-08T00-00-00-02-00.e00143acced0ea6f","predictionId":"ccdf-average-monthly-children-served-fy2027","specId":"spec.ccdf-average-monthly-children-served-fy2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.08,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: policyengine.simulate({ program: \"ccdf\", year: 2027, output: \"children_served\", takeup: \"waiting_list_constrained\" })","Tool result: { point: 1.34, ci80: [1.08, 1.71], drivers: [\"appropriations\", \"prices\", \"eligibility\"] }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.7, distribution present, forecast step count 1.","evidence":["Forecast: point 1.36, 80% interval [1.05, 1.75]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The service-count target captures whether dollars become slots. It is especially important for evaluating child care policy because higher provider reimbursement can raise cost per child while reducing waiting lists.","Tool result: { point: 1.34, ci80: [1.08, 1.71], drivers: [\"appropriations\", \"prices\", \"eligibility\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Central case lets pandemic-era funding unwind but assumes states preserve some rate increases: 1.36M children."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 1.34, ci80: [1.08, 1.71], drivers: [\"appropriations\", \"prices\", \"eligibility\"] }","Forecast: point 1.36, 80% interval [1.05, 1.75]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: ccdf-average-monthly-children-served-fy2027\nrunLabel: Headline\nresolutionDate: 2029-03-31\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.liheap-households-assisted-fy2027.2026-06-08T00-00-00-02-00.f0d44d126e5c2b1d","runId":"run.liheap-households-assisted-fy2027.2026-06-08T00-00-00-02-00.f0d44d126e5c2b1d","predictionId":"liheap-households-assisted-fy2027","specId":"spec.liheap-households-assisted-fy2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.19,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["LIHEAP is a useful stress-test cell because household counts can move in opposite directions from average benefit size. A cold winter or high energy prices may raise applications while fixed funding limits the number served.","Tool result: { point: 5.0, ci80: [3.6, 6.7], drivers: [\"appropriations\", \"energy prices\", \"weather\"] }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3.5, distribution present, forecast step count 1.","evidence":["Funding risk dominates: elimination or deep reduction creates the lower tail; normal block-grant funding keeps households near 5M.","Forecast: point 5.1, 80% interval [3.4, 6.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["LIHEAP is a useful stress-test cell because household counts can move in opposite directions from average benefit size. A cold winter or high energy prices may raise applications while fixed funding limits the number served.","Tool result: { point: 5.0, ci80: [3.6, 6.7], drivers: [\"appropriations\", \"energy prices\", \"weather\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Funding risk dominates: elimination or deep reduction creates the lower tail; normal block-grant funding keeps households near 5M."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 5.0, ci80: [3.6, 6.7], drivers: [\"appropriations\", \"energy prices\", \"weather\"] }","Forecast: point 5.1, 80% interval [3.4, 6.9]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: liheap-households-assisted-fy2027\nrunLabel: Headline\nresolutionDate: 2029-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.school-breakfast-participation-sy2026-27.2026-06-08T00-00-00-02-00.54d4aa5fccc01148","runId":"run.school-breakfast-participation-sy2026-27.2026-06-08T00-00-00-02-00.54d4aa5fccc01148","predictionId":"school-breakfast-participation-sy2026-27","specId":"spec.school-breakfast-participation-sy2026-27","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.7, distribution present, forecast step count 1.","evidence":["Forecast: point 15.2, 80% interval [14, 16.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Breakfast participation is a separate nutrition access indicator from lunch because many districts have different delivery models, stigma effects, and state universal-meals supplements.","Tool result: { point: 15.3, ci80: [14.1, 16.6], drivers: [\"CEP\", \"state supplements\", \"attendance\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 15.3, ci80: [14.1, 16.6], drivers: [\"CEP\", \"state supplements\", \"attendance\"] }","Forecast: point 15.2, 80% interval [14, 16.7]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: school-breakfast-participation-sy2026-27\nrunLabel: Headline\nresolutionDate: 2028-03-31\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.ssi-recipients-dec-2027.2026-06-08T00-00-00-02-00.a82e0161e9800985","runId":"run.ssi-recipients-dec-2027.2026-06-08T00-00-00-02-00.a82e0161e9800985","predictionId":"ssi-recipients-dec-2027","specId":"spec.ssi-recipients-dec-2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.65, distribution present, forecast step count 1.","evidence":["Forecast: point 7.35, 80% interval [7.05, 7.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 7.34, ci80: [7.08, 7.66], drivers: [\"awards\", \"reviews\", \"aging\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["SSI federal payments already forecast dollars; this cell forecasts people receiving SSI. It lets an agent separate caseload from benefit-level and COLA effects.","Tool result: { point: 7.34, ci80: [7.08, 7.66], drivers: [\"awards\", \"reviews\", \"aging\"] }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: ssi-recipients-dec-2027\nrunLabel: Headline\nresolutionDate: 2028-02-28\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-average-monthly-households-fy2027.2026-06-08T00-00-00-02-00.61d07174930550f1","runId":"run.snap-average-monthly-households-fy2027.2026-06-08T00-00-00-02-00.61d07174930550f1","predictionId":"snap-average-monthly-households-fy2027","specId":"spec.snap-average-monthly-households-fy2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["SNAP persons and benefit dollars can move for different reasons. Household participation is the administrative count closest to caseload pressure and state operations.","Persons forecast of 40.6M divided by a projected recipient household size of 1.87 gives 21.7M households."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Forecast: point 21.7, 80% interval [19.8, 23.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["SNAP persons and benefit dollars can move for different reasons. Household participation is the administrative count closest to caseload pressure and state operations.","Tool result: { point: 21.6, ci80: [20.0, 23.5], drivers: [\"eligibility\", \"take-up\", \"household size\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 21.6, ci80: [20.0, 23.5], drivers: [\"eligibility\", \"take-up\", \"household size\"] }","Persons forecast of 40.6M divided by a projected recipient household size of 1.87 gives 21.7M households."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-average-monthly-households-fy2027\nrunLabel: Headline\nresolutionDate: 2028-03-31\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-chip-child-enrollment-dec-2027.2026-06-08T00-00-00-02-00.4e9bb5196d54531a","runId":"run.medicaid-chip-child-enrollment-dec-2027.2026-06-08T00-00-00-02-00.4e9bb5196d54531a","predictionId":"medicaid-chip-child-enrollment-dec-2027","specId":"spec.medicaid-chip-child-enrollment-dec-2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.9, distribution present, forecast step count 1.","evidence":["Forecast: point 36.8, 80% interval [34.5, 39.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Total Medicaid and CHIP enrollment mixes adults and children. The child count is the cleaner policy target for poverty and family-benefit forecasting because children face different eligibility and continuity rules.","Tool result: { point: 36.7, ci80: [34.8, 39.1], drivers: [\"eligibility\", \"renewals\", \"CHIP premiums\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Total Medicaid and CHIP enrollment mixes adults and children. The child count is the cleaner policy target for poverty and family-benefit forecasting because children face different eligibility and continuity rules.","Tool result: { point: 36.7, ci80: [34.8, 39.1], drivers: [\"eligibility\", \"renewals\", \"CHIP premiums\"] }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-chip-child-enrollment-dec-2027\nrunLabel: Headline\nresolutionDate: 2028-04-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.housing-choice-voucher-households-leased-dec-2027.2026-06-08T00-00-00-02-00.6534edb16734e751","runId":"run.housing-choice-voucher-households-leased-dec-2027.2026-06-08T00-00-00-02-00.6534edb16734e751","predictionId":"housing-choice-voucher-households-leased-dec-2027","specId":"spec.housing-choice-voucher-households-leased-dec-2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: policyengine.simulate({ program: \"housing_choice_voucher\", year: 2027, month: \"december\", output: \"households_leased\", budget: \"appropriations_baseline\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Voucher outlays are already in the catalog; leased households isolate whether appropriations and rent inflation translate into families actually housed.","Tool call: policyengine.simulate({ program: \"housing_choice_voucher\", year: 2027, month: \"december\", output: \"households_leased\", budget: \"appropriations_baseline\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.34, distribution present, forecast step count 1.","evidence":["Forecast: point 2.34, 80% interval [2.18, 2.52]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 2.33, ci80: [2.20, 2.49], drivers: [\"appropriations\", \"rents\", \"lease-up\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Central case is near-flat leasing: appropriations offset rent inflation enough to hold 2.3-2.4M households."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 2.33, ci80: [2.20, 2.49], drivers: [\"appropriations\", \"rents\", \"lease-up\"] }","Forecast: point 2.34, 80% interval [2.18, 2.52]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: housing-choice-voucher-households-leased-dec-2027\nrunLabel: Headline\nresolutionDate: 2028-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.school-breakfast-federal-outlays-fy2027.2026-06-08T00-00-00-02-00.4826a8aac7557e9d","runId":"run.school-breakfast-federal-outlays-fy2027.2026-06-08T00-00-00-02-00.4826a8aac7557e9d","predictionId":"school-breakfast-federal-outlays-fy2027","specId":"spec.school-breakfast-federal-outlays-fy2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: policyengine.simulate({ program: \"school_breakfast\", year: 2027, output: \"federal_cost\", unit: \"billions\", reimbursement_rates: \"indexed\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2, distribution present, forecast step count 1.","evidence":["Forecast: point 6.7, 80% interval [5.8, 7.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 6.6, ci80: [5.9, 7.6], drivers: [\"participation\", \"meal mix\", \"rate indexation\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 6.6, ci80: [5.9, 7.6], drivers: [\"participation\", \"meal mix\", \"rate indexation\"] }","Forecast: point 6.7, 80% interval [5.8, 7.8]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: school-breakfast-federal-outlays-fy2027\nrunLabel: Headline\nresolutionDate: 2028-03-31\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.child-support-distributed-collections-fy2027.2026-06-08T00-00-00-02-00.1cf3276c19712dbf","runId":"run.child-support-distributed-collections-fy2027.2026-06-08T00-00-00-02-00.1cf3276c19712dbf","predictionId":"child-support-distributed-collections-fy2027","specId":"spec.child-support-distributed-collections-fy2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.05,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Child support collections are not a federal benefit outlay, but they are a measured family-resource flow that matters for poverty forecasts and policy simulations of custodial families.","Tool call: acf.lookup({ office: \"OCSS\", series: \"distributed_collections\", fiscal_years: [2019, 2024] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6, distribution present, forecast step count 1.","evidence":["Nominal earnings growth offsets caseload decline: $27.0B × 1.03^3 ≈ $29.5B, haircut for enforcement/caseload risk gives $27.8B.","Forecast: point 27.8, 80% interval [25, 31]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 27.7, ci80: [25.2, 30.7], drivers: [\"earnings\", \"caseload\", \"enforcement\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Child support collections are not a federal benefit outlay, but they are a measured family-resource flow that matters for poverty forecasts and policy simulations of custodial families.","Tool call: acf.lookup({ office: \"OCSS\", series: \"distributed_collections\", fiscal_years: [2019, 2024] })"]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Child support collections are not a federal benefit outlay, but they are a measured family-resource flow that matters for poverty forecasts and policy simulations of custodial families.","Tool result: { point: 27.7, ci80: [25.2, 30.7], drivers: [\"earnings\", \"caseload\", \"enforcement\"] }"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: child-support-distributed-collections-fy2027\nrunLabel: Headline\nresolutionDate: 2028-12-31\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.pell-grant-outlays-fy2027.2026-06-08T00-00-00-02-00.b6778ca60047b415","runId":"run.pell-grant-outlays-fy2027.2026-06-08T00-00-00-02-00.b6778ca60047b415","predictionId":"pell-grant-outlays-fy2027","specId":"spec.pell-grant-outlays-fy2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.95,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: policyengine.simulate({ program: \"pell\", year: 2027, output: \"grant_outlays\", unit: \"billions\", takeup: \"fafsa_simplification\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 15, distribution present, forecast step count 1.","evidence":["Forecast: point 34.5, 80% interval [28, 43]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 34.2, ci80: [28.6, 41.8], drivers: [\"recipients\", \"maximum_award\", \"SAI distribution\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Tool result: { point: 34.2, ci80: [28.6, 41.8], drivers: [\"recipients\", \"maximum_award\", \"SAI distribution\"] }"]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The catalog already forecasts Pell recipients. This cell forecasts fiscal cost, which can diverge if the maximum award or average Student Aid Index changes faster than enrollment.","Tool result: { point: 34.2, ci80: [28.6, 41.8], drivers: [\"recipients\", \"maximum_award\", \"SAI distribution\"] }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: pell-grant-outlays-fy2027\nrunLabel: Headline\nresolutionDate: 2028-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.wic-federal-outlays-fy2027.2026-06-08T00-00-00-02-00.b0b65342d1ec171a","runId":"run.wic-federal-outlays-fy2027.2026-06-08T00-00-00-02-00.b0b65342d1ec171a","predictionId":"wic-federal-outlays-fy2027","specId":"spec.wic-federal-outlays-fy2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.84,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: policyengine.simulate({ program: \"wic\", year: 2027, output: \"federal_cost\", unit: \"billions\", food_inflation: \"cbo_food_at_home\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.8, distribution present, forecast step count 1.","evidence":["Forecast: point 8.5, 80% interval [7.2, 10]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 8.4, ci80: [7.3, 9.8], drivers: [\"participation\", \"food_package\", \"rebates\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 8.4, ci80: [7.3, 9.8], drivers: [\"participation\", \"food_package\", \"rebates\"] }","Forecast: point 8.5, 80% interval [7.2, 10]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: wic-federal-outlays-fy2027\nrunLabel: Headline\nresolutionDate: 2028-03-31\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.liheap-federal-funding-fy2027.2026-06-08T00-00-00-02-00.7ff0da5a40f18b56","runId":"run.liheap-federal-funding-fy2027.2026-06-08T00-00-00-02-00.7ff0da5a40f18b56","predictionId":"liheap-federal-funding-fy2027","specId":"spec.liheap-federal-funding-fy2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: policyengine.simulate({ program: \"liheap\", year: 2027, output: \"federal_funding\", unit: \"billions\", appropriation: \"baseline_plus_tail\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: policyengine.simulate({ program: \"liheap\", year: 2027, output: \"federal_funding\", unit: \"billions\", appropriation: \"baseline_plus_tail\" })","Tool result: { point: 4.0, ci80: [2.6, 6.4], drivers: [\"appropriations\", \"energy_prices\", \"weather\"] }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.4, distribution present, forecast step count 1.","evidence":["Tool call: policyengine.simulate({ program: \"liheap\", year: 2027, output: \"federal_funding\", unit: \"billions\", appropriation: \"baseline_plus_tail\" })","Regular funding near $4B with a disaster/energy-price supplemental tail gives a wide upper interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 4.0, ci80: [2.6, 6.4], drivers: [\"appropriations\", \"energy_prices\", \"weather\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The existing LIHEAP cell forecasts households assisted. This cell forecasts the federal funding envelope, which determines whether states serve more households or increase benefit amounts.","Tool result: { point: 4.0, ci80: [2.6, 6.4], drivers: [\"appropriations\", \"energy_prices\", \"weather\"] }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: liheap-federal-funding-fy2027\nrunLabel: Headline\nresolutionDate: 2028-03-31\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oasdi-beneficiaries-dec-2027.2026-06-08T00-00-00-02-00.f27ed6b0d6923a2e","runId":"run.oasdi-beneficiaries-dec-2027.2026-06-08T00-00-00-02-00.f27ed6b0d6923a2e","predictionId":"oasdi-beneficiaries-dec-2027","specId":"spec.oasdi-beneficiaries-dec-2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.6, distribution present, forecast step count 1.","evidence":["Forecast: point 70, 80% interval [68.8, 71.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 70.0, ci80: [68.9, 71.2], drivers: [\"aging\", \"claiming\", \"mortality\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The catalog already forecasts OASDI benefit outlays. Beneficiary count isolates the demographic component from COLA and average-benefit growth.","Tool result: { point: 70.0, ci80: [68.9, 71.2], drivers: [\"aging\", \"claiming\", \"mortality\"] }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oasdi-beneficiaries-dec-2027\nrunLabel: Headline\nresolutionDate: 2028-02-28\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.dependent-care-credit-claimant-returns-ty2026.2026-06-08T00-00-00-02-00.c19f49e065b3e452","runId":"run.dependent-care-credit-claimant-returns-ty2026.2026-06-08T00-00-00-02-00.c19f49e065b3e452","predictionId":"dependent-care-credit-claimant-returns-ty2026","specId":"spec.dependent-care-credit-claimant-returns-ty2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2, distribution present, forecast step count 1.","evidence":["Forecast: point 5.9, 80% interval [5, 7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The child and dependent care credit is a direct PolicyEngine-relevant tax unit output. Claimant returns are useful because the nonrefundable credit can have stable claims even when revenue cost changes with income and tax liability.","Tool result: { point: 5.9, ci80: [5.1, 6.8], drivers: [\"childcare_expenses\", \"earned_income\", \"tax_liability\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 5.9, ci80: [5.1, 6.8], drivers: [\"childcare_expenses\", \"earned_income\", \"tax_liability\"] }","Forecast: point 5.9, 80% interval [5, 7]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: dependent-care-credit-claimant-returns-ty2026\nrunLabel: Headline\nresolutionDate: 2028-12-31\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.premium-tax-credit-claimant-returns-ty2026.2026-06-08T00-00-00-02-00.162b2c59109dd7fb","runId":"run.premium-tax-credit-claimant-returns-ty2026.2026-06-08T00-00-00-02-00.162b2c59109dd7fb","predictionId":"premium-tax-credit-claimant-returns-ty2026","specId":"spec.premium-tax-credit-claimant-returns-ty2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.92,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 7.8, distribution present, forecast step count 1.","evidence":["Forecast: point 10.8, 80% interval [7.4, 15.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["This cell turns ACA coverage policy into an IRS administrative count. It should move with exchange enrollment but not one-for-one because family members aggregate onto tax returns and some households only reconcile advance credits.","Tool result: { point: 10.7, ci80: [7.8, 14.8], drivers: [\"subsidy schedule\", \"exchange enrollment\", \"filing behavior\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["This cell turns ACA coverage policy into an IRS administrative count. It should move with exchange enrollment but not one-for-one because family members aggregate onto tax returns and some households only reconcile advance credits."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 10.7, ci80: [7.8, 14.8], drivers: [\"subsidy schedule\", \"exchange enrollment\", \"filing behavior\"] }","Forecast: point 10.8, 80% interval [7.4, 15.2]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: premium-tax-credit-claimant-returns-ty2026\nrunLabel: Headline\nresolutionDate: 2028-12-31\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.additional-child-tax-credit-claimant-returns-ty2026.2026-06-08T00-00-00-02-00.b75a8420a294b734","runId":"run.additional-child-tax-credit-claimant-returns-ty2026.2026-06-08T00-00-00-02-00.b75a8420a294b734","predictionId":"additional-child-tax-credit-claimant-returns-ty2026","specId":"spec.additional-child-tax-credit-claimant-returns-ty2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6.4, distribution present, forecast step count 1.","evidence":["Forecast: point 16.2, 80% interval [13.2, 19.6]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 16.1, ci80: [13.6, 19.2], drivers: [\"phase_in\", \"refundability_cap\", \"eligible_children\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 16.1, ci80: [13.6, 19.2], drivers: [\"phase_in\", \"refundability_cap\", \"eligible_children\"] }","Forecast: point 16.2, 80% interval [13.2, 19.6]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: additional-child-tax-credit-claimant-returns-ty2026\nrunLabel: Headline\nresolutionDate: 2028-12-31\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.charitable-contributions-deduction-ty2026.2026-06-08T00-00-00-02-00.1309812fc9faa8a4","runId":"run.charitable-contributions-deduction-ty2026.2026-06-08T00-00-00-02-00.1309812fc9faa8a4","predictionId":"charitable-contributions-deduction-ty2026","specId":"spec.charitable-contributions-deduction-ty2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.05,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Charitable deductions connect tax policy to nonprofit funding behavior. The forecast is sensitive to whether itemization remains constrained by a high standard deduction and SALT cap.","Tool call: irs.lookup({ dataset: \"statistics_of_income\", table: \"itemized_deductions\", series: \"charitable_contributions\", tax_years: [2019, 2023] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 130, distribution present, forecast step count 1.","evidence":["Nominal giving growth plus itemization-policy uncertainty: $285B · 1.023^3 ≈ $305B.","Forecast: point 305, 80% interval [245, 375]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 302, ci80: [252, 365], drivers: [\"itemizers\", \"asset_prices\", \"deduction_law\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool call: irs.lookup({ dataset: \"statistics_of_income\", table: \"itemized_deductions\", series: \"charitable_contributions\", tax_years: [2019, 2023] })","Tool call: policyengine.simulate({ deduction: \"charitable_contributions\", year: 2026, output: \"itemized_amount\", unit: \"billions\", behavior: \"giving_elasticity_central\" })"]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Charitable deductions connect tax policy to nonprofit funding behavior. The forecast is sensitive to whether itemization remains constrained by a high standard deduction and SALT cap.","Tool result: { point: 302, ci80: [252, 365], drivers: [\"itemizers\", \"asset_prices\", \"deduction_law\"] }"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: charitable-contributions-deduction-ty2026\nrunLabel: Headline\nresolutionDate: 2028-12-31\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicare-total-enrollment-dec-2027.2026-06-08T00-00-00-02-00.3a3595fcc8206de9","runId":"run.medicare-total-enrollment-dec-2027.2026-06-08T00-00-00-02-00.3a3595fcc8206de9","predictionId":"medicare-total-enrollment-dec-2027","specId":"spec.medicare-total-enrollment-dec-2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":["Recent 0.9-1.1M annual growth from the January 2026 base implies about 70.7M by December 2027."]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3.1, distribution present, forecast step count 1.","evidence":["Forecast: point 70.7, 80% interval [69.2, 72.3]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 70.6, ci80: [69.4, 72.0], drivers: [\"age_65_entries\", \"mortality\", \"disability\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Medicare benefit outlays combine enrollment, benefit mix, and health-care prices. Total enrollment gives the demographic denominator for those spending forecasts.","Tool result: { point: 70.6, ci80: [69.4, 72.0], drivers: [\"age_65_entries\", \"mortality\", \"disability\"] }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicare-total-enrollment-dec-2027\nrunLabel: Headline\nresolutionDate: 2028-03-31\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.retired-worker-average-benefit-dec-2027.2026-06-08T00-00-00-02-00.728cc048c74d94f9","runId":"run.retired-worker-average-benefit-dec-2027.2026-06-08T00-00-00-02-00.728cc048c74d94f9","predictionId":"retired-worker-average-benefit-dec-2027","specId":"spec.retired-worker-average-benefit-dec-2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":["$2,090 base × 1.035 COLA/benefit-mix growth ≈ $2,163, with new-award cohort replacement lifting the central estimate to $2,190."]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 175, distribution present, forecast step count 1.","evidence":["Forecast: point 2190, 80% interval [2110, 2285]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 2185, ci80: [2120, 2270], drivers: [\"cola\", \"new_awards\", \"claiming_age\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: policyengine.simulate({ program: \"oasdi\", year: 2027, month: \"december\", output: \"retired_worker_average_benefit\", cola: \"cpi_w_forecast\" })","Tool result: { point: 2185, ci80: [2120, 2270], drivers: [\"cola\", \"new_awards\", \"claiming_age\"] }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: retired-worker-average-benefit-dec-2027\nrunLabel: Headline\nresolutionDate: 2028-02-28\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.ctc-refundable-amount-ty2027.2026-06-08T00-00-00-02-00.b42ecf49b024dd59","runId":"run.ctc-refundable-amount-ty2027.2026-06-08T00-00-00-02-00.b42ecf49b024dd59","predictionId":"ctc-refundable-amount-ty2027","specId":"spec.ctc-refundable-amount-ty2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: policyengine.simulate({ reform: \"ctc_refundable_amount_1800\", year: 2027, output: [\"ctc_outlays\", \"spm_child_poverty_rate\"], unit: \"billions\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":1,"rationale":"Score 1/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1500, distribution present, forecast step count 1.","evidence":["The modal outcome is retaining the current refundable design with indexation. The lower tail remains real because the scheduled-law branch is a discrete cliff; the upper tail reflects a child-credit compromise that expands refundability without restoring the full 2021 policy.","Forecast: point 1800, 80% interval [1000, 2500]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The maximum refundable CTC amount is the policy parameter that drives outlays and child-poverty effects for low-income families. It is distinct from the headline maximum credit because families with low earnings can be limited by the refundable cap and phase-in.","The modal outcome is retaining the current refundable design with indexation. The lower tail remains real because the scheduled-law branch is a discrete cliff; the upper tail reflects a child-credit compromise that expands refundability without restoring the full 2021 policy."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 1800, 80% interval [1000, 2500]"]}],"flags":["weak_resolution_clarity","weak_counterarguments","no_ledger_target"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: ctc-refundable-amount-ty2027\nrunLabel: Headline\nresolutionDate: 2027-12-31\ntraceLineCount: 13\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: resolution clarity (1/4). Flags: weak_resolution_clarity, weak_counterarguments, no_ledger_target."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.eitc-max-credit-three-children-ty2027.2026-06-08T00-00-00-02-00.84466c453e2a7d12","runId":"run.eitc-max-credit-three-children-ty2027.2026-06-08T00-00-00-02-00.84466c453e2a7d12","predictionId":"eitc-max-credit-three-children-ty2027","specId":"spec.eitc-max-credit-three-children-ty2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["This cell forecasts a core EITC schedule parameter. The baseline is mostly mechanical indexation, but it is worth tracking because small parameter changes cascade into EITC outlays, marginal tax rates, and poverty forecasts.","Tool result: { formula: \"prior_year_amount indexed by chained CPI-U\", projected_value: 8500 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool result: { marginal_outlay_per_100: 0.9, note: \"billions of dollars before take-up calibration\" }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":1,"rationale":"Score 1/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1050, distribution present, forecast step count 1.","evidence":["The central estimate follows inflation indexation from the TY2026 estimate. The upper tail allows for a family-credit package that modestly raises EITC parameters; the lower tail is mainly lower CPI and rounding, not repeal.","Forecast: point 8500, 80% interval [8050, 9100]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["This cell forecasts a core EITC schedule parameter. The baseline is mostly mechanical indexation, but it is worth tracking because small parameter changes cascade into EITC outlays, marginal tax rates, and poverty forecasts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["This cell forecasts a core EITC schedule parameter. The baseline is mostly mechanical indexation, but it is worth tracking because small parameter changes cascade into EITC outlays, marginal tax rates, and poverty forecasts."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["This cell forecasts a core EITC schedule parameter. The baseline is mostly mechanical indexation, but it is worth tracking because small parameter changes cascade into EITC outlays, marginal tax rates, and poverty forecasts.","Forecast"]}],"flags":["weak_resolution_clarity","no_ledger_target"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: eitc-max-credit-three-children-ty2027\nrunLabel: Headline\nresolutionDate: 2026-10-31\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: resolution clarity (1/4). Flags: weak_resolution_clarity, no_ledger_target."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-average-benefit-per-person-fy2027.2026-06-08T00-00-00-02-00.67a726d89810fd9f","runId":"run.snap-average-benefit-per-person-fy2027.2026-06-08T00-00-00-02-00.67a726d89810fd9f","predictionId":"snap-average-benefit-per-person-fy2027","specId":"spec.snap-average-benefit-per-person-fy2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Total benefits / person-months cross-check: $128B / (46M persons x 12) = $232/mo."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 36, distribution present, forecast step count 1.","evidence":["Forecast: point 232, 80% interval [216, 252]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 231, ci80: [218, 249], drivers: [\"max allotment\", \"net income\", \"household size\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["SNAP caseload and total outlays are already separate cells. Average monthly benefit per person isolates the benefit-formula and income-composition channel, which is the piece PolicyEngine can forecast from household resources.","Tool result: { point: 231, ci80: [218, 249], drivers: [\"max allotment\", \"net income\", \"household size\"] }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-average-benefit-per-person-fy2027\nrunLabel: Headline\nresolutionDate: 2028-03-31\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.ptc-average-subsidy-per-enrollee-fy2027.2026-06-08T00-00-00-02-00.cc6ec471947ec530","runId":"run.ptc-average-subsidy-per-enrollee-fy2027.2026-06-08T00-00-00-02-00.cc6ec471947ec530","predictionId":"ptc-average-subsidy-per-enrollee-fy2027","specId":"spec.ptc-average-subsidy-per-enrollee-fy2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.92,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["If enhanced subsidies expire, lower-subsidy marginal enrollees leave first, mechanically raising average subsidy among those who remain. That composition effect offsets part of the statutory subsidy reduction."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 300, distribution present, forecast step count 1.","evidence":["Forecast: point 690, 80% interval [560, 860]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["PTC outlays can fall because enrollment falls or because the subsidy per enrollee falls. This cell isolates the per-enrollee subsidy, which is the clean target for modeling premium growth and subsidy formula changes.","Tool result: { point: 680, ci80: [560, 840], drivers: [\"premium growth\", \"income mix\", \"subsidy cliff\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["If enhanced subsidies expire, lower-subsidy marginal enrollees leave first, mechanically raising average subsidy among those who remain. That composition effect offsets part of the statutory subsidy reduction."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 680, ci80: [560, 840], drivers: [\"premium growth\", \"income mix\", \"subsidy cliff\"] }","Forecast: point 690, 80% interval [560, 860]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: ptc-average-subsidy-per-enrollee-fy2027\nrunLabel: Headline\nresolutionDate: 2028-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.initial-jobless-claims-week-ending-2026-06-06.2026-06-08T00-00-00-02-00.75d7c75b760f1a12","runId":"run.initial-jobless-claims-week-ending-2026-06-06.2026-06-08T00-00-00-02-00.75d7c75b760f1a12","predictionId":"initial-jobless-claims-week-ending-2026-06-06","specId":"spec.initial-jobless-claims-week-ending-2026-06-06","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and implicit outside-view language.","evidence":["Tool result: { median_thousands: 214, p10: 199, p90: 232 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Initial claims are the fastest clean labor-market calibration target in the launch slate: weekly, objective, fixed-release, and benchmarkable against consensus. This target resolves on 2026-06-11 under a first-print rule, with an expected ~5 days lag. The same series can also spawn next release, +4 weeks, threshold questions.","Tool call: consensus.lookup({ indicator: \"initial_jobless_claims\", release: \"2026-06-11\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Weekly next release cell","Initial claims are the fastest clean labor-market calibration target in the launch slate: weekly, objective, fixed-release, and benchmarkable against consensus. This target resolves on 2026-06-11 under a first-print rule, with an expected ~5 days lag. The same series can also spawn next release, +4 weeks, threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 36, distribution present, forecast step count 1.","evidence":["The agent run centers near the latest May 23 print and only slightly above the four-week average. Initial claims have stayed rangebound around 200k-215k, so the interval is tight enough to score the release while allowing a holiday-adjustment surprise.","Forecast: point 214, 80% interval [197, 233]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The agent run centers near the latest May 23 print and only slightly above the four-week average. Initial claims have stayed rangebound around 200k-215k, so the interval is tight enough to score the release while allowing a holiday-adjustment surprise.","Forecast: point 214, 80% interval [197, 233]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: initial-jobless-claims-week-ending-2026-06-06\nrunLabel: Headline\nresolutionDate: 2026-06-11\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.nonfarm-payrolls-may-2026.2026-06-08T00-00-00-02-00.e0b36ed2a135df63","runId":"run.nonfarm-payrolls-may-2026.2026-06-08T00-00-00-02-00.e0b36ed2a135df63","predictionId":"nonfarm-payrolls-may-2026","specId":"spec.nonfarm-payrolls-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.41,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Payrolls are crowded, but that is useful: Thesis can score itself against survey medians and show whether agents add value beyond consensus. This target resolves on 2026-06-05 under a first-print rule, with an expected ~1 week lag. The same series can also spawn next release, +3 months, +12 months, threshold questions.","Tool result: { median_thousands: 90, interquartile_range: [25, 155] }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Payrolls are crowded, but that is useful: Thesis can score itself against survey medians and show whether agents add value beyond consensus. This target resolves on 2026-06-05 under a first-print rule, with an expected ~1 week lag. The same series can also spawn next release, +3 months, +12 months, threshold questions.","Tool call: bls.lookup({ survey: \"CES\", series: \"total_nonfarm_change\", months: [\"2026-01\", \"2026-04\"], vintage: \"first_print\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Monthly next release cell","Payrolls are crowded, but that is useful: Thesis can score itself against survey medians and show whether agents add value beyond consensus. This target resolves on 2026-06-05 under a first-print rule, with an expected ~1 week lag. The same series can also spawn next release, +3 months, +12 months, threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 280, distribution present, forecast step count 1.","evidence":["Forecast: point 85, 80% interval [-60, 220]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Payrolls are crowded, but that is useful: Thesis can score itself against survey medians and show whether agents add value beyond consensus. This target resolves on 2026-06-05 under a first-print rule, with an expected ~1 week lag. The same series can also spawn next release, +3 months, +12 months, threshold questions.","The agent run lowers the center after the April +115k print and volatile first-quarter revisions. Claims remain low, but federal-government drag and weak net growth over the prior year keep the estimate below the earlier mock."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 85, 80% interval [-60, 220]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: nonfarm-payrolls-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-05\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.unemployment-rate-may-2026-first-print.2026-06-08T00-00-00-02-00.bc2560c9f3dbbe73","runId":"run.unemployment-rate-may-2026-first-print.2026-06-08T00-00-00-02-00.bc2560c9f3dbbe73","predictionId":"unemployment-rate-may-2026-first-print","specId":"spec.unemployment-rate-may-2026-first-print","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.24,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and implicit outside-view language.","evidence":["Tool result: { median_percent: 4.3, range_percent: [4.2, 4.4] }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["The unemployment rate pairs with payrolls but has different noise: household-survey employment, labor-force entry, and rounding to one decimal place. This target resolves on 2026-06-05 under a first-print rule, with an expected ~1 week lag. The same series can also spawn next release, +3 months, +12 months, threshold questions.","Tool call: bls.lookup({ survey: \"CPS\", series: \"unemployment_rate_sa\", months: [\"2026-01\", \"2026-04\"], vintage: \"first_print\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Monthly next release cell","The unemployment rate pairs with payrolls but has different noise: household-survey employment, labor-force entry, and rounding to one decimal place. This target resolves on 2026-06-05 under a first-print rule, with an expected ~1 week lag. The same series can also spawn next release, +3 months, +12 months, threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.4, distribution present, forecast step count 1.","evidence":["The unemployment rate has held at 4.3% for two consecutive months after 4.4% in February. Claims and insured unemployment do not yet point to a sharp break, so the run keeps the center unchanged with a two-tenths 80% interval.","Forecast: point 4.3, 80% interval [4.1, 4.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["The unemployment rate pairs with payrolls but has different noise: household-survey employment, labor-force entry, and rounding to one decimal place. This target resolves on 2026-06-05 under a first-print rule, with an expected ~1 week lag. The same series can also spawn next release, +3 months, +12 months, threshold questions."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The unemployment rate has held at 4.3% for two consecutive months after 4.4% in February. Claims and insured unemployment do not yet point to a sharp break, so the run keeps the center unchanged with a two-tenths 80% interval.","Forecast: point 4.3, 80% interval [4.1, 4.5]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: unemployment-rate-may-2026-first-print\nrunLabel: Headline\nresolutionDate: 2026-06-05\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.cpi-headline-mom-may-2026.2026-06-06T23-43-56-02-00.497b03f3b06819b9","runId":"run.cpi-headline-mom-may-2026.2026-06-06T23-43-56-02-00.497b03f3b06819b9","predictionId":"cpi-headline-mom-may-2026","specId":"spec.cpi-headline-mom-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.32,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["CPI is a launch flagship because it resolves quickly, has a consensus benchmark, and feeds formula-driven policy parameters later in the year. This target resolves on 2026-06-10 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, +12 months, threshold questions.","Tool call: bls.lookup({ survey: \"CPI\", series: \"CPI-U all items SA MoM\", months: [\"2026-01\", \"2026-04\"], vintage: \"first_print\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","CPI is a launch flagship because it resolves quickly, has a consensus benchmark, and feeds formula-driven policy parameters later in the year. This target resolves on 2026-06-10 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, +12 months, threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.4, distribution present, forecast step count 1.","evidence":["Three independent CPI agents converged on a 0.5% rounded headline print. The common signal is another positive gasoline contribution, confirmed by EIA's May price path and Cleveland Fed's 0.46% nowcast, while the interval allows late-May fuel softness or a shelter/food surprise to move the rounded print.","Forecast: point 0.5, 80% interval [0.3, 0.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["CPI is a launch flagship because it resolves quickly, has a consensus benchmark, and feeds formula-driven policy parameters later in the year. This target resolves on 2026-06-10 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, +12 months, threshold questions."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Three independent CPI agents converged on a 0.5% rounded headline print. The common signal is another positive gasoline contribution, confirmed by EIA's May price path and Cleveland Fed's 0.46% nowcast, while the interval allows late-May fuel softness or a shelter/food surprise to move the rounded print."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { agent_points: [0.49, 0.48, 0.52], ensemble_point: 0.50, ensemble_ci80: [0.30, 0.70], likely_rounded_print: 0.5 }","Three independent CPI agents converged on a 0.5% rounded headline print. The common signal is another positive gasoline contribution, confirmed by EIA's May price path and Cleveland Fed's 0.46% nowcast, while the interval allows late-May fuel softness or a shelter/food surprise to move the rounded print."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: cpi-headline-mom-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-10\ntraceLineCount: 12\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.retail-sales-mom-may-2026.2026-06-08T00-00-00-02-00.8ff89b7696efc334","runId":"run.retail-sales-mom-may-2026.2026-06-08T00-00-00-02-00.8ff89b7696efc334","predictionId":"retail-sales-mom-may-2026","specId":"spec.retail-sales-mom-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.46,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Retail sales add a high-frequency demand-side series to the launch set and produce many derivable questions from one source. This target resolves on 2026-06-17 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, control group, threshold questions.","Tool call: census.lookup({ survey: \"MARTS\", series: \"adv44X72\", months: [\"2026-03\", \"2026-04\"], vintage: \"advance\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Monthly next release cell","Retail sales add a high-frequency demand-side series to the launch set and produce many derivable questions from one source. This target resolves on 2026-06-17 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, control group, threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.4, distribution present, forecast step count 1.","evidence":["Retail sales add a high-frequency demand-side series to the launch set and produce many derivable questions from one source. This target resolves on 2026-06-17 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, control group, threshold questions.","March and April nominal retail sales were strong, but the forecast centers below April's pace because some momentum should fade and gasoline receipts can drag the headline. Advance retail sales remain volatile, so the 80% interval spans a small decline through a near-1% gain."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["March and April nominal retail sales were strong, but the forecast centers below April's pace because some momentum should fade and gasoline receipts can drag the headline. Advance retail sales remain volatile, so the 80% interval spans a small decline through a near-1% gain."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["March and April nominal retail sales were strong, but the forecast centers below April's pace because some momentum should fade and gasoline receipts can drag the headline. Advance retail sales remain volatile, so the 80% interval spans a small decline through a near-1% gain."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["March and April nominal retail sales were strong, but the forecast centers below April's pace because some momentum should fade and gasoline receipts can drag the headline. Advance retail sales remain volatile, so the 80% interval spans a small decline through a near-1% gain.","Forecast: point 0.2, 80% interval [-0.5, 0.9]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: retail-sales-mom-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-17\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.retail-sales-mom-may-2026.2026-06-15T10-05-00-04-00.retail-control-no-packs.987df99045d5dcd8","runId":"run.retail-sales-mom-may-2026.2026-06-15T10-05-00-04-00.retail-control-no-packs.987df99045d5dcd8","predictionId":"retail-sales-mom-may-2026","specId":"spec.retail-sales-mom-may-2026","runLabel":"Scout-2 - no packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.73,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 0 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.6, distribution present, forecast step count 1.","evidence":["Retail sales control run","The control starts from the strong March and April advance retail prints, then fades momentum toward the recent nominal retail mean without separating autos, gasoline, or control-group demand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The control starts from the strong March and April advance retail prints, then fades momentum toward the recent nominal retail mean without separating autos, gasoline, or control-group demand.","Headline fade = 0.35 * April momentum + 0.65 * recent monthly mean = about +0.1%."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 0.1, 80% interval [-0.7, 0.9]"]}],"flags":["no_typed_tool_call"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: retail-sales-mom-may-2026\nrunLabel: Scout-2 - no packs\nresolutionDate: 2026-06-17\ntraceLineCount: 4\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). Flags: no_typed_tool_call."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.retail-sales-mom-may-2026.2026-06-15T10-10-00-04-00.retail-consumer-spending-packs.570cc5ab36fe824c","runId":"run.retail-sales-mom-may-2026.2026-06-15T10-10-00-04-00.retail-consumer-spending-packs.570cc5ab36fe824c","predictionId":"retail-sales-mom-may-2026","specId":"spec.retail-sales-mom-may-2026","runLabel":"Brier-1 - spending packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.43,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"consumer-spending-nowcast@0.1.0\", \"release-vintage-calibration@0.1.0\"], target: \"census.marts.adv44x72.may_2026.monthly_change.advance\" })","Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"retail_base_rate\", \"auto_gas_control_group_split\", \"advance_release_error\"] }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Consumer-spending pack run","Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"consumer-spending-nowcast@0.1.0\", \"release-vintage-calibration@0.1.0\"], target: \"census.marts.adv44x72.may_2026.monthly_change.advance\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"consumer-spending-nowcast@0.1.0\", \"release-vintage-calibration@0.1.0\"], target: \"census.marts.adv44x72.may_2026.monthly_change.advance\" })","Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"retail_base_rate\", \"auto_gas_control_group_split\", \"advance_release_error\"] }"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.2, distribution present, forecast step count 1.","evidence":["Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"retail_base_rate\", \"auto_gas_control_group_split\", \"advance_release_error\"] }","The pack keeps the headline retail fade but adds back some support from control-group and auto-sales momentum while treating gasoline receipts as a volatile channel rather than a broad demand signal."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The pack keeps the headline retail fade but adds back some support from control-group and auto-sales momentum while treating gasoline receipts as a volatile channel rather than a broad demand signal."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The pack keeps the headline retail fade but adds back some support from control-group and auto-sales momentum while treating gasoline receipts as a volatile channel rather than a broad demand signal."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 0.25, 80% interval [-0.35, 0.85]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: retail-sales-mom-may-2026\nrunLabel: Brier-1 - spending packs\nresolutionDate: 2026-06-17\ntraceLineCount: 5\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.core-pce-mom-may-2026.2026-06-08T00-00-00-02-00.724540c0830f0540","runId":"run.core-pce-mom-may-2026.2026-06-08T00-00-00-02-00.724540c0830f0540","predictionId":"core-pce-mom-may-2026","specId":"spec.core-pce-mom-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Core PCE gives the launch slate a second inflation target with a different source and mapping from CPI and PPI. This target resolves on 2026-06-25 under a first-print rule, with an expected ~4 weeks lag. The same series can also spawn next release, +12 months, threshold questions."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Monthly next release cell","Core PCE gives the launch slate a second inflation target with a different source and mapping from CPI and PPI. This target resolves on 2026-06-25 under a first-print rule, with an expected ~4 weeks lag. The same series can also spawn next release, +12 months, threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.3, distribution present, forecast step count 1.","evidence":["The bridge points to another 0.2% print. The upper interval leaves room for financial-services and health-care categories that CPI does not measure cleanly.","Forecast: point 0.2, 80% interval [0.1, 0.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The bridge points to another 0.2% print. The upper interval leaves room for financial-services and health-care categories that CPI does not measure cleanly.","Forecast: point 0.2, 80% interval [0.1, 0.4]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: core-pce-mom-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-25\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.core-pce-mom-may-2026.2026-06-20T09-12-00-04-00.core-pce-mom-may-2026-brier-shadow-no-packs.535cd429edf5344c","runId":"run.core-pce-mom-may-2026.2026-06-20T09-12-00-04-00.core-pce-mom-may-2026-brier-shadow-no-packs.535cd429edf5344c","predictionId":"core-pce-mom-may-2026","specId":"spec.core-pce-mom-may-2026","runLabel":"Brier-1 - no packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 0 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.33, distribution present, forecast step count 1.","evidence":["Forecast: point 0.21, 80% interval [0.06, 0.39]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The control run extrapolates recent core PCE momentum without translating CPI and PPI source data into PCE concepts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 0.21, 80% interval [0.06, 0.39]"]}],"flags":["weak_counterarguments","no_typed_tool_call"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: core-pce-mom-may-2026\nrunLabel: Brier-1 - no packs\nresolutionDate: 2026-06-25\ntraceLineCount: 3\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments, no_typed_tool_call."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.core-pce-mom-may-2026.2026-06-20T09-12-00-04-00.core-pce-mom-may-2026-brier-shadow-with-packs.801d56ba45e3d236","runId":"run.core-pce-mom-may-2026.2026-06-20T09-12-00-04-00.core-pce-mom-may-2026-brier-shadow-with-packs.801d56ba45e3d236","predictionId":"core-pce-mom-may-2026","specId":"spec.core-pce-mom-may-2026","runLabel":"Brier-1 - packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.41,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: brier.pack.apply({ target: \"bea.pce.core_mom.may_2026.first_print\", packs: [\"base-rate-first@0.1.0\", \"pce-cpi-bridge@0.1.0\", \"release-vintage-calibration@0.1.0\"] })","Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"core_pce_base_rate\",\"cpi_scope_bridge\",\"ppi_services_inputs\",\"bea_release_calibration\"] }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: brier.pack.apply({ target: \"bea.pce.core_mom.may_2026.first_print\", packs: [\"base-rate-first@0.1.0\", \"pce-cpi-bridge@0.1.0\", \"release-vintage-calibration@0.1.0\"] })","Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"core_pce_base_rate\",\"cpi_scope_bridge\",\"ppi_services_inputs\",\"bea_release_calibration\"] }"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.32, distribution present, forecast step count 1.","evidence":["Forecast: point 0.27, 80% interval [0.11, 0.43]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The pack run raises the center because CPI/PPI source data point to firmer BEA core PCE than the no-pack persistence baseline."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The pack run raises the center because CPI/PPI source data point to firmer BEA core PCE than the no-pack persistence baseline.","Forecast: point 0.27, 80% interval [0.11, 0.43]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: core-pce-mom-may-2026\nrunLabel: Brier-1 - packs\nresolutionDate: 2026-06-25\ntraceLineCount: 5\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-participation-april-2026.2026-06-08T00-00-00-02-00.12162e65d4607dd0","runId":"run.snap-participation-april-2026.2026-06-08T00-00-00-02-00.12162e65d4607dd0","predictionId":"snap-participation-april-2026","specId":"spec.snap-participation-april-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.27,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and explicit outside-view language.","evidence":["The forecast expects participation to flatten near 41 million. The value comes from combining administrative trend with a bottom-up eligibility/take-up prior."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["SNAP participation is a Thesis niche in the working doc: monthly, public, objective, decision-relevant, and under-forecasted compared with macro indicators. This target resolves on 2026-08-31 under a fixed-vintage rule, with an expected ~2 months lag. The same series can also spawn next release, +3 months, +12 months, threshold questions.","Tool call: usda.fns.lookup({ program: \"snap\", series: \"persons\", months: [\"2025-10\", \"2026-01\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["SNAP participation is a Thesis niche in the working doc: monthly, public, objective, decision-relevant, and under-forecasted compared with macro indicators. This target resolves on 2026-08-31 under a fixed-vintage rule, with an expected ~2 months lag. The same series can also spawn next release, +3 months, +12 months, threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.7, distribution present, forecast step count 1.","evidence":["Forecast: point 40.8, 80% interval [39.5, 42.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 40.9, ci80: [39.6, 42.1], drivers: [\"eligible_population\", \"recertification\", \"earnings\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["SNAP participation is a Thesis niche in the working doc: monthly, public, objective, decision-relevant, and under-forecasted compared with macro indicators. This target resolves on 2026-08-31 under a fixed-vintage rule, with an expected ~2 months lag. The same series can also spawn next release, +3 months, +12 months, threshold questions.","Tool result: { point: 40.9, ci80: [39.6, 42.1], drivers: [\"eligible_population\", \"recertification\", \"earnings\"] }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-participation-april-2026\nrunLabel: Headline\nresolutionDate: 2026-08-31\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-participation-april-2026.2026-06-27T13-41-51Z.snap-participation-april-2026-thesis-analyst-fast-2026-06-27t13-41-51z.8dcfcfb841a70fa8","runId":"run.snap-participation-april-2026.2026-06-27T13-41-51Z.snap-participation-april-2026-thesis-analyst-fast-2026-06-27t13-41-51z.8dcfcfb841a70fa8","predictionId":"snap-participation-april-2026","specId":"spec.snap-participation-april-2026","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: Read the prior-year and latest FY2026 rows in the USDA FNS SNAP monthly PDF.","Base-rate reference class: April observations in the fetched current table for 2023-2025 were 41.914 million, 41.612 million, and 42.353 million, so the simple same-month base rate is about 41.96 million before current-release adjustments."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Forecast USDA FNS SNAP persons for April 2026 first print","The target is the national SNAP FY2026 National View Summary monthly table, April 2026 row, Participation Persons field, resolved from USDA FNS SNAP Data Tables on the first public monthly print and converted from persons to millions."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast USDA FNS SNAP persons for April 2026 first print","The target is the national SNAP FY2026 National View Summary monthly table, April 2026 row, Participation Persons field, resolved from USDA FNS SNAP Data Tables on the first public monthly print and converted from persons to millions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.8, distribution present, forecast step count 1.","evidence":["Interval sizing: the fetched April same-month 2023-2025 range is 0.741 million and the Oct-Nov 2025 move is -0.696 million, but policy and first-print reporting risk make a wider judgmental 80% half-width appropriate. I use +/-1.4 million around 39.8, about twice those recent realized moves, for an 80% interval of 38.4 to 41.2 million.","Review disposition: accepted the resolver clarification by naming the exact FY2026 National View Summary monthly table and Participation Persons field, accepted adding Nov 2024 evidence before the ratio calculation, accepted making the interval width explicitly judgmental and tied to fetched realized moves, and clarified that historical values are current-table lookup values while resolution uses the first posted April 2026 print."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Interval sizing: the fetched April same-month 2023-2025 range is 0.741 million and the Oct-Nov 2025 move is -0.696 million, but policy and first-print reporting risk make a wider judgmental 80% half-width appropriate. I use +/-1.4 million around 39.8, about twice those recent realized moves, for an 80% interval of 38.4 to 41.2 million."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast USDA FNS SNAP persons for April 2026 first print","Current-level adjustment: Nov 2025 was 40.395735 million versus Nov 2024 43.018848 million, a ratio of 0.9390. Applying that ratio to Apr 2025 42.353149 million gives 39.77 million; rounding and allowing partial stabilization gives a 39.8 million point estimate."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-participation-april-2026\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-08-31\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-chip-enrollment-april-2026.2026-06-08T00-00-00-02-00.14f03c7c906231a1","runId":"run.medicaid-chip-enrollment-april-2026.2026-06-08T00-00-00-02-00.14f03c7c906231a1","predictionId":"medicaid-chip-enrollment-april-2026","specId":"spec.medicaid-chip-enrollment-april-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.24,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Medicaid enrollment is a high-value monthly program series: it resolves from administrative data, affects coverage and poverty forecasts, and gives repeated feedback on eligibility/take-up modeling. This target resolves on 2026-09-30 under a fixed-vintage rule, with an expected ~2-3 months lag. The same series can also spawn next release, +3 months, +12 months, threshold questions."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Medicaid enrollment is a high-value monthly program series: it resolves from administrative data, affects coverage and poverty forecasts, and gives repeated feedback on eligibility/take-up modeling. This target resolves on 2026-09-30 under a fixed-vintage rule, with an expected ~2-3 months lag. The same series can also spawn next release, +3 months, +12 months, threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6.4, distribution present, forecast step count 1.","evidence":["The central estimate holds enrollment close to its post-unwinding floor. The interval is wider than SNAP because state reporting and renewal policy create larger cross-state movement.","Forecast: point 79.1, 80% interval [76.2, 82.6]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 79.2, ci80: [76.3, 82.4], drivers: [\"state_renewals\", \"child_continuity\", \"income_growth\"] }","The central estimate holds enrollment close to its post-unwinding floor. The interval is wider than SNAP because state reporting and renewal policy create larger cross-state movement."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Medicaid enrollment is a high-value monthly program series: it resolves from administrative data, affects coverage and poverty forecasts, and gives repeated feedback on eligibility/take-up modeling. This target resolves on 2026-09-30 under a fixed-vintage rule, with an expected ~2-3 months lag. The same series can also spawn next release, +3 months, +12 months, threshold questions.","Tool result: { point: 79.2, ci80: [76.3, 82.4], drivers: [\"state_renewals\", \"child_continuity\", \"income_growth\"] }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-chip-enrollment-april-2026\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-chip-enrollment-april-2026.2026-06-27T23-09-35Z.medicaid-chip-enrollment-april-2026-thesis-analyst-fast-2026-06-27t23-09-35z.65abab9abd63ee56","runId":"run.medicaid-chip-enrollment-april-2026.2026-06-27T23-09-35Z.medicaid-chip-enrollment-april-2026-thesis-analyst-fast-2026-06-27t23-09-35z.65abab9abd63ee56","predictionId":"medicaid-chip-enrollment-april-2026","specId":"spec.medicaid-chip-enrollment-april-2026","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base-rate/reference-class anchor: the latest official level is 74.294 million in March 2026, and CMS's release list shows comparable monthly files. I use March persistence as the model prior because the fast run did not fetch a clean sequence of earlier same-vintage national totals; using older catalog levels near 79 million would overweight stale pre-current-level information.","Point: start from the March official persistence prior of 74.294361 million, subtract a judgmental 0.20 million for continued post-unwinding attrition, and add a judgmental 0.06 million for updated-vintage retroactive/late processing, giving 74.154361 million, rounded to 74.15. Interval: in the absence of a fetched same-vintage month-over-month sample in this fast run, use a quantitative uncertainty model with 1.0 million process standard deviation for monthly enrollment movement plus 0.5 million reporting/revision standard deviation; 1.28 * sqrt(1.0^2 + 0.5^2) = 1.43 million, rounded to an 80% band of 72.70 to 75.60 million."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The resolver is the April 2026 updated-data national Total Medicaid and CHIP Enrollment value in CMS monthly Medicaid and CHIP enrollment data, converted from persons to millions. This is a national total, not a weighted average or a state row.","Tool call: Read the same official CMS highlights page for child-enrollment context and data timestamp."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: Opened the Medicaid.gov monthly reports page for release availability and target timing.","Tool result: Fetched official release list showing Preliminary March 2026 data last updated June 26, 2026; Updated February 2026 data last updated June 26, 2026; Updated January 2026 data last updated June 26, 2026; and no April 2026 entry visible as of this run."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.9, distribution present, forecast step count 1.","evidence":["Point: start from the March official persistence prior of 74.294361 million, subtract a judgmental 0.20 million for continued post-unwinding attrition, and add a judgmental 0.06 million for updated-vintage retroactive/late processing, giving 74.154361 million, rounded to 74.15. Interval: in the absence of a fetched same-vintage month-over-month sample in this fast run, use a quantitative uncertainty model with 1.0 million process standard deviation for monthly enrollment movement plus 0.5 million reporting/revision standard deviation; 1.28 * sqrt(1.0^2 + 0.5^2) = 1.43 million, rounded to an 80% band of 72.70 to 75.60 million.","Counter-consideration and scenarios: downside outside the interval would require April updated enrollment more than about 1.59 million below March, likely from broad state renewal drops or reporting cleanups. Upside outside the interval would require April updated enrollment more than about 1.31 million above March, likely from unusually large retroactive enrollment, state resubmissions, or a reporting-break rebound. The central case is near-flat to mildly down from March."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base-rate/reference-class anchor: the latest official level is 74.294 million in March 2026, and CMS's release list shows comparable monthly files. I use March persistence as the model prior because the fast run did not fetch a clean sequence of earlier same-vintage national totals; using older catalog levels near 79 million would overweight stale pre-current-level information.","Level, momentum, and vintage split: March gives the level anchor; post-unwinding Medicaid/CHIP enrollment still appears to be drifting down, but by 2026 the extreme unwinding losses should be mostly over. The updated April vintage should be a little higher than a preliminary April print would be because updated data include retroactive and late-processed enrollment."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, and vintage split: March gives the level anchor; post-unwinding Medicaid/CHIP enrollment still appears to be drifting down, but by 2026 the extreme unwinding losses should be mostly over. The updated April vintage should be a little higher than a preliminary April print would be because updated data include retroactive and late-processed enrollment.","Point: start from the March official persistence prior of 74.294361 million, subtract a judgmental 0.20 million for continued post-unwinding attrition, and add a judgmental 0.06 million for updated-vintage retroactive/late processing, giving 74.154361 million, rounded to 74.15. Interval: in the absence of a fetched same-vintage month-over-month sample in this fast run, use a quantitative uncertainty model with 1.0 million process standard deviation for monthly enrollment movement plus 0.5 million reporting/revision standard deviation; 1.28 * sqrt(1.0^2 + 0.5^2) = 1.43 million, rounded to an 80% band of 72.70 to 75.60 million."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast April 2026 CMS Medicaid and CHIP enrollment","Point: start from the March official persistence prior of 74.294361 million, subtract a judgmental 0.20 million for continued post-unwinding attrition, and add a judgmental 0.06 million for updated-vintage retroactive/late processing, giving 74.154361 million, rounded to 74.15. Interval: in the absence of a fetched same-vintage month-over-month sample in this fast run, use a quantitative uncertainty model with 1.0 million process standard deviation for monthly enrollment movement plus 0.5 million reporting/revision standard deviation; 1.28 * sqrt(1.0^2 + 0.5^2) = 1.43 million, rounded to an 80% band of 72.70 to 75.60 million."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-chip-enrollment-april-2026\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-09-30\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.belgium-consumer-confidence-august-2026.2026-08-13T17-40-05Z.a4a2d46ad6d408f2","runId":"run.belgium-consumer-confidence-august-2026.2026-08-13T17-40-05Z.a4a2d46ad6d408f2","predictionId":"belgium-consumer-confidence-august-2026","specId":"spec.belgium-consumer-confidence-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: using the 13 official NBB monthly first prints from 2025-07 through 2026-07, the latest print is -5.0, the 13-print mean is -2.9, the last-six mean is -6.0, the last-three mean is -7.3, and the range is -10.0 to 4.0. Persistence is the base rate because it has the lowest walk-forward MAE among the simple candidates.","Prior/update/interval: persistence prior = -5.0 from the July 2026 first print; historical sample = NBB 2025-07 through 2026-07 first-print table; adjustment components = +0.0 for August because July's improvement and unemployment deterioration are already in the latest print and no direct August signal is fetched. For this level survey-balance series, use successive monthly changes: sigma = 3.37 from changes [2, 1, 1, 2, -3, 5, -3, -7, -3, -1, 3, 2]. The raw 80% half-width is 1.28*sigma = 4.31; widen by about 1.39x to 6.0 for small-sample calibration and conservative one-month survey outcome volatility, giving -5.0 - 6.0 = -11.0 and -5.0 + 6.0 = 1.0."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Belgium August 2026 NBB Consumer Confidence Forecast","Framing and exact resolver: the target is the National Bank of Belgium's first published August 2026 consumer confidence indicator, seasonally adjusted, in signed index points. The canonical ledger target uses country BE, unit index_points, dataPointId nbb.consumer_confidence.indicator.2026-08.first_print, and an expected release window from 2026-08-16 through 2026-08-24."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: the target is the National Bank of Belgium's first published August 2026 consumer confidence indicator, seasonally adjusted, in signed index points. The canonical ledger target uses country BE, unit index_points, dataPointId nbb.consumer_confidence.indicator.2026-08.first_print, and an expected release window from 2026-08-16 through 2026-08-24.","Tool call: Fetched the NBB upcoming latest-figures view for consumer confidence releases."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 12, distribution present, forecast step count 1.","evidence":["Tool result: Model candidate numbers from fetched history: persistence point -5.0, p10 -9.3, p50 -5.0, p90 -0.7, 80% interval [-9.3, -0.7], 90% interval [-10.5, 0.5], train cutoff 2026-07, calibration_n 12, walk-forward MAE 2.75; recent monthly changes were 2, 1, 1, 2, -3, 5, -3, -7, -3, -1, 3, 2.","Prior/update/interval: persistence prior = -5.0 from the July 2026 first print; historical sample = NBB 2025-07 through 2026-07 first-print table; adjustment components = +0.0 for August because July's improvement and unemployment deterioration are already in the latest print and no direct August signal is fetched. For this level survey-balance series, use successive monthly changes: sigma = 3.37 from changes [2, 1, 1, 2, -3, 5, -3, -7, -3, -1, 3, 2]. The raw 80% half-width is 1.28*sigma = 4.31; widen by about 1.39x to 6.0 for small-sample calibration and conservative one-month survey outcome volatility, giving -5.0 - 6.0 = -11.0 and -5.0 + 6.0 = 1.0."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate/reference class: using the 13 official NBB monthly first prints from 2025-07 through 2026-07, the latest print is -5.0, the 13-print mean is -2.9, the last-six mean is -6.0, the last-three mean is -7.3, and the range is -10.0 to 4.0. Persistence is the base rate because it has the lowest walk-forward MAE among the simple candidates.","Level, momentum, one-off, and policy mechanisms: the level remains negative but has improved from May -10 and June -7 to July -5; momentum is upward, but the July table also shows unemployment expectations at 14, worse than June 13, while savings improved from 19 to 23. I have no direct public August survey signal before the first print, so I do not move materially away from the persistence benchmark."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, one-off, and policy mechanisms: the level remains negative but has improved from May -10 and June -7 to July -5; momentum is upward, but the July table also shows unemployment expectations at 14, worse than June 13, while savings improved from 19 to 23. I have no direct public August survey signal before the first print, so I do not move materially away from the persistence benchmark.","Counter-consideration and falsification: upside risk is a stronger August improvement in household saving and macro expectations, which would land above the interval if the first print is 1.1 or higher. Downside risk is a renewed deterioration in unemployment or financial-situation expectations, which would land below the interval if the first print is -11.1 or lower. Outside the interval would require a larger one-month move than most recent NBB changes."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Belgium August 2026 NBB Consumer Confidence Forecast","Framing and exact resolver: the target is the National Bank of Belgium's first published August 2026 consumer confidence indicator, seasonally adjusted, in signed index points. The canonical ledger target uses country BE, unit index_points, dataPointId nbb.consumer_confidence.indicator.2026-08.first_print, and an expected release window from 2026-08-16 through 2026-08-24."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: belgium-consumer-confidence-august-2026\nrunLabel: Headline\nresolutionDate: 2026-08-21\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.cps-computer-math-employment-august-2026.2026-08-13T17-43-03Z.6c28b69b1b53c5de","runId":"run.cps-computer-math-employment-august-2026.2026-08-13T17-43-03Z.6c28b69b1b53c5de","predictionId":"cps-computer-math-employment-august-2026","specId":"spec.cps-computer-math-employment-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The outside-view base rate/reference class is last-print persistence from the latest same-table first-print value: July 2026 = 6.924 million. The fetched trailing first-print sequence is March 2026 6.574, April 2026 6.834, May 2026 6.903, June 2026 6.950, and July 2026 6.924 million; recent gains slowed and the latest move was a small decline, so there is no direct current signal that clears the update test for moving materially away from persistence.","Prior/update/interval: persistence model prior = 6.924 million; historical sample = 6.574, 6.834, 6.903, 6.950, and 6.924 million. Successive changes are +0.260, +0.069, +0.047, and -0.026 million, giving sample sigma = 0.122 million from only four month-to-month changes, so the interval is mechanically derived but sample-thin. Adjustment components are +0.000 momentum, +0.000 one-off, and +0.000 policy because no release-specific August evidence justifies moving more than one rounding unit away from persistence, yielding point = 6.924 million. The 80% half-width is roughly 1.28*sigma = 1.28*0.122 = 0.156 million, implying 6.924-0.156 = 6.768 and 6.924+0.156 = 7.080, so the final 80% interval is [6.768, 7.080] million."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 7 source-context item(s), activity log present.","evidence":["The resolver is the first August 2026 BLS CPS Employment Situation Table A-19 print for employed people age 16 and over in 'Computer and mathematical occupations,' not seasonally adjusted. The registered ledger target reports the table as A-19 at cpseea19.htm, with values in thousands transformed to millions by multiplying by 0.001.","Tool call: Open https://www.bls.gov/web/empsit/cpseea19.htm"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The resolver is the first August 2026 BLS CPS Employment Situation Table A-19 print for employed people age 16 and over in 'Computer and mathematical occupations,' not seasonally adjusted. The registered ledger target reports the table as A-19 at cpseea19.htm, with values in thousands transformed to millions by multiplying by 0.001.","Tool call: Verify official release date at https://www.bls.gov/schedule/2026/home.htm"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.31, distribution present, forecast step count 1.","evidence":["Model candidates under thesis_model_candidate_v1: persistence candidate point = 6.924, p10 = 6.768, p50 = 6.924, p90 = 7.080, 80% interval = [6.768, 7.080], 90% interval = [6.723, 7.125], intervalMethod = first-print month-to-month residual sigma with 1.28*sigma and 1.645*sigma, calibration_n = 4 changes, trainCutoff = 2026-07, walkForwardScore = not estimated because only five exact comparable first-print observations were fetched. A mean-change candidate would give point = 7.012, but the positive mean change comes from a short, noisy subgroup sequence and lacks a direct August signal, so I select persistence.","Prior/update/interval: persistence model prior = 6.924 million; historical sample = 6.574, 6.834, 6.903, 6.950, and 6.924 million. Successive changes are +0.260, +0.069, +0.047, and -0.026 million, giving sample sigma = 0.122 million from only four month-to-month changes, so the interval is mechanically derived but sample-thin. Adjustment components are +0.000 momentum, +0.000 one-off, and +0.000 policy because no release-specific August evidence justifies moving more than one rounding unit away from persistence, yielding point = 6.924 million. The 80% half-width is roughly 1.28*sigma = 1.28*0.122 = 0.156 million, implying 6.924-0.156 = 6.768 and 6.924+0.156 = 7.080, so the final 80% interval is [6.768, 7.080] million."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Model candidates under thesis_model_candidate_v1: persistence candidate point = 6.924, p10 = 6.768, p50 = 6.924, p90 = 7.080, 80% interval = [6.768, 7.080], 90% interval = [6.723, 7.125], intervalMethod = first-print month-to-month residual sigma with 1.28*sigma and 1.645*sigma, calibration_n = 4 changes, trainCutoff = 2026-07, walkForwardScore = not estimated because only five exact comparable first-print observations were fetched. A mean-change candidate would give point = 7.012, but the positive mean change comes from a short, noisy subgroup sequence and lacks a direct August signal, so I select persistence.","Prior/update/interval: persistence model prior = 6.924 million; historical sample = 6.574, 6.834, 6.903, 6.950, and 6.924 million. Successive changes are +0.260, +0.069, +0.047, and -0.026 million, giving sample sigma = 0.122 million from only four month-to-month changes, so the interval is mechanically derived but sample-thin. Adjustment components are +0.000 momentum, +0.000 one-off, and +0.000 policy because no release-specific August evidence justifies moving more than one rounding unit away from persistence, yielding point = 6.924 million. The 80% half-width is roughly 1.28*sigma = 1.28*0.122 = 0.156 million, implying 6.924-0.156 = 6.768 and 6.924+0.156 = 7.080, so the final 80% interval is [6.768, 7.080] million."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Model candidates under thesis_model_candidate_v1: persistence candidate point = 6.924, p10 = 6.768, p50 = 6.924, p90 = 7.080, 80% interval = [6.768, 7.080], 90% interval = [6.723, 7.125], intervalMethod = first-print month-to-month residual sigma with 1.28*sigma and 1.645*sigma, calibration_n = 4 changes, trainCutoff = 2026-07, walkForwardScore = not estimated because only five exact comparable first-print observations were fetched. A mean-change candidate would give point = 7.012, but the positive mean change comes from a short, noisy subgroup sequence and lacks a direct August signal, so I select persistence.","Prior/update/interval: persistence model prior = 6.924 million; historical sample = 6.574, 6.834, 6.903, 6.950, and 6.924 million. Successive changes are +0.260, +0.069, +0.047, and -0.026 million, giving sample sigma = 0.122 million from only four month-to-month changes, so the interval is mechanically derived but sample-thin. Adjustment components are +0.000 momentum, +0.000 one-off, and +0.000 policy because no release-specific August evidence justifies moving more than one rounding unit away from persistence, yielding point = 6.924 million. The 80% half-width is roughly 1.28*sigma = 1.28*0.122 = 0.156 million, implying 6.924-0.156 = 6.768 and 6.924+0.156 = 7.080, so the final 80% interval is [6.768, 7.080] million."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["August 2026 computer and mathematical employment forecast","Model candidates under thesis_model_candidate_v1: persistence candidate point = 6.924, p10 = 6.768, p50 = 6.924, p90 = 7.080, 80% interval = [6.768, 7.080], 90% interval = [6.723, 7.125], intervalMethod = first-print month-to-month residual sigma with 1.28*sigma and 1.645*sigma, calibration_n = 4 changes, trainCutoff = 2026-07, walkForwardScore = not estimated because only five exact comparable first-print observations were fetched. A mean-change candidate would give point = 7.012, but the positive mean change comes from a short, noisy subgroup sequence and lacks a direct August signal, so I select persistence."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: cps-computer-math-employment-august-2026\nrunLabel: Headline\nresolutionDate: 2026-09-04\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.cps-office-admin-employment-august-2026.2026-08-13T17-46-45Z.830a8711b0a0da61","runId":"run.cps-office-admin-employment-august-2026.2026-08-13T17-46-45Z.830a8711b0a0da61","predictionId":"cps-office-admin-employment-august-2026","specId":"spec.cps-office-admin-employment-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Base rate / reference class: using the last 24 available BLS LNU02032207 monthly values from 2024-07 through 2026-07, excluding the missing 2025-10 print, the levels are 15.814 to 17.102 million with mean 16.316, median 16.362, and latest 16.457. For this repeated level series the benchmark prior is last-print persistence at 16.457 million; the two fetched July-to-August moves are mixed, +0.088 million in 2024 and -0.150 million in 2025, so they do not justify a material move from persistence.","Prior/update/interval: prior = last-print persistence from July 2026 BLS LNU02032207 at 16.457 million; historical sample = last 24 available official monthly values and 22 consecutive monthly changes through 2026-07; adjustment components = 0.000 million because July-to-August history is mixed (+0.088, -0.150) and no current official signal was fetched that clears the update test; interval method = recent first-print/contemporaneous BLS monthly change residuals, sigma = 0.270 million, half-width = 1.28*sigma = 0.345 million, implying 80% bounds 16.112 to 16.802 million."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing: this target resolves to the BLS CPS Employment Situation Table A-19 row 'Office and administrative support occupations,' Total, 16 years and over, not seasonally adjusted, for August 2026, first print, with the BLS thousands value converted to millions by multiplying by 0.001. The registered target binds slug cps-office-admin-employment-august-2026, unit millions, and dataPointId bls.cps.employed_people_by_occupation.office_administrative_support.august_2026.first_print.","Tool call: Open https://www.bls.gov/schedule/news_release/empsit.htm during this run."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing: this target resolves to the BLS CPS Employment Situation Table A-19 row 'Office and administrative support occupations,' Total, 16 years and over, not seasonally adjusted, for August 2026, first print, with the BLS thousands value converted to millions by multiplying by 0.001. The registered target binds slug cps-office-admin-employment-august-2026, unit millions, and dataPointId bls.cps.employed_people_by_occupation.office_administrative_support.august_2026.first_print.","Tool call: Open https://www.bls.gov/schedule/news_release/empsit.htm during this run."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.69, distribution present, forecast step count 1.","evidence":["Model candidates under thesis_model_candidate_v1: persistence candidate point 16.457, p10 16.112, p50 16.457, p90 16.802, 80% interval [16.112, 16.802], 90% interval [16.013, 16.901], interval_method recent consecutive-change residual sigma, calibration_n 22, train_cutoff 2026-07, walk_forward_mae 0.202 million, walk_forward_rmse 0.264 million. I select persistence because no direct August-specific signal beats it.","Prior/update/interval: prior = last-print persistence from July 2026 BLS LNU02032207 at 16.457 million; historical sample = last 24 available official monthly values and 22 consecutive monthly changes through 2026-07; adjustment components = 0.000 million because July-to-August history is mixed (+0.088, -0.150) and no current official signal was fetched that clears the update test; interval method = recent first-print/contemporaneous BLS monthly change residuals, sigma = 0.270 million, half-width = 1.28*sigma = 0.345 million, implying 80% bounds 16.112 to 16.802 million."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: BLS API series LNU02032207 values fetched this run include 2026-07 16,457 thousand, 2026-06 16,184, 2026-05 16,335, 2026-04 16,471, 2026-03 16,563, 2026-02 16,380, 2026-01 16,291, 2025-12 16,344, 2025-11 17,102, 2025-09 16,608, 2025-08 16,415, and 2025-07 16,565; 2025-10 is '-' because data were unavailable due to the 2025 lapse in appropriations.","Model candidates under thesis_model_candidate_v1: persistence candidate point 16.457, p10 16.112, p50 16.457, p90 16.802, 80% interval [16.112, 16.802], 90% interval [16.013, 16.901], interval_method recent consecutive-change residual sigma, calibration_n 22, train_cutoff 2026-07, walk_forward_mae 0.202 million, walk_forward_rmse 0.264 million. I select persistence because no direct August-specific signal beats it."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-consideration: upside risk would land above the interval if the August CPS sample reverses the May-June softness and clerical employment jumps by more than about 345 thousand from July. Downside risk would land below the interval if the July rebound was sampling noise and office/admin employment falls by more than about 345 thousand, as happened in several recent large negative monthly moves."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["August 2026 office/admin CPS employment forecast","Framing: this target resolves to the BLS CPS Employment Situation Table A-19 row 'Office and administrative support occupations,' Total, 16 years and over, not seasonally adjusted, for August 2026, first print, with the BLS thousands value converted to millions by multiplying by 0.001. The registered target binds slug cps-office-admin-employment-august-2026, unit millions, and dataPointId bls.cps.employed_people_by_occupation.office_administrative_support.august_2026.first_print."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: cps-office-admin-employment-august-2026\nrunLabel: Headline\nresolutionDate: 2026-09-11\ntraceLineCount: 19\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-dod-prime-award-obligations-fy2027-no-fy27-ndaa.2026-08-13T17-36-46Z.8ed61f59afbee88b","runId":"run.us-dod-prime-award-obligations-fy2027-no-fy27-ndaa.2026-08-13T17-36-46Z.8ed61f59afbee88b","predictionId":"us-dod-prime-award-obligations-fy2027-no-fy27-ndaa","specId":"spec.us-dod-prime-award-obligations-fy2027-no-fy27-ndaa","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 9 historical point(s) and explicit outside-view language.","evidence":["Base rate / reference class: comparable complete registered-query prints are FY2017-FY2025 obligations values of 328.0B, 365.9B, 391.3B, 431.9B, 395.3B, 424.5B, 467.3B, 456.9B, and 501.5B. This reference class has mean level 418.1B, median level 424.5B, range 328.0B-501.5B, annual changes +37.9B, +25.4B, +40.5B, -36.6B, +29.2B, +42.8B, -10.3B, and +44.6B, and annual-change sigma 29.5B. FY2026 is excluded from the base rate because it is an incomplete year-to-date value.","Prior/update/interval: persistence prior = 501.5B from the completed FY2025 registered-query print; historical sample = FY2017-FY2025 complete values with successive annual changes 37.9, 25.4, 40.5, -36.6, 29.2, 42.8, -10.3, and 44.6B; adjustment components = -8.0B judgmental no-FY2027-NDAA adjustment, because authorization delay can slow program direction but USAspending prime award obligations are funded by appropriations and execution, not by the authorization act alone. Interval method = annual-change residual, sigma = 29.5B, nominal 80% half-width = 1.28*sigma = 1.28*29.5 = 37.7B; I widen by 1.5x to 56.6B for the two-fiscal-year horizon and conditional legislative uncertainty. Point = 501.5 - 8.0 = 493.5B; interval = 493.5 +/- 56.6 = [436.9, 550.1]B after rounding to 0.1B."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 13 source-context item(s), activity log present.","evidence":["This cell resolves the registered conditional target for USAspending API v2 agency 097 award obligations, fiscal_year=2027, field obligations, transformed by 1e-9 to billions USD. The target registration commits the expected release window 2027-10-15 through 2027-10-22; I set resolutionDate to the window end, 2027-10-22, and keep the registered query URL as the resolver rather than substituting an agency profile total or search summary.","Tool result: Registered target fields inspected this run: catalogSlug us-dod-prime-award-obligations-fy2027-no-fy27-ndaa; period 2027; unit billions USD; dataPointId usaspending.dod.prime_award_obligations.2027.registered_query_snapshot.no_fy27_ndaa; conditionDeadline 2026-12-31; sourceUrl https://api.usaspending.gov/api/v2/agency/097/awards/?fiscal_year={fiscal_year}; field obligations; transform factor 1e-9; expectedReleaseWindow start 2027-10-15 and end 2027-10-22."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["This cell resolves the registered conditional target for USAspending API v2 agency 097 award obligations, fiscal_year=2027, field obligations, transformed by 1e-9 to billions USD. The target registration commits the expected release window 2027-10-15 through 2027-10-22; I set resolutionDate to the window end, 2027-10-22, and keep the registered query URL as the resolver rather than substituting an agency profile total or search summary.","Tool result: Registered target fields inspected this run: catalogSlug us-dod-prime-award-obligations-fy2027-no-fy27-ndaa; period 2027; unit billions USD; dataPointId usaspending.dod.prime_award_obligations.2027.registered_query_snapshot.no_fy27_ndaa; conditionDeadline 2026-12-31; sourceUrl https://api.usaspending.gov/api/v2/agency/097/awards/?fiscal_year={fiscal_year}; field obligations; transform factor 1e-9; expectedReleaseWindow start 2027-10-15 and end 2027-10-22."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 113.2, distribution present, forecast step count 1.","evidence":["Tool result: Fetched USAspending agency 097 awards obligations from the registered endpoint: FY2022 obligations 424512414112.80 USD = 424.512B, transaction_count 4377450; FY2023 obligations 467273435599.16 USD = 467.273B, transaction_count 4430019; FY2024 obligations 456945504400.91 USD = 456.946B, transaction_count 4447901; FY2025 obligations 501543513238.03 USD = 501.544B, transaction_count 4516359. FY2026 is incomplete: obligations 298980123138.95 USD = 298.980B through latest_action_date 2026-08-11 with transaction_count 2641896. FY2027 returned detail Field fiscal_year value 2027 is above max 2026, so no current outcome print exists.","Model candidates under thesis_model_candidate_v1, summarized in trace: two-year persistence uses the FY2025 completed registered-query print as point 501.5, p10 463.8, p50 501.5, p90 539.3, 80% interval [463.8, 539.3], 90% interval [453.2, 549.9], interval_method annual-change residual normal, calibration_n 8, train_cutoff FY2025, walk_forward_mae 30.0 over FY2021-FY2025 two-year-origin backtests. A two-year mean-change drift candidate has point 544.9, p10 507.2, p50 544.9, p90 582.6, 80% interval [507.2, 582.6], 90% interval [496.5, 593.3], interval_method annual-change residual normal, calibration_n 8, train_cutoff FY2025, walk_forward_mae 38.5. I select two-year persistence because it has the lower walk-forward MAE for this horizon."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate / reference class: comparable complete registered-query prints are FY2017-FY2025 obligations values of 328.0B, 365.9B, 391.3B, 431.9B, 395.3B, 424.5B, 467.3B, 456.9B, and 501.5B. This reference class has mean level 418.1B, median level 424.5B, range 328.0B-501.5B, annual changes +37.9B, +25.4B, +40.5B, -36.6B, +29.2B, +42.8B, -10.3B, and +44.6B, and annual-change sigma 29.5B. FY2026 is excluded from the base rate because it is an incomplete year-to-date value.","Model candidates under thesis_model_candidate_v1, summarized in trace: two-year persistence uses the FY2025 completed registered-query print as point 501.5, p10 463.8, p50 501.5, p90 539.3, 80% interval [463.8, 539.3], 90% interval [453.2, 549.9], interval_method annual-change residual normal, calibration_n 8, train_cutoff FY2025, walk_forward_mae 30.0 over FY2021-FY2025 two-year-origin backtests. A two-year mean-change drift candidate has point 544.9, p10 507.2, p50 544.9, p90 582.6, 80% interval [507.2, 582.6], 90% interval [496.5, 593.3], interval_method annual-change residual normal, calibration_n 8, train_cutoff FY2025, walk_forward_mae 38.5. I select two-year persistence because it has the lower walk-forward MAE for this horizon."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence prior = 501.5B from the completed FY2025 registered-query print; historical sample = FY2017-FY2025 complete values with successive annual changes 37.9, 25.4, 40.5, -36.6, 29.2, 42.8, -10.3, and 44.6B; adjustment components = -8.0B judgmental no-FY2027-NDAA adjustment, because authorization delay can slow program direction but USAspending prime award obligations are funded by appropriations and execution, not by the authorization act alone. Interval method = annual-change residual, sigma = 29.5B, nominal 80% half-width = 1.28*sigma = 1.28*29.5 = 37.7B; I widen by 1.5x to 56.6B for the two-fiscal-year horizon and conditional legislative uncertainty. Point = 501.5 - 8.0 = 493.5B; interval = 493.5 +/- 56.6 = [436.9, 550.1]B after rounding to 0.1B.","Sanity and falsification: a +/-56.6B interval around prior-year prints would have covered all 8 fetched annual changes from FY2018-FY2025. Downside risk outside the interval would be a long continuing resolution, delayed appropriations, DoD award timing slippage, or deobligation cleanup that would land below the interval. Upside risk outside the interval would be large late-FY procurement or RDT&E awards, supplemental defense appropriations, or unusually fast USAspending posting that would land above the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Registered target fields inspected this run: catalogSlug us-dod-prime-award-obligations-fy2027-no-fy27-ndaa; period 2027; unit billions USD; dataPointId usaspending.dod.prime_award_obligations.2027.registered_query_snapshot.no_fy27_ndaa; conditionDeadline 2026-12-31; sourceUrl https://api.usaspending.gov/api/v2/agency/097/awards/?fiscal_year={fiscal_year}; field obligations; transform factor 1e-9; expectedReleaseWindow start 2027-10-15 and end 2027-10-22.","Tool result: Fetched USAspending agency 097 awards obligations from the registered endpoint: FY2017 obligations 327990949917.96 USD = 327.991B, transaction_count 3689848; FY2018 obligations 365937501255.11 USD = 365.938B, transaction_count 4528752; FY2019 obligations 391333992872.89 USD = 391.334B, transaction_count 4359716; FY2020 obligations 431883672152.30 USD = 431.884B, transaction_count 4059194; FY2021 obligations 395332709399.53 USD = 395.333B, transaction_count 4362064."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-dod-prime-award-obligations-fy2027-no-fy27-ndaa\nrunLabel: Headline\nresolutionDate: 2027-10-22\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.cps-healthcare-support-employment-august-2026.2026-08-13T16-52-26Z.dbbe9aa72729c5d9","runId":"run.cps-healthcare-support-employment-august-2026.2026-08-13T16-52-26Z.dbbe9aa72729c5d9","predictionId":"cps-healthcare-support-employment-august-2026","specId":"spec.cps-healthcare-support-employment-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["The outside-view base rate/reference class is last-print persistence from the latest same-table first-print value: July 2026 = 5.797 million. The fetched same-row history is thin but exact: June 2025 5.950, July 2025 6.038, June 2026 5.691, July 2026 5.797 million. It shows the 2026 level running below 2025, while the latest June-to-July movement was positive.","Prior/update/interval: persistence model prior = 5.797 million; historical sample = 5.950, 6.038, 5.691, and 5.797 million. Successive changes are +0.088, -0.347, and +0.106 million, giving sample sigma = 0.257 million. No material current evidence clears the update test for moving more than one rounding unit away from persistence, so adjustment components are +0.000 momentum, +0.000 one-off, and +0.000 policy, yielding point = 5.797 million. The 80% half-width is roughly 1.28*sigma = 1.28*0.257 = 0.329 million, implying 5.797-0.329 = 5.468 and 5.797+0.329 = 6.126, rounded to [5.469, 6.125] million. The interval is wide because the realized first-print changes in this CPS occupation subgroup are noisy and the fetched same-row sample is sparse."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The resolver is the first August 2026 BLS CPS Employment Situation Table A-19 print for employed people age 16 and over in 'Healthcare support occupations,' not seasonally adjusted. Table values are published in thousands and converted to millions with the registered 0.001 multiplier.","Tool call: Fetch current BLS Table A-19 at https://www.bls.gov/web/empsit/cpseea19.htm"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is the first August 2026 BLS CPS Employment Situation Table A-19 print for employed people age 16 and over in 'Healthcare support occupations,' not seasonally adjusted. Table values are published in thousands and converted to millions with the registered 0.001 multiplier.","Tool call: Verify official release date at https://www.bls.gov/schedule/2026/home.htm"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.66, distribution present, forecast step count 1.","evidence":["Model candidates under thesis_model_candidate_v1: persistence candidate point = 5.797, p10 = 5.469, p50 = 5.797, p90 = 6.125, 80% interval = [5.469, 6.125], 90% interval = [5.374, 6.220], intervalMethod = sample-change residual 1.28*sigma and 1.645*sigma, calibration_n = 3 changes, trainCutoff = 2026-07, walkForwardScore = not estimated because only four comparable first-print observations were fetched. No stronger open-source candidate is admissible from this thin sample.","Prior/update/interval: persistence model prior = 5.797 million; historical sample = 5.950, 6.038, 5.691, and 5.797 million. Successive changes are +0.088, -0.347, and +0.106 million, giving sample sigma = 0.257 million. No material current evidence clears the update test for moving more than one rounding unit away from persistence, so adjustment components are +0.000 momentum, +0.000 one-off, and +0.000 policy, yielding point = 5.797 million. The 80% half-width is roughly 1.28*sigma = 1.28*0.257 = 0.329 million, implying 5.797-0.329 = 5.468 and 5.797+0.329 = 6.126, rounded to [5.469, 6.125] million. The interval is wide because the realized first-print changes in this CPS occupation subgroup are noisy and the fetched same-row sample is sparse."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Model candidates under thesis_model_candidate_v1: persistence candidate point = 5.797, p10 = 5.469, p50 = 5.797, p90 = 6.125, 80% interval = [5.469, 6.125], 90% interval = [5.374, 6.220], intervalMethod = sample-change residual 1.28*sigma and 1.645*sigma, calibration_n = 3 changes, trainCutoff = 2026-07, walkForwardScore = not estimated because only four comparable first-print observations were fetched. No stronger open-source candidate is admissible from this thin sample.","Prior/update/interval: persistence model prior = 5.797 million; historical sample = 5.950, 6.038, 5.691, and 5.797 million. Successive changes are +0.088, -0.347, and +0.106 million, giving sample sigma = 0.257 million. No material current evidence clears the update test for moving more than one rounding unit away from persistence, so adjustment components are +0.000 momentum, +0.000 one-off, and +0.000 policy, yielding point = 5.797 million. The 80% half-width is roughly 1.28*sigma = 1.28*0.257 = 0.329 million, implying 5.797-0.329 = 5.468 and 5.797+0.329 = 6.126, rounded to [5.469, 6.125] million. The interval is wide because the realized first-print changes in this CPS occupation subgroup are noisy and the fetched same-row sample is sparse."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The outside-view base rate/reference class is last-print persistence from the latest same-table first-print value: July 2026 = 5.797 million. The fetched same-row history is thin but exact: June 2025 5.950, July 2025 6.038, June 2026 5.691, July 2026 5.797 million. It shows the 2026 level running below 2025, while the latest June-to-July movement was positive.","Upside risk: a strong August CPS sample for healthcare aides, labor-force entry, late-summer healthcare staffing, or rebound in service occupations would land above the interval at more than 6.125 million. Downside risk: adverse CPS rotation/sample noise in healthcare support, weaker healthcare support participation, or a sharp late-summer employment pullback would land below the interval at less than 5.469 million and outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["August 2026 healthcare support employment forecast","Model candidates under thesis_model_candidate_v1: persistence candidate point = 5.797, p10 = 5.469, p50 = 5.797, p90 = 6.125, 80% interval = [5.469, 6.125], 90% interval = [5.374, 6.220], intervalMethod = sample-change residual 1.28*sigma and 1.645*sigma, calibration_n = 3 changes, trainCutoff = 2026-07, walkForwardScore = not estimated because only four comparable first-print observations were fetched. No stronger open-source candidate is admissible from this thin sample."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: cps-healthcare-support-employment-august-2026\nrunLabel: Headline\nresolutionDate: 2026-09-04\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.cps-production-employment-august-2026.2026-08-13T17-02-02Z.cd9f6fa2343b0563","runId":"run.cps-production-employment-august-2026.2026-08-13T17-02-02Z.cd9f6fa2343b0563","predictionId":"cps-production-employment-august-2026","specId":"spec.cps-production-employment-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool call: Compute thesis_model_candidate_v1-style baselines from fetched LNU02032213 history, excluding the blank 2025-10 observation and using only consecutive-month changes for residual sigma.","The outside-view base rate/reference class is latest-print persistence at 8.121 million for this repeated official series. The direct same-series July-to-August NSA reference class is small but relevant: August was below July by 0.112 million in 2024 and 0.180 million in 2025, average -0.146 million. Because the question is August NSA employment and that seasonal comparison is direct, I select the seasonal candidate over pure persistence while keeping the update inside the realized month-to-month volatility."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["The registered target is BLS CPS employed people in Production occupations for August 2026, not seasonally adjusted, first print, from cpseea19.htm Table A-19. The FRED/BLS mirror labels the same current-population-survey occupation release table as A-13 and gives source code LNU02032213; I use it only as the sanctioned history mirror and keep the ledger resolver as Table A-19.","Tool call: curl -sS 'https://fred.stlouisfed.org/series/LNU02032213' | rg -n -C 2 'Employment Level - Production Occupations|Jul 2026|LNU02032213|Thousands of Persons|Not Seasonally Adjusted|Source'"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The registered target is BLS CPS employed people in Production occupations for August 2026, not seasonally adjusted, first print, from cpseea19.htm Table A-19. The FRED/BLS mirror labels the same current-population-survey occupation release table as A-13 and gives source code LNU02032213; I use it only as the sanctioned history mirror and keep the ledger resolver as Table A-19.","Tool call: curl -sS 'https://fred.stlouisfed.org/release/tables?eid=3149&rid=50' | sed -n '1008,1038p'"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.54, distribution present, forecast step count 1.","evidence":["Tool call: curl -sS 'https://fred.stlouisfed.org/graph/fredgraph.csv?id=LNU02032213' | tail -n 25","Tool result: Persistence candidate: point 8.121, p10 7.849, p50 8.121, p90 8.393, 80% interval [7.849, 8.393], 90% interval [7.772, 8.470], interval_method residual_sigma_22, calibration_n 22, train_cutoff 2026-07. Seasonal July-to-August candidate: recent Jul-Aug changes are -0.112 million in 2024 and -0.180 million in 2025, mean -0.146; point 7.975, p10 7.703, p50 7.975, p90 8.247, 80% interval [7.703, 8.247], 90% interval [7.626, 8.324], interval_method residual_sigma_22, calibration_n 22, train_cutoff 2026-07."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The outside-view base rate/reference class is latest-print persistence at 8.121 million for this repeated official series. The direct same-series July-to-August NSA reference class is small but relevant: August was below July by 0.112 million in 2024 and 0.180 million in 2025, average -0.146 million. Because the question is August NSA employment and that seasonal comparison is direct, I select the seasonal candidate over pure persistence while keeping the update inside the realized month-to-month volatility."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The outside-view base rate/reference class is latest-print persistence at 8.121 million for this repeated official series. The direct same-series July-to-August NSA reference class is small but relevant: August was below July by 0.112 million in 2024 and 0.180 million in 2025, average -0.146 million. Because the question is August NSA employment and that seasonal comparison is direct, I select the seasonal candidate over pure persistence while keeping the update inside the realized month-to-month volatility.","Upside risk: if July's +0.362 million rebound reflects real production-occupation hiring rather than household-survey noise, or if August avoids the recent NSA seasonal decline, the print would land above the interval at more than 8.247 million. Downside risk: if the July spike reverses like the larger negative months in 2024-2025 or production employment follows manufacturing weakness, it would land below the interval at less than 7.703 million. Either case would be outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["August 2026 CPS production-occupation employment forecast","Tool result: Persistence candidate: point 8.121, p10 7.849, p50 8.121, p90 8.393, 80% interval [7.849, 8.393], 90% interval [7.772, 8.470], interval_method residual_sigma_22, calibration_n 22, train_cutoff 2026-07. Seasonal July-to-August candidate: recent Jul-Aug changes are -0.112 million in 2024 and -0.180 million in 2025, mean -0.146; point 7.975, p10 7.703, p50 7.975, p90 8.247, 80% interval [7.703, 8.247], 90% interval [7.626, 8.324], interval_method residual_sigma_22, calibration_n 22, train_cutoff 2026-07."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: cps-production-employment-august-2026\nrunLabel: Headline\nresolutionDate: 2026-09-10\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.cps-transport-material-moving-employment-august-2026.2026-08-13T17-06-34Z.f3ca30095e2e5a07","runId":"run.cps-transport-material-moving-employment-august-2026.2026-08-13T17-06-34Z.f3ca30095e2e5a07","predictionId":"cps-transport-material-moving-employment-august-2026","specId":"spec.cps-transport-material-moving-employment-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 7 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the strongest benchmark is July-level persistence because this is a noisy not-seasonally-adjusted CPS occupation level and no walk-forward evidence here beats persistence. Recent fetched levels run 12.202, 11.737, 12.214, 12.127, 12.120, 12.010, and 12.223 million, with a range of 11.737 to 12.223 million; the two observed July-to-August seasonal changes are mixed at +0.345 and -0.012 million.","Prior/update/interval: persistence prior = July 2026 first print 12.223 million; historical sample = fetched January-July 2026 first-print levels plus 2024-2025 July-to-August same-row reference class; adjustment components = +0.25*0.1665 = +0.041625 million August seasonal pull and 0.000 million for current payroll context, giving 12.223 + 0.041625 = 12.264625 million, rounded to point 12.26. Successive fetched 2026 changes are -0.465, +0.477, -0.087, -0.007, -0.110, and +0.213 million; sample sigma = 0.319 million. The 80% half-width is 1.28*sigma = 1.28*0.319 = 0.408 million, so 12.26 - 0.408 = 11.852 and 12.26 + 0.408 = 12.668, rounded to 11.85 to 12.67."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 6 typed tool call(s), 12 source-context item(s), activity log present.","evidence":["The resolver is the BLS CPS occupation table row 'Transportation and material moving occupations,' total age 16 years and over, not seasonally adjusted, first August 2026 print, reported in thousands and converted to millions. The ledger binds cpseea19/Table A-19; current BLS release navigation exposes the same occupation table as Table A-13, so I keep the registered source URL and target identity.","Tool call: Checked the current BLS Employment Situation release notice and registered target context."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is the BLS CPS occupation table row 'Transportation and material moving occupations,' total age 16 years and over, not seasonally adjusted, first August 2026 print, reported in thousands and converted to millions. The ledger binds cpseea19/Table A-19; current BLS release navigation exposes the same occupation table as Table A-13, so I keep the registered source URL and target identity.","Tool call: Checked the current BLS Employment Situation release notice and registered target context."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.82, distribution present, forecast step count 1.","evidence":["Tool result: Candidate persistence: point 12.223, p10 11.815, p50 12.223, p90 12.631, 80% interval [11.815, 12.631], 90% interval [11.698, 12.748], interval_method recent_change_normal_sigma_0.319, calibration_n 6, train_cutoff 2026-07, walk_forward_score unavailable. Candidate seasonal-shrunken persistence: point 12.265, p10 11.856, p50 12.265, p90 12.673, 80% interval [11.856, 12.673], 90% interval [11.739, 12.790], interval_method recent_change_normal_sigma_0.319, calibration_n 6, train_cutoff 2026-07, walk_forward_score unavailable.","Prior/update/interval: persistence prior = July 2026 first print 12.223 million; historical sample = fetched January-July 2026 first-print levels plus 2024-2025 July-to-August same-row reference class; adjustment components = +0.25*0.1665 = +0.041625 million August seasonal pull and 0.000 million for current payroll context, giving 12.223 + 0.041625 = 12.264625 million, rounded to point 12.26. Successive fetched 2026 changes are -0.465, +0.477, -0.087, -0.007, -0.110, and +0.213 million; sample sigma = 0.319 million. The 80% half-width is 1.28*sigma = 1.28*0.319 = 0.408 million, so 12.26 - 0.408 = 11.852 and 12.26 + 0.408 = 12.668, rounded to 11.85 to 12.67."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate/reference class: the strongest benchmark is July-level persistence because this is a noisy not-seasonally-adjusted CPS occupation level and no walk-forward evidence here beats persistence. Recent fetched levels run 12.202, 11.737, 12.214, 12.127, 12.120, 12.010, and 12.223 million, with a range of 11.737 to 12.223 million; the two observed July-to-August seasonal changes are mixed at +0.345 and -0.012 million.","Review disposition: accepted the coherence critique by restating the unrounded seasonal adjustment as +0.041625 million, which keeps the 12.26 point estimate internally consistent. I retained the registered 2026-09-10 resolutionDate while explicitly noting the checked BLS September 4, 2026 scheduled release discrepancy, because the ledger target contract instructs this cell to stay tied to the registered target identity."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Inside-view update: the August seasonal sample points up on average, but it is only two years and highly dispersed. July 2026 already rebounded +0.213 million from June, and the establishment-survey transportation and warehousing context was little changed, so I use only 25 percent of the +0.1665 million seasonal average rather than a full seasonal add.","Upside risk: another August seasonal gain like 2024's +0.345 million, combined with sampling noise after July's rebound, would land above the interval. Downside risk: a reversal of July's CPS jump, weak household employment, or logistics-sector weakness would land below the interval; either tail would be outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["August 2026 CPS transportation and material-moving employment forecast","Tool result: Candidate persistence: point 12.223, p10 11.815, p50 12.223, p90 12.631, 80% interval [11.815, 12.631], 90% interval [11.698, 12.748], interval_method recent_change_normal_sigma_0.319, calibration_n 6, train_cutoff 2026-07, walk_forward_score unavailable. Candidate seasonal-shrunken persistence: point 12.265, p10 11.856, p50 12.265, p90 12.673, 80% interval [11.856, 12.673], 90% interval [11.739, 12.790], interval_method recent_change_normal_sigma_0.319, calibration_n 6, train_cutoff 2026-07, walk_forward_score unavailable."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: cps-transport-material-moving-employment-august-2026\nrunLabel: Headline\nresolutionDate: 2026-09-10\ntraceLineCount: 20\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.cps-business-financial-employment-august-2026.2026-08-13T16-41-03Z.191fcc28624aede1","runId":"run.cps-business-financial-employment-august-2026.2026-08-13T16-41-03Z.191fcc28624aede1","predictionId":"cps-business-financial-employment-august-2026","specId":"spec.cps-business-financial-employment-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate / reference class: the same-row recent level history available this run is 10.291, 10.195, 10.033, 9.720, and 9.835 million. The trailing observed range is 9.720-10.291 million, and last-print persistence from July 2026 is 9.835 million. No direct August-specific official signal was fetched that clears the update test, so persistence is the prior and the forecast point. The Wayback-derived history is forecast evidence for recent first-print dispersion; the resolver remains the official BLS Table A-19 URL in the registered target.","Prior/update/interval: prior = persistence.last_print from July 2026 = 9.835 million; historical sample = same-row A-19 levels 2026-01, 2026-03, 2026-05, 2026-06, 2026-07; successive changes = -0.096, -0.162, -0.313, +0.115 million, so sigma = 0.178 million using sample standard deviation. Update components = 0.000 million because no release-specific current signal justifies moving more than one rounding unit from persistence. Interval method = realized successive-change sigma; 80% half-width = 1.28*sigma = 1.28*0.178 = 0.227 million, giving 9.835 - 0.227 = 9.608 and 9.835 + 0.227 = 10.062. This final symmetric interval intentionally uses realized same-row volatility rather than the persistence helper's narrower upper p90 output."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 7 source-context item(s), activity log present.","evidence":["BLS CPS A-19 occupation employment forecast","The target is the BLS CPS Employment Situation Table A-19 row 'Business and financial operations occupations,' total age 16 years and over, not seasonally adjusted, for August 2026, first print, transformed from thousands to millions. The canonical Thesis target fixes slug, unit, dataPointId, source URL, and resolutionDate."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the BLS CPS Employment Situation Table A-19 row 'Business and financial operations occupations,' total age 16 years and over, not seasonally adjusted, for August 2026, first print, transformed from thousands to millions. The canonical Thesis target fixes slug, unit, dataPointId, source URL, and resolutionDate.","Tool call: Open https://www.bls.gov/schedule/news_release/empsit.htm / BLS schedule result for Employment Situation"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.45, distribution present, forecast step count 1.","evidence":["Tool result: thesis_model_candidate_v1 persistence.last_print: trainCutoff 2026-07, pointEstimate 9.835, p10 9.567, p50 9.835, p90 9.887, interval80 lower 9.567 upper 9.887, calibrationN 4, walk_forward_1_step rows 4, meanAbsoluteError 0.1715.","Prior/update/interval: prior = persistence.last_print from July 2026 = 9.835 million; historical sample = same-row A-19 levels 2026-01, 2026-03, 2026-05, 2026-06, 2026-07; successive changes = -0.096, -0.162, -0.313, +0.115 million, so sigma = 0.178 million using sample standard deviation. Update components = 0.000 million because no release-specific current signal justifies moving more than one rounding unit from persistence. Interval method = realized successive-change sigma; 80% half-width = 1.28*sigma = 1.28*0.178 = 0.227 million, giving 9.835 - 0.227 = 9.608 and 9.835 + 0.227 = 10.062. This final symmetric interval intentionally uses realized same-row volatility rather than the persistence helper's narrower upper p90 output."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: prior = persistence.last_print from July 2026 = 9.835 million; historical sample = same-row A-19 levels 2026-01, 2026-03, 2026-05, 2026-06, 2026-07; successive changes = -0.096, -0.162, -0.313, +0.115 million, so sigma = 0.178 million using sample standard deviation. Update components = 0.000 million because no release-specific current signal justifies moving more than one rounding unit from persistence. Interval method = realized successive-change sigma; 80% half-width = 1.28*sigma = 1.28*0.178 = 0.227 million, giving 9.835 - 0.227 = 9.608 and 9.835 + 0.227 = 10.062. This final symmetric interval intentionally uses realized same-row volatility rather than the persistence helper's narrower upper p90 output."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-consideration: downside risk outside the interval would come from another occupation-cell drop like the May-to-June move plus broader household employment weakness, which would land below 9.608 million. Upside risk outside the interval would come from a reversal of the June drop plus stronger white-collar hiring or classification mix, which would land above 10.062 million."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["BLS CPS A-19 occupation employment forecast","The target is the BLS CPS Employment Situation Table A-19 row 'Business and financial operations occupations,' total age 16 years and over, not seasonally adjusted, for August 2026, first print, transformed from thousands to millions. The canonical Thesis target fixes slug, unit, dataPointId, source URL, and resolutionDate."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: cps-business-financial-employment-august-2026\nrunLabel: Headline\nresolutionDate: 2026-09-11\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.abs-labour-employment-change-australia-august-2026.2026-08-13T17-09-13Z.dfa8074d29c5e187","runId":"run.abs-labour-employment-change-australia-august-2026.2026-08-13T17-09-13Z.dfa8074d29c5e187","predictionId":"abs-labour-employment-change-australia-august-2026","specId":"spec.abs-labour-employment-change-australia-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 7 historical point(s) and explicit outside-view language.","evidence":["Tool result: Computed recent changes in thousands from fetched ABS LF/M3.3.1599.20.AUS.M levels: 2026-02 +22.9, 2026-03 +20.3, 2026-04 -38.6, 2026-05 +44.0, 2026-06 +76.3; last 24 changes had mean +20.9, median +32.0, sample sigma 39.7, min -74.8, max +104.0.","Base rate / reference class: using the last 24 fetched same-series month-over-month employment changes through June 2026, the distribution is mean +20.9 thousand, median +32.0 thousand, sample sigma 39.7 thousand, range -74.8 to +104.0 thousand. Last-print persistence at +76.3 thousand is a high-side June spike and had materially worse walk-forward error than recent-mean candidates, so I use the trailing/recent-mean model as the outside-view prior."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Tool call: curl -sS 'https://data.api.abs.gov.au/rest/data/LF/M3.3.1599.20.AUS.M?lastNObservations=30&format=jsondata'","Tool result: Model candidates for 2026-08 employment change, train_cutoff 2026-06, calibration_n 24: persistence point +76.3 with 80% interval +25.6 to +127.1; trailing12mean point +21.0 with 80% interval -29.8 to +71.8; last24mean point +20.9 with 80% interval -29.8 to +71.7. Walk-forward calibration over 17 observations: persistence MAE 56.7 RMSE 66.7; trailing12mean MAE 38.9 RMSE 47.8; expandingmean MAE 36.4 RMSE 46.7."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Framing and resolver: the registered target is abs.labour.employment_change.australia for August 2026, unit thousands, dataPointId abs.labour.employment_change.australia.august_2026.first_print, and catalog slug abs-labour-employment-change-australia-august-2026. The canonical sourceBinding URL returns ABS employed-person levels in thousands for LF/M3.3.1599.20.AUS.M; this forecast preserves the registered employment-change target and treats the resolving value as the same-release month-over-month difference.","Tool call: curl -sSL https://www.abs.gov.au/release-calendar/future-releases/202609 and extract the Labour Force, Australia row"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 101.6, distribution present, forecast step count 1.","evidence":["Tool result: Model candidates for 2026-08 employment change, train_cutoff 2026-06, calibration_n 24: persistence point +76.3 with 80% interval +25.6 to +127.1; trailing12mean point +21.0 with 80% interval -29.8 to +71.8; last24mean point +20.9 with 80% interval -29.8 to +71.7. Walk-forward calibration over 17 observations: persistence MAE 56.7 RMSE 66.7; trailing12mean MAE 38.9 RMSE 47.8; expandingmean MAE 36.4 RMSE 46.7.","Prior/update/interval: selected prior = trailing12mean/last24mean blend centered at +21.0 thousand because trailing12mean point +21.0 and last24mean point +20.9 are effectively identical, with no official July print or direct August-specific signal fetched this run to justify a material deviation. Adjustment components: +0.0 thousand current-evidence update, since the June +76.3 spike is already in the fetched history and persistence underperformed in walk-forward tests. Interval method = normal wrapper from last-24 realized change dispersion; sigma = 39.7 thousand, 80% half-width = 1.28*sigma = 1.28*39.7 = 50.8 thousand, so 21.0 - 50.8 = -29.8 and 21.0 + 50.8 = 71.8."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: selected prior = trailing12mean/last24mean blend centered at +21.0 thousand because trailing12mean point +21.0 and last24mean point +20.9 are effectively identical, with no official July print or direct August-specific signal fetched this run to justify a material deviation. Adjustment components: +0.0 thousand current-evidence update, since the June +76.3 spike is already in the fetched history and persistence underperformed in walk-forward tests. Interval method = normal wrapper from last-24 realized change dispersion; sigma = 39.7 thousand, 80% half-width = 1.28*sigma = 1.28*39.7 = 50.8 thousand, so 21.0 - 50.8 = -29.8 and 21.0 + 50.8 = 71.8.","Review disposition: accepted the optional clarity suggestion by tightening the resolver discussion around the registered employment-change target and ABS level-series mechanics. Rejected removing the specs.json entry because it was actually fetched during slug checking, even though it returned 404 and was not affirmative source evidence."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate / reference class: using the last 24 fetched same-series month-over-month employment changes through June 2026, the distribution is mean +20.9 thousand, median +32.0 thousand, sample sigma 39.7 thousand, range -74.8 to +104.0 thousand. Last-print persistence at +76.3 thousand is a high-side June spike and had materially worse walk-forward error than recent-mean candidates, so I use the trailing/recent-mean model as the outside-view prior.","Counter-consideration: upside risk outside the interval would be another broad hiring surge or survey rotation effect that keeps the August same-vintage employment gain above +71.8 thousand; downside risk outside the interval would be payback after June's unusually strong gain, weaker vacancies, or a participation/labour-demand softening that pulls the August change below -29.8 thousand."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Framing and resolver: the registered target is abs.labour.employment_change.australia for August 2026, unit thousands, dataPointId abs.labour.employment_change.australia.august_2026.first_print, and catalog slug abs-labour-employment-change-australia-august-2026. The canonical sourceBinding URL returns ABS employed-person levels in thousands for LF/M3.3.1599.20.AUS.M; this forecast preserves the registered employment-change target and treats the resolving value as the same-release month-over-month difference.","Tool result: Model candidates for 2026-08 employment change, train_cutoff 2026-06, calibration_n 24: persistence point +76.3 with 80% interval +25.6 to +127.1; trailing12mean point +21.0 with 80% interval -29.8 to +71.8; last24mean point +20.9 with 80% interval -29.8 to +71.7. Walk-forward calibration over 17 observations: persistence MAE 56.7 RMSE 66.7; trailing12mean MAE 38.9 RMSE 47.8; expandingmean MAE 36.4 RMSE 46.7."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: abs-labour-employment-change-australia-august-2026\nrunLabel: Headline\nresolutionDate: 2026-09-24\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.belgium-nbb-business-barometer-august-2026.2026-08-13T07-20-15Z.3a8bc9fa794455ee","runId":"run.belgium-nbb-business-barometer-august-2026.2026-08-13T07-20-15Z.3a8bc9fa794455ee","predictionId":"belgium-nbb-business-barometer-august-2026","specId":"spec.belgium-nbb-business-barometer-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: trailing 12 official NBB total synthetic-curve prints range from -14.2 to -7.9 and average -11.2; the latest six average -13.2, the latest three average -12.5, and the latest print is -11.9. Because persistence beats the trailing-3 mean in the walk-forward check, the outside-view base rate and strongest benchmark is last-print persistence at -11.9.","Prior/update/interval: persistence prior = -11.9 from the July 2026 official print; historical sample = NBB total synthetic curve 2025-08 through 2026-07 with changes +1.0,-1.2,+0.9,-3.7,+3.1,-4.9,+0.0,-0.5,+0.9,+0.9,+0.5. Adjustment components: +0.2 for recent improvement momentum, -0.2 for mixed sector composition and no direct August signal, net 0.0, so point = -11.9. For the interval, sigma = 2.28 from successive fetched monthly changes; 1.28*sigma = 2.91, widened modestly to half-width 3.2 because only 7 of the last 10 changes fit within 2.91 while 8 of 10 fit within 3.2. Final 80% bounds: -11.9 - 3.2 = -15.1 and -11.9 + 3.2 = -8.7."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing and resolver: the registered target is nbb.business_barometer.overall for 2026-08, country BE, unit index_points, dataPointId nbb.business_barometer.overall.2026-08.first_print, and ledger resolutionDate 2026-08-28. The exact resolving series is the National Bank of Belgium monthly business surveys overall synthetic curve, Belgium, total sector, seasonally adjusted, first print. I fetched https://app.thesisinstitute.org/specs.json during the run; it returned a 404 HTML page rather than a usable specs JSON, so I kept the registered ledger slug belgium-nbb-business-barometer-august-2026.","Tool result: Fetched NBB DSD at prepared time 2026-08-13T07:17:04Z. Dimension order is 1 FREQ, 2 BUSSURVM_INDICATOR, 3 BE_AREA, 4 BUSSURV_SECTOR, 5 BUSSURVM_ADJ, 6 TIME_PERIOD; target key is M.SYNC.BE.A999.S, with DECIMALS=1 for one-decimal index-point observations."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Framing and resolver: the registered target is nbb.business_barometer.overall for 2026-08, country BE, unit index_points, dataPointId nbb.business_barometer.overall.2026-08.first_print, and ledger resolutionDate 2026-08-28. The exact resolving series is the National Bank of Belgium monthly business surveys overall synthetic curve, Belgium, total sector, seasonally adjusted, first print. I fetched https://app.thesisinstitute.org/specs.json during the run; it returned a 404 HTML page rather than a usable specs JSON, so I kept the registered ledger slug belgium-nbb-business-barometer-august-2026.","Counter-consideration and falsification: upside risk is a broad August improvement in manufacturing and trade matching July's services rebound, which would land above the interval if the first print is -8.6 or higher. Downside risk is renewed trade/export weakness or cost-pressure pessimism spreading across sectors, which would land below the interval if the first print is -15.2 or lower. Either outside the interval would be a sharper one-month move than the widened recent-change reference class expects."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6.4, distribution present, forecast step count 1.","evidence":["Tool result: thesis_model_candidate_v1 persistence candidate: point -11.9, p10 -15.1, p50 -11.9, p90 -8.7, interval80 [-15.1,-8.7], interval90 [-15.6,-8.2], intervalMethod residual_change_sigma_widened, calibration_n 11, trainCutoff 2026-07, walkForwardMae 1.60. trailing3_mean candidate: point -12.5, p10 -15.7, p50 -12.5, p90 -9.3, interval80 [-15.7,-9.3], interval90 [-16.2,-8.8], intervalMethod residual_change_sigma_widened, calibration_n 9, trainCutoff 2026-07, walkForwardMae 1.84.","Prior/update/interval: persistence prior = -11.9 from the July 2026 official print; historical sample = NBB total synthetic curve 2025-08 through 2026-07 with changes +1.0,-1.2,+0.9,-3.7,+3.1,-4.9,+0.0,-0.5,+0.9,+0.9,+0.5. Adjustment components: +0.2 for recent improvement momentum, -0.2 for mixed sector composition and no direct August signal, net 0.0, so point = -11.9. For the interval, sigma = 2.28 from successive fetched monthly changes; 1.28*sigma = 2.91, widened modestly to half-width 3.2 because only 7 of the last 10 changes fit within 2.91 while 8 of 10 fit within 3.2. Final 80% bounds: -11.9 - 3.2 = -15.1 and -11.9 + 3.2 = -8.7."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate/reference class: trailing 12 official NBB total synthetic-curve prints range from -14.2 to -7.9 and average -11.2; the latest six average -13.2, the latest three average -12.5, and the latest print is -11.9. Because persistence beats the trailing-3 mean in the walk-forward check, the outside-view base rate and strongest benchmark is last-print persistence at -11.9.","Prior/update/interval: persistence prior = -11.9 from the July 2026 official print; historical sample = NBB total synthetic curve 2025-08 through 2026-07 with changes +1.0,-1.2,+0.9,-3.7,+3.1,-4.9,+0.0,-0.5,+0.9,+0.9,+0.5. Adjustment components: +0.2 for recent improvement momentum, -0.2 for mixed sector composition and no direct August signal, net 0.0, so point = -11.9. For the interval, sigma = 2.28 from successive fetched monthly changes; 1.28*sigma = 2.91, widened modestly to half-width 3.2 because only 7 of the last 10 changes fit within 2.91 while 8 of 10 fit within 3.2. Final 80% bounds: -11.9 - 3.2 = -15.1 and -11.9 + 3.2 = -8.7."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Inside-view update: July had a third consecutive improvement from the April trough, and business-related services improved from -7.4 to -3.8, but trade worsened from -9.3 to -10.8 and manufacturing was nearly flat at -15.5. With no direct August survey signal before the print, I do not move materially away from the persistence benchmark.","Counter-consideration and falsification: upside risk is a broad August improvement in manufacturing and trade matching July's services rebound, which would land above the interval if the first print is -8.6 or higher. Downside risk is renewed trade/export weakness or cost-pressure pessimism spreading across sectors, which would land below the interval if the first print is -15.2 or lower. Either outside the interval would be a sharper one-month move than the widened recent-change reference class expects."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Belgium August 2026 NBB Business Barometer Forecast","Framing and resolver: the registered target is nbb.business_barometer.overall for 2026-08, country BE, unit index_points, dataPointId nbb.business_barometer.overall.2026-08.first_print, and ledger resolutionDate 2026-08-28. The exact resolving series is the National Bank of Belgium monthly business surveys overall synthetic curve, Belgium, total sector, seasonally adjusted, first print. I fetched https://app.thesisinstitute.org/specs.json during the run; it returned a 404 HTML page rather than a usable specs JSON, so I kept the registered ledger slug belgium-nbb-business-barometer-august-2026."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: belgium-nbb-business-barometer-august-2026\nrunLabel: Headline\nresolutionDate: 2026-08-28\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.belgium-cpi-annual-rate-august-2026.2026-08-13T07-07-42Z.d812113f0121b1ec","runId":"run.belgium-cpi-annual-rate-august-2026.2026-08-13T07-07-42Z.d812113f0121b1ec","predictionId":"belgium-cpi-annual-rate-august-2026","specId":"spec.belgium-cpi-annual-rate-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Framing: this target is Statbel's national not-seasonally-adjusted headline consumer price index annual inflation field MS_CPI_INFL for August 2026, base year 2025, first print. The series is not a human-adjudicated market outcome; it resolves mechanically from Statbel's CPI/health-index release or the matching official open-data file.","Tool call: download and parse Statbel CPI All base years TXT from the official ZIP"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing: this target is Statbel's national not-seasonally-adjusted headline consumer price index annual inflation field MS_CPI_INFL for August 2026, base year 2025, first print. The series is not a human-adjudicated market outcome; it resolves mechanically from Statbel's CPI/health-index release or the matching official open-data file.","Tool result: Fetched official Statbel open-data listing: 'Consumer price index and health index', period since 1920, TXT ZIP length 106388 and XLSX length 422150; also 'Indexes by product group' XLSX length 14536586 and ZIP length 5128865."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing: this target is Statbel's national not-seasonally-adjusted headline consumer price index annual inflation field MS_CPI_INFL for August 2026, base year 2025, first print. The series is not a human-adjudicated market outcome; it resolves mechanically from Statbel's CPI/health-index release or the matching official open-data file.","Tool call: curl Statbel 2026 calendar around CPI/health-index releases"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.69, distribution present, forecast step count 1.","evidence":["Model candidates: persistence candidate point 3.56, p10 2.72, p50 3.56, p90 4.40, 80% interval [2.72, 4.40], 90% interval [2.47, 4.65], interval method recent-change Gaussian with calibration_n 23 and train cutoff 2026-07. Bias-adjusted FPB candidate uses FPB August 3.35 plus the July forecast miss of +0.19, giving point 3.54 with the same interval method.","Prior/update/interval: persistence prior is 3.56 from Statbel July 2026. Historical sample is the last 24 fetched MS_CPI_INFL values from 2024-08 through 2026-07; successive monthly changes have sigma = 0.659 percentage points, so 1.28*sigma = 0.843 pp. Current update is the FPB August forecast 3.35, adjusted by its July undercall versus Statbel first print (3.56 - 3.37 = +0.19), giving 3.54. Weighting 70% persistence and 30% bias-adjusted FPB gives 0.70*3.56 + 0.30*3.54 = 3.55. Applying the 0.843 half-width gives [2.71, 4.40]."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-considerations: upside risk would land above the interval if August repeats an energy or administered-price jump like the March-to-April 2026 move and headline inflation exceeds 4.40%. Downside risk would land below the interval if the July rebound reverses sharply through energy, travel, or communication-price cuts and the first print falls below 2.71%."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Belgium Statbel CPI headline annual inflation forecast","Tool call: curl Federal Planning Bureau CPI inflation forecasts page dated 07/07/2026"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: belgium-cpi-annual-rate-august-2026\nrunLabel: Headline\nresolutionDate: 2026-09-03\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.belgium-health-index-annual-rate-august-2026.2026-08-13T07-10-48Z.221e736ef47cbeef","runId":"run.belgium-health-index-annual-rate-august-2026.2026-08-13T07-10-48Z.221e736ef47cbeef","predictionId":"belgium-health-index-annual-rate-august-2026","specId":"spec.belgium-health-index-annual-rate-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool call: Fetched be.STAT health-index-by-base-year table e8fad1c0-5270-4d62-9118-0999ee8cb323.","Tool result: be.STAT view 'Health index since 1994, by base year, last 13 months' was last changed 30/07/2026 12:22 GMT+0200. For base year 2025=100 it reports July 2025 100.02, August 2025 100.05, June 2026 102.59, and July 2026 103.24 for the Health index. Computed July 2026 annual rate = 103.24/100.02 - 1 = 3.22%."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["The target is the registered Statbel health-index year-over-year rate for August 2026, first print. The ledger target country is BE even though the older exploratory cell menu omitted Belgium; I preserve the registered BE target identity. The public specs check at app.thesisinstitute.org/specs.json returned a 404 HTML page in this run, so I rely on the registered local target slug rather than a live specs JSON confirmation.","Tool result: The local registered target gives catalogSlug belgium-health-index-annual-rate-august-2026, dataPointId statbel.health_index.yoy.2026-08.first_print, targetUnit percent, expectedReleaseWindow 2026-08-26 to 2026-09-03, and generated ledger resolutionDate 2026-09-03. Statbel's CPI page states results are available on the penultimate working day of the reference period; for August 2026 the final working day is 2026-08-31 and the penultimate working day is 2026-08-28, inside the registered bound."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the registered Statbel health-index year-over-year rate for August 2026, first print. The ledger target country is BE even though the older exploratory cell menu omitted Belgium; I preserve the registered BE target identity. The public specs check at app.thesisinstitute.org/specs.json returned a 404 HTML page in this run, so I rely on the registered local target slug rather than a live specs JSON confirmation.","Tool call: Checked the registered target and publication-date basis for statbel.health_index.yoy.2026-08.first_print."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.2, distribution present, forecast step count 1.","evidence":["Model candidates under thesis_model_candidate_v1: persistence from the latest Statbel health-index level gives point 3.19%, p10 2.1, p50 3.2, p90 4.3, 80% interval [2.1, 4.3], 90% interval [1.7, 4.7], interval_method successive-yoy-change sigma, calibration_n 6, train_cutoff 2026-07, walk_forward_score not estimated because the current-base first-print sample is short. FPB benchmark gives point 3.21% from its July forecast table. I select persistence/FPB agreement rounded to 3.2%.","Prior/update/interval: Start with the last-print persistence prior 103.24/100.05 - 1 = 3.188%, weight 80%, and the FPB public benchmark 3.21%, weight 20%; no material inside-view adjustment because the FPB benchmark and persistence agree within 0.03 pp and no direct August Statbel component evidence is available before the first print. Rounded point = 3.2%. For the interval, use successive changes in fetched/derived Jan-Jul health-index annual rates: +0.31, -0.30, +2.00, +0.10, -0.49, +0.23 pp; sample sigma = 0.89 pp, so 1.28*sigma = 1.14 pp. Rounded 80% interval = 3.2 +/- 1.1 = [2.1, 4.3]."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Model candidates under thesis_model_candidate_v1: persistence from the latest Statbel health-index level gives point 3.19%, p10 2.1, p50 3.2, p90 4.3, 80% interval [2.1, 4.3], 90% interval [1.7, 4.7], interval_method successive-yoy-change sigma, calibration_n 6, train_cutoff 2026-07, walk_forward_score not estimated because the current-base first-print sample is short. FPB benchmark gives point 3.21% from its July forecast table. I select persistence/FPB agreement rounded to 3.2%.","Prior/update/interval: Start with the last-print persistence prior 103.24/100.05 - 1 = 3.188%, weight 80%, and the FPB public benchmark 3.21%, weight 20%; no material inside-view adjustment because the FPB benchmark and persistence agree within 0.03 pp and no direct August Statbel component evidence is available before the first print. Rounded point = 3.2%. For the interval, use successive changes in fetched/derived Jan-Jul health-index annual rates: +0.31, -0.30, +2.00, +0.10, -0.49, +0.23 pp; sample sigma = 0.89 pp, so 1.28*sigma = 1.14 pp. Rounded 80% interval = 3.2 +/- 1.1 = [2.1, 4.3]."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Upside risk: a large August increase in health-index-covered energy, rents, package holidays, or services would land above the interval, especially because July energy was still 109.41 on the 2025=100 base. Downside risk: a reversal in energy and travel prices or another broad monthly fall in the health index would land below the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Belgium August 2026 Health-Index Inflation Forecast","Tool result: The local registered target gives catalogSlug belgium-health-index-annual-rate-august-2026, dataPointId statbel.health_index.yoy.2026-08.first_print, targetUnit percent, expectedReleaseWindow 2026-08-26 to 2026-09-03, and generated ledger resolutionDate 2026-09-03. Statbel's CPI page states results are available on the penultimate working day of the reference period; for August 2026 the final working day is 2026-08-31 and the penultimate working day is 2026-08-28, inside the registered bound."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: belgium-health-index-annual-rate-august-2026\nrunLabel: Headline\nresolutionDate: 2026-09-03\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.japan-tokyo-cpi-annual-rate-august-2026-prelim.2026-08-13T07-04-09Z.d70bbbc202f5ddf2","runId":"run.japan-tokyo-cpi-annual-rate-august-2026-prelim.2026-08-13T07-04-09Z.d70bbbc202f5ddf2","predictionId":"japan-tokyo-cpi-annual-rate-august-2026-prelim","specId":"spec.japan-tokyo-cpi-annual-rate-august-2026-prelim","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Framing: the target is Japan Statistics Bureau CPI for the Ku-area of Tokyo, all-items, August 2026 preliminary mid-month first print, non-seasonally adjusted, unit percent. Ledger discrepancy noted: the canonical target fixes resolutionDate 2026-09-04 and a 2020-base table-1-2 binding, while the official schedule fetched this run lists August 28, 2026 for the August Tokyo preliminary release and labels it the 2025-base CPI revision release.","Tool result: Fetched official CPI schedule: Last Update 23 January 2026; Ku-area of Tokyo preliminary August survey month date of release is August 28, 2026; the same row's remarks say Revision to 2025-Base Consumer Price Index. The ledger supplied resolutionDate is 2026-09-04, so the cell preserves 2026-09-04 and records the discrepancy."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 7 source-context item(s), activity log present.","evidence":["Framing: the target is Japan Statistics Bureau CPI for the Ku-area of Tokyo, all-items, August 2026 preliminary mid-month first print, non-seasonally adjusted, unit percent. Ledger discrepancy noted: the canonical target fixes resolutionDate 2026-09-04 and a 2020-base table-1-2 binding, while the official schedule fetched this run lists August 28, 2026 for the August Tokyo preliminary release and labels it the 2025-base CPI revision release.","Tool result: Fetched official CPI schedule: Last Update 23 January 2026; Ku-area of Tokyo preliminary August survey month date of release is August 28, 2026; the same row's remarks say Revision to 2025-Base Consumer Price Index. The ledger supplied resolutionDate is 2026-09-04, so the cell preserves 2026-09-04 and records the discrepancy."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing: the target is Japan Statistics Bureau CPI for the Ku-area of Tokyo, all-items, August 2026 preliminary mid-month first print, non-seasonally adjusted, unit percent. Ledger discrepancy noted: the canonical target fixes resolutionDate 2026-09-04 and a 2020-base table-1-2 binding, while the official schedule fetched this run lists August 28, 2026 for the August Tokyo preliminary release and labels it the 2025-base CPI revision release.","Tool result: Fetched official CPI schedule: Last Update 23 January 2026; Ku-area of Tokyo preliminary August survey month date of release is August 28, 2026; the same row's remarks say Revision to 2025-Base Consumer Price Index. The ledger supplied resolutionDate is 2026-09-04, so the cell preserves 2026-09-04 and records the discrepancy."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1, distribution present, forecast step count 1.","evidence":["Model candidates under thesis_model_candidate_v1: persistence_yoy has point 1.6, p10 1.3, p50 1.6, p90 1.9, 80% interval [1.3, 1.9], 90% interval [1.2, 2.0], train cutoff 2026-06, interval method successive-yoy-change residual sigma from revised 2025-base history, calibration_n 11. mean_recent_yoy_change has point 1.5, p10 1.1, p50 1.5, p90 1.8, 80% interval [1.1, 1.8], 90% interval [1.0, 1.9], same interval method and calibration_n 11. I select persistence as the prior and adjust only modestly because the July signal is old-base.","Prior/update/interval: persistence prior is revised 2025-base June 2026 all-items YoY at 1.6. Historical sample is the last 12 revised 2025-base YoY values through 2026-06; successive changes are -0.2, -0.3, +0.3, -0.2, -0.7, -0.3, +0.0, -0.1, -0.1, -0.1, +0.3 percentage point, so sigma = 0.267. Adjustment components: +0.15 pp for the fetched old-base July preliminary rise to 2.0%, +0.05 pp for August base-revision transition/current-food-energy uncertainty, giving 1.6 + 0.15 + 0.05 = 1.8. The raw 80% half-width is roughly 1.28*sigma = 1.28*0.267 = 0.342 pp; I widen to 0.5 pp, 1.46x raw, because the revised-methodology history lacks a July 2026 print and August is the scheduled base-revision release. Final implied bounds: 1.8 - 0.5 = 1.3 and 1.8 + 0.5 = 2.3."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Model candidates under thesis_model_candidate_v1: persistence_yoy has point 1.6, p10 1.3, p50 1.6, p90 1.9, 80% interval [1.3, 1.9], 90% interval [1.2, 2.0], train cutoff 2026-06, interval method successive-yoy-change residual sigma from revised 2025-base history, calibration_n 11. mean_recent_yoy_change has point 1.5, p10 1.1, p50 1.5, p90 1.8, 80% interval [1.1, 1.8], 90% interval [1.0, 1.9], same interval method and calibration_n 11. I select persistence as the prior and adjust only modestly because the July signal is old-base.","Prior/update/interval: persistence prior is revised 2025-base June 2026 all-items YoY at 1.6. Historical sample is the last 12 revised 2025-base YoY values through 2026-06; successive changes are -0.2, -0.3, +0.3, -0.2, -0.7, -0.3, +0.0, -0.1, -0.1, -0.1, +0.3 percentage point, so sigma = 0.267. Adjustment components: +0.15 pp for the fetched old-base July preliminary rise to 2.0%, +0.05 pp for August base-revision transition/current-food-energy uncertainty, giving 1.6 + 0.15 + 0.05 = 1.8. The raw 80% half-width is roughly 1.28*sigma = 1.28*0.267 = 0.342 pp; I widen to 0.5 pp, 1.46x raw, because the revised-methodology history lacks a July 2026 print and August is the scheduled base-revision release. Final implied bounds: 1.8 - 0.5 = 1.3 and 1.8 + 0.5 = 2.3."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool result: Fetched latest old-method Tokyo table 1-2 workbook statInfId=000040475902 published 2026-07-31. All-items code 0001: 2026-06 index 112.7 and YoY 1.7%; 2026-07 preliminary index 113.2 and YoY 2.0%. This is a current directional signal but not the revised 2025-base history.","Prior/update/interval: persistence prior is revised 2025-base June 2026 all-items YoY at 1.6. Historical sample is the last 12 revised 2025-base YoY values through 2026-06; successive changes are -0.2, -0.3, +0.3, -0.2, -0.7, -0.3, +0.0, -0.1, -0.1, -0.1, +0.3 percentage point, so sigma = 0.267. Adjustment components: +0.15 pp for the fetched old-base July preliminary rise to 2.0%, +0.05 pp for August base-revision transition/current-food-energy uncertainty, giving 1.6 + 0.15 + 0.05 = 1.8. The raw 80% half-width is roughly 1.28*sigma = 1.28*0.267 = 0.342 pp; I widen to 0.5 pp, 1.46x raw, because the revised-methodology history lacks a July 2026 print and August is the scheduled base-revision release. Final implied bounds: 1.8 - 0.5 = 1.3 and 1.8 + 0.5 = 2.3."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for Tokyo all-items CPI annual rate, August 2026 preliminary","Tool result: Checked live specs endpoint for slug japan-tokyo-cpi-annual-rate-august-2026-prelim: contains_target_slug=False; response body returned a 404 shell, so no duplicate slug was found from the fetched endpoint."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: japan-tokyo-cpi-annual-rate-august-2026-prelim\nrunLabel: Headline\nresolutionDate: 2026-09-04\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-personal-transfer-payments-q2-2026.2026-08-13T06-59-12Z.8b177e41079f38fd","runId":"run.us-personal-transfer-payments-q2-2026.2026-08-13T06-59-12Z.8b177e41079f38fd","predictionId":"us-personal-transfer-payments-q2-2026","specId":"spec.us-personal-transfer-payments-q2-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate / reference class: the last 12 comparable BEA iTable observations available before the 2026-Q2 first print range from 16,749 to 18,737 usd_millions, with the latest four prints 18,641, 18,596, 18,552, and 18,511. These modeling values may reflect the current/revised iTable history available at draft time, while the target itself resolves only to the 2026-Q2 first print. The default base rate prior for this repeated level series is last-print persistence at 18,511 because recent changes are modest and no direct Q2 pre-release signal was fetched.","Prior/update/interval: selected prior is last-print persistence from BEA Table 5.1 line 18 QSA, 2026-Q1 = 18,511 usd_millions. Historical sample is the last 12 fetched quarterly values, with successive changes [325, 425, 524, 382, 237, 95, -49, -47, -45, -44, -41]. Adjustment components: recent momentum is about -41 to -49 per quarter, but the material-deviation threshold is max(1 rounding unit, 25% of the 80% band) = max(1, 191), so no direct evidence justifies moving the point away from persistence. For interval, sigma = 223.597 from successive changes; 1.28*sigma = 286.204. I widen the half-width to 382, about 1.34x the 1.28*sigma width, because the same fetched 12-quarter reference class includes 2023-2024 transition changes up to 524 and a 382 width covers 8 of the last 10 one-step changes. Final implied bounds: 18,511 - 382 = 18,129 and 18,511 + 382 = 18,893 usd_millions."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this forecasts BEA U.S. International Transactions Table 5.1, line 18, Personal transfers, quarterly seasonally adjusted, for 2026-Q2, first print only, in millions of dollars. The registered ledger target binds slug, unit, dataPointId, sourceSeriesId ITA:T5.1:L18:QSA, and the BEA iTable resolver.","Tool call: curl -sS https://www.bea.gov/news/schedule and parse the schedule row for U.S. International Transactions and Investment Position, 2nd Quarter 2026"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["BEA Personal Transfers Q2 2026 First Print","Framing and exact resolver: this forecasts BEA U.S. International Transactions Table 5.1, line 18, Personal transfers, quarterly seasonally adjusted, for 2026-Q2, first print only, in millions of dollars. The registered ledger target binds slug, unit, dataPointId, sourceSeriesId ITA:T5.1:L18:QSA, and the BEA iTable resolver."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 764, distribution present, forecast step count 1.","evidence":["Tool call: Compute thesis_model_candidate_v1 persistence candidate from fetched BEA values, using successive changes for interval calibration","Tool result: Generated persistence candidate: point=18511, p10=18225, p50=18511, p90=18797, ci80=[18225,18797], ci90=[18143,18879], interval_method=1.28*sample_stdev_successive_changes_last_12_official_iTable_prints, calibration_n=11, train_cutoff=2026-Q1, walk_forward_mae_last8=117.5. Successive changes were 325, 425, 524, 382, 237, 95, -49, -47, -45, -44, -41."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: Fetched slug-check endpoint https://app.thesisinstitute.org/specs.json: HTTP 404 with 11289-byte HTML error page; fetched app root: HTTP 200 with 384682-byte forecasts page. Because the required specs JSON was unavailable, I keep the registered catalogSlug us-personal-transfer-payments-q2-2026 rather than inventing an alternate slug.","Base rate / reference class: the last 12 comparable BEA iTable observations available before the 2026-Q2 first print range from 16,749 to 18,737 usd_millions, with the latest four prints 18,641, 18,596, 18,552, and 18,511. These modeling values may reflect the current/revised iTable history available at draft time, while the target itself resolves only to the 2026-Q2 first print. The default base rate prior for this repeated level series is last-print persistence at 18,511 because recent changes are modest and no direct Q2 pre-release signal was fetched."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: selected prior is last-print persistence from BEA Table 5.1 line 18 QSA, 2026-Q1 = 18,511 usd_millions. Historical sample is the last 12 fetched quarterly values, with successive changes [325, 425, 524, 382, 237, 95, -49, -47, -45, -44, -41]. Adjustment components: recent momentum is about -41 to -49 per quarter, but the material-deviation threshold is max(1 rounding unit, 25% of the 80% band) = max(1, 191), so no direct evidence justifies moving the point away from persistence. For interval, sigma = 223.597 from successive changes; 1.28*sigma = 286.204. I widen the half-width to 382, about 1.34x the 1.28*sigma width, because the same fetched 12-quarter reference class includes 2023-2024 transition changes up to 524 and a 382 width covers 8 of the last 10 one-step changes. Final implied bounds: 18,511 - 382 = 18,129 and 18,511 + 382 = 18,893 usd_millions.","Upside risk: a renewed broad rise in secondary-income personal transfers like the 2023-Q4 to 2024-Q1 jump of +524 would land above the interval. Downside risk: a sharper reversal in personal-transfer payments, larger than the recent -41 to -49 declines and worse than -382 from Q1, would land below the interval. Outside the interval would require a Q2 level below 18,129 or above 18,893."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Framing and exact resolver: this forecasts BEA U.S. International Transactions Table 5.1, line 18, Personal transfers, quarterly seasonally adjusted, for 2026-Q2, first print only, in millions of dollars. The registered ledger target binds slug, unit, dataPointId, sourceSeriesId ITA:T5.1:L18:QSA, and the BEA iTable resolver.","Tool result: Fetched slug-check endpoint https://app.thesisinstitute.org/specs.json: HTTP 404 with 11289-byte HTML error page; fetched app root: HTTP 200 with 384682-byte forecasts page. Because the required specs JSON was unavailable, I keep the registered catalogSlug us-personal-transfer-payments-q2-2026 rather than inventing an alternate slug."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-personal-transfer-payments-q2-2026\nrunLabel: Headline\nresolutionDate: 2026-09-24\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.belgium-unemployment-rate-august-2026.2026-08-13T07-14-07Z.b758e133d776e4f9","runId":"run.belgium-unemployment-rate-august-2026.2026-08-13T07-14-07Z.b758e133d776e4f9","predictionId":"belgium-unemployment-rate-august-2026","specId":"spec.belgium-unemployment-rate-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the last 23 comparable Eurostat Belgium total SA monthly unemployment prints run from 5.7% to 6.4%, mean 6.139%, median 6.2%, and latest 6.3%. The last 22 month-to-month changes are +0.1, 0.0, +0.1, +0.1, +0.1, +0.1, 0.0, -0.1, -0.1, +0.1, 0.0, 0.0, +0.2, +0.1, 0.0, 0.0, -0.1, 0.0, -0.1, 0.0, +0.1, 0.0 pp. Last-print persistence is the prior because its walk-forward MAE, 0.056 pp, beats mean-change drift's 0.082 pp.","Prior/update/interval: prior = selected persistence candidate at 6.3 from the fetched 2024-08 to 2026-06 official history; adjustment components = 0.0 pp momentum update and 0.0 pp current-evidence update because no direct public release-specific signal was fetched that clears the update test; point = 6.3 + 0.0 + 0.0 = 6.3. Interval method = two-step raw monthly-change volatility, equivalent to persistence residual changes, because July and August are both unreleased from the June latest print. From the 22 fetched monthly changes, sigma = 0.083 pp; two-step sigma = sqrt(2)*0.083 = 0.117 pp; 80% half-width = 1.28*0.117 = 0.150 pp. Raw 80% interval is 6.3 +/- 0.150 = [6.150, 6.450], widened to one-decimal published bounds [6.1, 6.5] to avoid understating discrete publication rounding over a two-month horizon."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing: the registered target is Eurostat une_rt_m, monthly seasonally adjusted unemployment, Belgium, total sex, total age, percentage of population in the labour force, for August 2026, first print. The canonical ledger binds slug belgium-unemployment-rate-august-2026, unit percent, dataPointId eurostat.une_rt_m.unemployment_rate.belgium.2026_08.first_print, and resolutionDate 2026-10-05. I keep that ledger resolutionDate and note the official Eurostat calendar event separately.","Tool result: Official Eurostat calendar JSON returned 1 event: recordid 22494146, title Unemployment, period August 2026, start 2026-10-01T11:00Z, datasetCodes une_rt_m, euroind true, preliminary false."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing: the registered target is Eurostat une_rt_m, monthly seasonally adjusted unemployment, Belgium, total sex, total age, percentage of population in the labour force, for August 2026, first print. The canonical ledger binds slug belgium-unemployment-rate-august-2026, unit percent, dataPointId eurostat.une_rt_m.unemployment_rate.belgium.2026_08.first_print, and resolutionDate 2026-10-05. I keep that ledger resolutionDate and note the official Eurostat calendar event separately.","Prior/update/interval: prior = selected persistence candidate at 6.3 from the fetched 2024-08 to 2026-06 official history; adjustment components = 0.0 pp momentum update and 0.0 pp current-evidence update because no direct public release-specific signal was fetched that clears the update test; point = 6.3 + 0.0 + 0.0 = 6.3. Interval method = two-step raw monthly-change volatility, equivalent to persistence residual changes, because July and August are both unreleased from the June latest print. From the 22 fetched monthly changes, sigma = 0.083 pp; two-step sigma = sqrt(2)*0.083 = 0.117 pp; 80% half-width = 1.28*0.117 = 0.150 pp. Raw 80% interval is 6.3 +/- 0.150 = [6.150, 6.450], widened to one-decimal published bounds [6.1, 6.5] to avoid understating discrete publication rounding over a two-month horizon."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.4, distribution present, forecast step count 1.","evidence":["Tool result: thesis_model_candidate_v1 persistence: point 6.3, p10 6.1, p50 6.3, p90 6.5, 80 interval [6.1, 6.5], 90 interval [6.1, 6.5], interval_method two-step raw monthly-change residual sigma rounded/widened to one decimal, calibration_n 22 changes, train_cutoff 2026-06, walk_forward_mae 0.056. Mean-change drift candidate: point about 6.4 from mean monthly change +0.027, walk_forward_mae 0.082, weaker than persistence.","Prior/update/interval: prior = selected persistence candidate at 6.3 from the fetched 2024-08 to 2026-06 official history; adjustment components = 0.0 pp momentum update and 0.0 pp current-evidence update because no direct public release-specific signal was fetched that clears the update test; point = 6.3 + 0.0 + 0.0 = 6.3. Interval method = two-step raw monthly-change volatility, equivalent to persistence residual changes, because July and August are both unreleased from the June latest print. From the 22 fetched monthly changes, sigma = 0.083 pp; two-step sigma = sqrt(2)*0.083 = 0.117 pp; 80% half-width = 1.28*0.117 = 0.150 pp. Raw 80% interval is 6.3 +/- 0.150 = [6.150, 6.450], widened to one-decimal published bounds [6.1, 6.5] to avoid understating discrete publication rounding over a two-month horizon."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate/reference class: the last 23 comparable Eurostat Belgium total SA monthly unemployment prints run from 5.7% to 6.4%, mean 6.139%, median 6.2%, and latest 6.3%. The last 22 month-to-month changes are +0.1, 0.0, +0.1, +0.1, +0.1, +0.1, 0.0, -0.1, -0.1, +0.1, 0.0, 0.0, +0.2, +0.1, 0.0, 0.0, -0.1, 0.0, -0.1, 0.0, +0.1, 0.0 pp. Last-print persistence is the prior because its walk-forward MAE, 0.056 pp, beats mean-change drift's 0.082 pp.","Prior/update/interval: prior = selected persistence candidate at 6.3 from the fetched 2024-08 to 2026-06 official history; adjustment components = 0.0 pp momentum update and 0.0 pp current-evidence update because no direct public release-specific signal was fetched that clears the update test; point = 6.3 + 0.0 + 0.0 = 6.3. Interval method = two-step raw monthly-change volatility, equivalent to persistence residual changes, because July and August are both unreleased from the June latest print. From the 22 fetched monthly changes, sigma = 0.083 pp; two-step sigma = sqrt(2)*0.083 = 0.117 pp; 80% half-width = 1.28*0.117 = 0.150 pp. Raw 80% interval is 6.3 +/- 0.150 = [6.150, 6.450], widened to one-decimal published bounds [6.1, 6.5] to avoid understating discrete publication rounding over a two-month horizon."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Upside risk outside the interval: a July-August deterioration like the 2025-08 to 2025-10 rise of +0.3 pp, or a country-specific labour-force shock, would land above the interval. Downside risk outside the interval: a renewed two-month improvement matching or exceeding the 2026-02 to 2026-04 decline of -0.1 pp plus additional acceleration would land below the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Framing: the registered target is Eurostat une_rt_m, monthly seasonally adjusted unemployment, Belgium, total sex, total age, percentage of population in the labour force, for August 2026, first print. The canonical ledger binds slug belgium-unemployment-rate-august-2026, unit percent, dataPointId eurostat.une_rt_m.unemployment_rate.belgium.2026_08.first_print, and resolutionDate 2026-10-05. I keep that ledger resolutionDate and note the official Eurostat calendar event separately.","Tool result: thesis_model_candidate_v1 persistence: point 6.3, p10 6.1, p50 6.3, p90 6.5, 80 interval [6.1, 6.5], 90 interval [6.1, 6.5], interval_method two-step raw monthly-change residual sigma rounded/widened to one decimal, calibration_n 22 changes, train_cutoff 2026-06, walk_forward_mae 0.056. Mean-change drift candidate: point about 6.4 from mean monthly change +0.027, walk_forward_mae 0.082, weaker than persistence."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: belgium-unemployment-rate-august-2026\nrunLabel: Headline\nresolutionDate: 2026-10-05\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.initial-claims-week-2026-08-15.2026-08-12T21-25-05Z.ffe22805bcb0c5da","runId":"run.initial-claims-week-2026-08-15.2026-08-12T21-25-05Z.ffe22805bcb0c5da","predictionId":"initial-claims-week-2026-08-15","specId":"spec.initial-claims-week-2026-08-15","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 3 historical point(s) and explicit outside-view language.","evidence":["Base rate / reference class: the last 24 fetched weekly ICSA prints run from 211.0 thousand on 2026-02-21 to 199.0 thousand on 2026-08-01, with range 189.0-230.0 thousand. The latest three prints were 189.0, 198.0, and 199.0 thousand. For this two-week-ahead target, recent two-week changes over the fetched window ranged from -28.0 to +22.0 thousand, with 8 of the last 10 two-week changes within +/-15.9 thousand.","Prior/update/interval: prior = two-week last-print persistence model candidate using 24 fetched ICSA prints through 2026-08-01; adjustment components = 0.0 thousand because no direct current signal cleared the update test; interval method = normal residual interval from fetched two-week changes. Two-week changes were +2, -9, -2, -2, +7, +5, -3, -18, -16, +22, +11, +0, +15, +18, +2, -14, -10, +1, -8, -28, -11, +10 thousand; sigma = 12.43 thousand; half-width = 1.28*sigma = 15.91 thousand; implied 80% bounds = 199.0 +/- 15.91 = [183.09, 214.91], rounded to [183, 215]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The target is the registered U.S. DOL/FRED-ALFRED seasonally adjusted initial claims series ICSA for week ending 2026-08-15, first print, transformed from persons to thousands. The local generated ledger target gives slug initial-claims-week-2026-08-15, unit thousands, dataPointId us.dol.initial_claims.sa.week_2026-08-15, sourceBinding releasePolicy advance_vintage, and resolutionDate 2026-08-24. DOL weekly claims normally publish on Thursdays, so 2026-08-20 is the apparent release day inside the registered expectedReleaseWindow, but I keep the ledger target date and state the discrepancy.","Tool call: Read records/targets/2026-08-12-ba7909136ce260dfbd43442621dd88fdef9abd8d2b02c81dfcb114251a76b8bd.json and site/src/data/ledger-targets.generated.ts for this target."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the registered U.S. DOL/FRED-ALFRED seasonally adjusted initial claims series ICSA for week ending 2026-08-15, first print, transformed from persons to thousands. The local generated ledger target gives slug initial-claims-week-2026-08-15, unit thousands, dataPointId us.dol.initial_claims.sa.week_2026-08-15, sourceBinding releasePolicy advance_vintage, and resolutionDate 2026-08-24. DOL weekly claims normally publish on Thursdays, so 2026-08-20 is the apparent release day inside the registered expectedReleaseWindow, but I keep the ledger target date and state the discrepancy.","Tool result: Fetched target fields: catalogSlug initial-claims-week-2026-08-15; target unit thousands; dataPointId us.dol.initial_claims.sa.week_2026-08-15; source field ICSA; transform factor 0.001; expectedReleaseWindow start 2026-08-20 end 2026-08-24; generated resolutionDate 2026-08-24; targetContentHash ba7909136ce260dfbd43442621dd88fdef9abd8d2b02c81dfcb114251a76b8bd."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 32, distribution present, forecast step count 1.","evidence":["Tool result: Model candidate two_week_persistence_with_two_week_change_residual_interval: point 199.0, p10 183.2, p50 198.0, p90 213.6, 80% interval [183, 215], 90% interval [181, 217], calibration_n 22, train_cutoff 2026-08-01, walk-forward MAE 9.73 thousand, RMSE 12.21 thousand, sigma 12.43 thousand, half_width 15.91 thousand.","Prior/update/interval: prior = two-week last-print persistence model candidate using 24 fetched ICSA prints through 2026-08-01; adjustment components = 0.0 thousand because no direct current signal cleared the update test; interval method = normal residual interval from fetched two-week changes. Two-week changes were +2, -9, -2, -2, +7, +5, -3, -18, -16, +22, +11, +0, +15, +18, +2, -14, -10, +1, -8, -28, -11, +10 thousand; sigma = 12.43 thousand; half-width = 1.28*sigma = 15.91 thousand; implied 80% bounds = 199.0 +/- 15.91 = [183.09, 214.91], rounded to [183, 215]."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: prior = two-week last-print persistence model candidate using 24 fetched ICSA prints through 2026-08-01; adjustment components = 0.0 thousand because no direct current signal cleared the update test; interval method = normal residual interval from fetched two-week changes. Two-week changes were +2, -9, -2, -2, +7, +5, -3, -18, -16, +22, +11, +0, +15, +18, +2, -14, -10, +1, -8, -28, -11, +10 thousand; sigma = 12.43 thousand; half-width = 1.28*sigma = 15.91 thousand; implied 80% bounds = 199.0 +/- 15.91 = [183.09, 214.91], rounded to [183, 215]."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The target is the registered U.S. DOL/FRED-ALFRED seasonally adjusted initial claims series ICSA for week ending 2026-08-15, first print, transformed from persons to thousands. The local generated ledger target gives slug initial-claims-week-2026-08-15, unit thousands, dataPointId us.dol.initial_claims.sa.week_2026-08-15, sourceBinding releasePolicy advance_vintage, and resolutionDate 2026-08-24. DOL weekly claims normally publish on Thursdays, so 2026-08-20 is the apparent release day inside the registered expectedReleaseWindow, but I keep the ledger target date and state the discrepancy.","Tool result: DOL UI data PDF returned HTTP 200 with content-length 606807 and last-modified Thu, 06 Aug 2026 12:30:00 GMT; claims.asp returned the DOL Unemployment Insurance Weekly Claims Data page with final_yr value 2027. This supports the DOL weekly claims data source but did not provide a contrary target-specific 2026-08-24 date in the extracted response."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast ICSA for week ending 2026-08-15","The target is the registered U.S. DOL/FRED-ALFRED seasonally adjusted initial claims series ICSA for week ending 2026-08-15, first print, transformed from persons to thousands. The local generated ledger target gives slug initial-claims-week-2026-08-15, unit thousands, dataPointId us.dol.initial_claims.sa.week_2026-08-15, sourceBinding releasePolicy advance_vintage, and resolutionDate 2026-08-24. DOL weekly claims normally publish on Thursdays, so 2026-08-20 is the apparent release day inside the registered expectedReleaseWindow, but I keep the ledger target date and state the discrepancy."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: initial-claims-week-2026-08-15\nrunLabel: Headline\nresolutionDate: 2026-08-24\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.continued-claims-week-2026-08-15.2026-08-12T21-28-20Z.a0784653e0c6b135","runId":"run.continued-claims-week-2026-08-15.2026-08-12T21-28-20Z.a0784653e0c6b135","predictionId":"continued-claims-week-2026-08-15","specId":"spec.continued-claims-week-2026-08-15","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool result: DOL states the ETA Unemployment Insurance Weekly Claims release occurs each Thursday at 8:30 a.m. The DOL ETA release index showed Unemployment Insurance Weekly Claims Report dated August 6, 2026 for week ending August 1 with initial claims 199,000, prior revised from 197,000 to 198,000, and 4-week moving average 198,750; the prior report was July 30, 2026 for week ending July 25 with initial claims 197,000.","Tool result: thesis_model_candidate_v1 candidates: persistence point=1.801, p10=1.752, p50=1.801, p90=1.850, interval80=[1.752,1.850], interval90=[1.738,1.864], calibration_n=23, train_cutoff=2026-07-25, interval_method=horizon-scaled weekly-change residual; last24_mean point=1.803, p10=1.754, p90=1.852; four_week_drift_to_target point=1.786, p10=1.737, p90=1.835. Last-24 level distribution mean=1.803, median=1.800, min=1.758, max=1.871; weekly changes n=23, mean=-0.001, one-week sigma=0.022, three-week horizon sigma=sqrt(3)*0.022=0.038, 1.28*horizon sigma=0.049."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 6 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["Target is registered as continued-claims-week-2026-08-15 with unit millions and dataPointId dol.eta.continued_claims.sa.week_2026-08-15.first_print. The registered resolver uses ALFRED graph CSV series CCSA with factor 1e-6. The public specs endpoint requested by the harness returned HTTP 404 in this run, so I could not independently confirm catalog uniqueness there; I kept the canonical ledger slug.","Tool result: Fetched ALFRED CCSA header observation_date,CCSA_20260812. Last 24 values in millions included 2026-02-14=1.827, 2026-02-21=1.871, 2026-03-28=1.787, 2026-04-25=1.758, 2026-05-30=1.786, 2026-06-27=1.821, 2026-07-04=1.798, 2026-07-11=1.789, 2026-07-18=1.777, 2026-07-25=1.801."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Target is registered as continued-claims-week-2026-08-15 with unit millions and dataPointId dol.eta.continued_claims.sa.week_2026-08-15.first_print. The registered resolver uses ALFRED graph CSV series CCSA with factor 1e-6. The public specs endpoint requested by the harness returned HTTP 404 in this run, so I could not independently confirm catalog uniqueness there; I kept the canonical ledger slug.","Tool call: curl -L -sS 'https://www.dol.gov/newsroom/releases/opa/opa20200701' and curl -L -sS 'https://www.dol.gov/newsroom/releases/eta?date=2026&page=0'"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.1, distribution present, forecast step count 1.","evidence":["Tool call: curl -L -sS 'https://alfred.stlouisfed.org/graph/alfredgraph.csv?id=CCSA' | tail -n 25","Tool result: thesis_model_candidate_v1 candidates: persistence point=1.801, p10=1.752, p50=1.801, p90=1.850, interval80=[1.752,1.850], interval90=[1.738,1.864], calibration_n=23, train_cutoff=2026-07-25, interval_method=horizon-scaled weekly-change residual; last24_mean point=1.803, p10=1.754, p90=1.852; four_week_drift_to_target point=1.786, p10=1.737, p90=1.835. Last-24 level distribution mean=1.803, median=1.800, min=1.758, max=1.871; weekly changes n=23, mean=-0.001, one-week sigma=0.022, three-week horizon sigma=sqrt(3)*0.022=0.038, 1.28*horizon sigma=0.049."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate / reference class: last 24 weekly CCSA observations from ALFRED, transformed to millions, have mean 1.803, median 1.800, min 1.758, max 1.871. The strongest simple prior is last-print persistence at 1.801m because weekly changes are close to zero on average and the latest level is essentially the same as the 24-week center."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool result: thesis_model_candidate_v1 candidates: persistence point=1.801, p10=1.752, p50=1.801, p90=1.850, interval80=[1.752,1.850], interval90=[1.738,1.864], calibration_n=23, train_cutoff=2026-07-25, interval_method=horizon-scaled weekly-change residual; last24_mean point=1.803, p10=1.754, p90=1.852; four_week_drift_to_target point=1.786, p10=1.737, p90=1.835. Last-24 level distribution mean=1.803, median=1.800, min=1.758, max=1.871; weekly changes n=23, mean=-0.001, one-week sigma=0.022, three-week horizon sigma=sqrt(3)*0.022=0.038, 1.28*horizon sigma=0.049.","Prior/update/interval: prior = persistence candidate 1.801m from ALFRED CCSA 2026-07-25. Historical sample = 24 weekly values from 2026-02-14 through 2026-07-25, with successive changes used for volatility. Forecast horizon = three weekly observation steps from 2026-07-25 to 2026-08-15, so I scale one-week volatility by sqrt(3). Adjustment components: recent four-week drift is -0.005m per week and latest initial claims are low at 199k, but the implied drift candidate 1.786m is a material move from persistence without enough direct continued-claims evidence for week ending 2026-08-15, so weight persistence 90% and drift signal 10%, rounded back to 1.801m at published precision. Interval method = horizon-scaled weekly-change residual: one-week sigma is 0.022m, horizon sigma = sqrt(3)*0.022 = 0.038m, so sigma = 0.038m for the target horizon. Half-width = 1.28*sigma = 1.28*0.038 = 0.049m, so 80% interval = 1.801 +/- 0.049 = [1.752, 1.850]m."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Target is registered as continued-claims-week-2026-08-15 with unit millions and dataPointId dol.eta.continued_claims.sa.week_2026-08-15.first_print. The registered resolver uses ALFRED graph CSV series CCSA with factor 1e-6. The public specs endpoint requested by the harness returned HTTP 404 in this run, so I could not independently confirm catalog uniqueness there; I kept the canonical ledger slug.","Tool result: thesis_model_candidate_v1 candidates: persistence point=1.801, p10=1.752, p50=1.801, p90=1.850, interval80=[1.752,1.850], interval90=[1.738,1.864], calibration_n=23, train_cutoff=2026-07-25, interval_method=horizon-scaled weekly-change residual; last24_mean point=1.803, p10=1.754, p90=1.852; four_week_drift_to_target point=1.786, p10=1.737, p90=1.835. Last-24 level distribution mean=1.803, median=1.800, min=1.758, max=1.871; weekly changes n=23, mean=-0.001, one-week sigma=0.022, three-week horizon sigma=sqrt(3)*0.022=0.038, 1.28*horizon sigma=0.049."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: continued-claims-week-2026-08-15\nrunLabel: Headline\nresolutionDate: 2026-08-27\ntraceLineCount: 19\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-cpi-annual-rate-august-2026.2026-08-12T21-45-21Z.4cda521fe1402678","runId":"run.canada-cpi-annual-rate-august-2026.2026-08-12T21-45-21Z.4cda521fe1402678","predictionId":"canada-cpi-annual-rate-august-2026","specId":"spec.canada-cpi-annual-rate-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base rate / reference class: latest 18 transformed first-print YoY values from 2025-01 through 2026-06 have mean 2.232, range 1.727 to 3.226, q10 1.740 and q90 2.803. The strongest simple benchmark is last-print persistence at the June 2026 YoY value of 2.798, rounded to 2.8 percent.","Prior/update/interval: prior is last-print persistence, 2.798 percent from 2026-06. Historical sample is 18 transformed StatCan vector values from 2025-01 to 2026-06. Update components: +0.002 percentage point from the two-year June-to-August seasonal carry model, because 2024 and 2025 June-August cumulative index moves average 0.246 percent and imply August YoY 2.800; no additional current-evidence adjustment. Successive YoY changes are 0.750, -0.330, -0.572, -0.009, 0.125, -0.132, 0.127, 0.505, -0.196, 0.062, 0.132, -0.063, -0.515, 0.606, 0.430, 0.411, -0.428, so sigma = 0.394 percentage points and 1.28*sigma = 0.505. Rounded 80 percent interval is 2.8 +/- 0.5 = [2.3, 3.3]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Target is the registered Canada all-items CPI annual rate for August 2026. The ledger binds slug canada-cpi-annual-rate-august-2026, unit percent, dataPointId statcan.cpi.allitems.yoy.2026_08.first_print, StatCan vector v41690973, and first_print resolution. The registered expectedReleaseWindow has start=end 2026-09-14; a static fetch of the StatCan release calendar page did not expose the event row, so I used the ledger-bound release window and did not infer any alternate date from cadence. The specs.json check was used only for target identity and slug context, not for any forecast point or interval.","Tool call: curl -sS -H 'Content-Type: application/json' -X POST 'https://www150.statcan.gc.ca/t1/wds/rest/getDataFromVectorsAndLatestNPeriods' -d '[{\"vectorId\":41690973,\"latestN\":30}]'"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Canada CPI August 2026 First Print","Target is the registered Canada all-items CPI annual rate for August 2026. The ledger binds slug canada-cpi-annual-rate-august-2026, unit percent, dataPointId statcan.cpi.allitems.yoy.2026_08.first_print, StatCan vector v41690973, and first_print resolution. The registered expectedReleaseWindow has start=end 2026-09-14; a static fetch of the StatCan release calendar page did not expose the event row, so I used the ledger-bound release window and did not infer any alternate date from cadence. The specs.json check was used only for target identity and slug context, not for any forecast point or interval."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1, distribution present, forecast step count 1.","evidence":["Target is the registered Canada all-items CPI annual rate for August 2026. The ledger binds slug canada-cpi-annual-rate-august-2026, unit percent, dataPointId statcan.cpi.allitems.yoy.2026_08.first_print, StatCan vector v41690973, and first_print resolution. The registered expectedReleaseWindow has start=end 2026-09-14; a static fetch of the StatCan release calendar page did not expose the event row, so I used the ledger-bound release window and did not infer any alternate date from cadence. The specs.json check was used only for target identity and slug context, not for any forecast point or interval.","Tool result: thesis_model_candidate_v1: last_print_persistence_yoy point=2.8, p10=2.3, p50=2.8, p90=3.3, 80 interval=[2.3,3.3], 90 interval=[2.1,3.4], calibration_n=17, train_cutoff=2026-06; two-year_jul_aug_seasonal_carry_from_index point=2.8, p10=2.3, p50=2.8, p90=3.3, 80 interval=[2.3,3.3], 90 interval=[2.2,3.4], calibration_n=17, train_cutoff=2026-06."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: prior is last-print persistence, 2.798 percent from 2026-06. Historical sample is 18 transformed StatCan vector values from 2025-01 to 2026-06. Update components: +0.002 percentage point from the two-year June-to-August seasonal carry model, because 2024 and 2025 June-August cumulative index moves average 0.246 percent and imply August YoY 2.800; no additional current-evidence adjustment. Successive YoY changes are 0.750, -0.330, -0.572, -0.009, 0.125, -0.132, 0.127, 0.505, -0.196, 0.062, 0.132, -0.063, -0.515, 0.606, 0.430, 0.411, -0.428, so sigma = 0.394 percentage points and 1.28*sigma = 0.505. Rounded 80 percent interval is 2.8 +/- 0.5 = [2.3, 3.3]."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-consideration: upside risk outside the interval would require a sharper July-August price rise than the 2024-2025 seasonal carry, for example renewed energy or travel price spikes pushing the August index above about 170.2. Downside risk outside the interval would require July-August prices to fall enough to put the August index below about 168.6, such as broad gasoline and goods deflation."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Target is the registered Canada all-items CPI annual rate for August 2026. The ledger binds slug canada-cpi-annual-rate-august-2026, unit percent, dataPointId statcan.cpi.allitems.yoy.2026_08.first_print, StatCan vector v41690973, and first_print resolution. The registered expectedReleaseWindow has start=end 2026-09-14; a static fetch of the StatCan release calendar page did not expose the event row, so I used the ledger-bound release window and did not infer any alternate date from cadence. The specs.json check was used only for target identity and slug context, not for any forecast point or interval.","Tool result: thesis_model_candidate_v1: last_print_persistence_yoy point=2.8, p10=2.3, p50=2.8, p90=3.3, 80 interval=[2.3,3.3], 90 interval=[2.1,3.4], calibration_n=17, train_cutoff=2026-06; two-year_jul_aug_seasonal_carry_from_index point=2.8, p10=2.3, p50=2.8, p90=3.3, 80 interval=[2.3,3.3], 90 interval=[2.2,3.4], calibration_n=17, train_cutoff=2026-06."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-cpi-annual-rate-august-2026\nrunLabel: Headline\nresolutionDate: 2026-09-14\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-unemployment-rate-august-2026.2026-08-12T21-39-34Z.be7951953f6866f0","runId":"run.australia-unemployment-rate-august-2026.2026-08-12T21-39-34Z.be7951953f6866f0","predictionId":"australia-unemployment-rate-august-2026","specId":"spec.australia-unemployment-rate-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Base rate / reference class: last 24 fetched ABS monthly unemployment-rate levels, 2024-07 through 2026-06, had n=24, mean 4.1991, median 4.1633, min 3.9370, max 4.4905, level std 0.1507. The last 23 successive month-to-month changes had mean +0.0100 percentage points, sigma 0.1201, min -0.2062, max +0.2218. Last-print persistence is 2026-06 raw 4.42834371, published as 4.4, and the last-three average is 4.4301, also rounding to 4.4.","Prior/update/interval: prior is the thesis_model_candidate_v1 persistence.last_print benchmark from the fetched ABS history through 2026-06, point 4.4 after one-decimal publication rounding. Adjustment components: +0.0 for current official evidence because the latest ABS release only confirms June at 4.4 and the August print is still two monthly releases away; +0.0 for policy/one-off because no fetched official source identified an August-specific measurement change. For this level/rate series, one-month successive-change sigma = 0.1201 percentage points over the last 23 fetched changes; because the target is two reference months after the latest observed print, scale by sqrt(2), so sigma = 0.1698 percentage points. 1.28*sigma = 0.2173. Around point 4.4 this implies 4.1827 to 4.6173 before publication rounding; mapping to one-decimal published outcomes gives an 80% interval of 4.2 to 4.6 percent. Implied bounds: point 4.4, ciLow 4.2, ciHigh 4.6."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing: the registered target is ABS dataflow LF/M13.3.1599.20.AUS.M for August 2026, unemployment rate, persons, total age, seasonally adjusted, Australia, monthly percent, first print. The canonical ledger context binds slug australia-unemployment-rate-august-2026, unit percent, dataPointId abs.labour.unemployment_rate.2026_08.first_print, and the registered ABS Data API resolver.","Tool call: curl -sS https://data.api.abs.gov.au/rest/data/LF/M13.3.1599.20.AUS.M?lastNObservations=30&format=jsondata and parse SDMX JSON observations"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Australia Labour Force first-print forecast","Framing: the registered target is ABS dataflow LF/M13.3.1599.20.AUS.M for August 2026, unemployment rate, persons, total age, seasonally adjusted, Australia, monthly percent, first print. The canonical ledger context binds slug australia-unemployment-rate-august-2026, unit percent, dataPointId abs.labour.unemployment_rate.2026_08.first_print, and the registered ABS Data API resolver."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.4, distribution present, forecast step count 1.","evidence":["Tool result: thesis_model_candidate_v1 persistence.last_print generatedAt 2026-08-12T21:37:23Z: pointEstimate 4.4, p10 4.3, p50 4.4, p90 4.6, interval80 lower 4.3 upper 4.6, interval90 lower 4.2 upper 4.6, calibrationN 29, trainCutoff 2026-06, walk_forward_1_step meanAbsoluteError 0.10970723586206897.","Prior/update/interval: prior is the thesis_model_candidate_v1 persistence.last_print benchmark from the fetched ABS history through 2026-06, point 4.4 after one-decimal publication rounding. Adjustment components: +0.0 for current official evidence because the latest ABS release only confirms June at 4.4 and the August print is still two monthly releases away; +0.0 for policy/one-off because no fetched official source identified an August-specific measurement change. For this level/rate series, one-month successive-change sigma = 0.1201 percentage points over the last 23 fetched changes; because the target is two reference months after the latest observed print, scale by sqrt(2), so sigma = 0.1698 percentage points. 1.28*sigma = 0.2173. Around point 4.4 this implies 4.1827 to 4.6173 before publication rounding; mapping to one-decimal published outcomes gives an 80% interval of 4.2 to 4.6 percent. Implied bounds: point 4.4, ciLow 4.2, ciHigh 4.6."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: prior is the thesis_model_candidate_v1 persistence.last_print benchmark from the fetched ABS history through 2026-06, point 4.4 after one-decimal publication rounding. Adjustment components: +0.0 for current official evidence because the latest ABS release only confirms June at 4.4 and the August print is still two monthly releases away; +0.0 for policy/one-off because no fetched official source identified an August-specific measurement change. For this level/rate series, one-month successive-change sigma = 0.1201 percentage points over the last 23 fetched changes; because the target is two reference months after the latest observed print, scale by sqrt(2), so sigma = 0.1698 percentage points. 1.28*sigma = 0.2173. Around point 4.4 this implies 4.1827 to 4.6173 before publication rounding; mapping to one-decimal published outcomes gives an 80% interval of 4.2 to 4.6 percent. Implied bounds: point 4.4, ciLow 4.2, ciHigh 4.6.","Review disposition: accepted the interval critique by treating August 2026 as a two-reference-month horizon from the latest fetched June 2026 print and scaling month-to-month sigma by sqrt(2). Accepted the timestamp clarification by setting runAt after the model-candidate artifact time. The failed specs.json check did not affect target identity because the ledger-bound slug, unit, dataPointId, resolver URL, and resolution date were provided in the canonical target context."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-consideration: upside risk outside the interval would require unemployment to rise above 4.6 if July and August labour-force prints both weakened or participation rose faster than employment. Downside risk outside the interval would require a drop below 4.2 if employment growth reaccelerated while participation stopped adding unemployed persons."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Australia Labour Force first-print forecast","Framing: the registered target is ABS dataflow LF/M13.3.1599.20.AUS.M for August 2026, unemployment rate, persons, total age, seasonally adjusted, Australia, monthly percent, first print. The canonical ledger context binds slug australia-unemployment-rate-august-2026, unit percent, dataPointId abs.labour.unemployment_rate.2026_08.first_print, and the registered ABS Data API resolver."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-unemployment-rate-august-2026\nrunLabel: Headline\nresolutionDate: 2026-09-24\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-annual-rate-august-2026.2026-08-12T21-36-26Z.8c92e4560b695f7f","runId":"run.australia-cpi-annual-rate-august-2026.2026-08-12T21-36-26Z.8c92e4560b695f7f","predictionId":"australia-cpi-annual-rate-august-2026","specId":"spec.australia-cpi-annual-rate-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the 15 fetched monthly ABS annual-change prints from 2025-04 to 2026-06 have mean 3.42, sample std of values 0.772, range 1.9 to 4.6, and last print 3.8. The reference class is short because the registered complete monthly CPI API series only returned 15 observations.","Prior/update/interval: prior = last-print persistence from 2026-06 at 3.8 because its fetched walk-forward absolute-change proxy MAE 0.3571 is slightly better than the mean-change rule's 0.3714. Adjustment components: no direct August pre-release signal fetched, so update = 0.0 and point = 3.8. Successive changes are -0.3, -0.2, +1.1, +0.2, +0.4, +0.2, -0.4, +0.4, 0.0, -0.1, +0.9, -0.4, -0.2, -0.2; one-month sigma = 0.466, two-month sigma = sqrt(2)*0.466 = 0.659, and 80% half-width = 1.28*sigma = 1.28*0.659 = 0.844, rounded to 0.8. Implied bounds: 3.8 - 0.8 = 3.0 and 3.8 + 0.8 = 4.6."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Target identity is tied to the registered ledger slug australia-cpi-annual-rate-august-2026, unit percent, and dataPointId abs.cpi.all_groups.yoy.2026_08.first_print. The public specs.json check returned a 404 page during this run, so I used the local generated ledger target and target registration for slug identity rather than inventing a replacement.","Tool call: curl -sSL https://www.abs.gov.au/release-calendar/future-releases/202609 and extract Consumer Price Index entry"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Target identity is tied to the registered ledger slug australia-cpi-annual-rate-august-2026, unit percent, and dataPointId abs.cpi.all_groups.yoy.2026_08.first_print. The public specs.json check returned a 404 page during this run, so I used the local generated ledger target and target registration for slug identity rather than inventing a replacement.","Tool call: curl -sSL https://www.abs.gov.au/release-calendar/future-releases/202609 and extract Consumer Price Index entry"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.6, distribution present, forecast step count 1.","evidence":["Tool result: thesis_model_candidate_v1 benchmarks: persistence point=3.8, p10=3.0, p50=3.8, p90=4.6, 80_interval=[3.0,4.6], 90_interval=[2.7,4.9], interval_method=two-step residual sigma from 14 successive changes, calibration_n=14, train_cutoff=2026-06, walk_forward_MAE=0.3571; mean-change candidate point=4.0, interval=[3.2,4.8], calibration_n=14, train_cutoff=2026-06, in-sample MAE proxy=0.3714.","Prior/update/interval: prior = last-print persistence from 2026-06 at 3.8 because its fetched walk-forward absolute-change proxy MAE 0.3571 is slightly better than the mean-change rule's 0.3714. Adjustment components: no direct August pre-release signal fetched, so update = 0.0 and point = 3.8. Successive changes are -0.3, -0.2, +1.1, +0.2, +0.4, +0.2, -0.4, +0.4, 0.0, -0.1, +0.9, -0.4, -0.2, -0.2; one-month sigma = 0.466, two-month sigma = sqrt(2)*0.466 = 0.659, and 80% half-width = 1.28*sigma = 1.28*0.659 = 0.844, rounded to 0.8. Implied bounds: 3.8 - 0.8 = 3.0 and 3.8 + 0.8 = 4.6."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate/reference class: the 15 fetched monthly ABS annual-change prints from 2025-04 to 2026-06 have mean 3.42, sample std of values 0.772, range 1.9 to 4.6, and last print 3.8. The reference class is short because the registered complete monthly CPI API series only returned 15 observations.","Prior/update/interval: prior = last-print persistence from 2026-06 at 3.8 because its fetched walk-forward absolute-change proxy MAE 0.3571 is slightly better than the mean-change rule's 0.3714. Adjustment components: no direct August pre-release signal fetched, so update = 0.0 and point = 3.8. Successive changes are -0.3, -0.2, +1.1, +0.2, +0.4, +0.2, -0.4, +0.4, 0.0, -0.1, +0.9, -0.4, -0.2, -0.2; one-month sigma = 0.466, two-month sigma = sqrt(2)*0.466 = 0.659, and 80% half-width = 1.28*sigma = 1.28*0.659 = 0.844, rounded to 0.8. Implied bounds: 3.8 - 0.8 = 3.0 and 3.8 + 0.8 = 4.6."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Sanity check: with a 0.8-point half-width around persistence, 12 of the 14 one-step historical moves were inside the band; the two misses were +1.1 in 2025-07 and +0.9 in 2026-03. For a two-month August target this coverage check supports, but does not narrow, the interval.","Downside risk outside the interval: a faster disinflation sequence like another pair of -0.4 monthly changes would land below the interval. Upside risk outside the interval: a renewed price shock comparable to the +1.1 or +0.9 historical jumps would land above the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Australia August 2026 CPI annual-rate forecast","Target identity is tied to the registered ledger slug australia-cpi-annual-rate-august-2026, unit percent, and dataPointId abs.cpi.all_groups.yoy.2026_08.first_print. The public specs.json check returned a 404 page during this run, so I used the local generated ledger target and target registration for slug identity rather than inventing a replacement."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-annual-rate-august-2026\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.ssi-recipients-august-2026.2026-08-12T21-31-23Z.2d099a4c8a454544","runId":"run.ssi-recipients-august-2026.2026-08-12T21-31-23Z.2d099a4c8a454544","predictionId":"ssi-recipients-august-2026","specId":"spec.ssi-recipients-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 13 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the trailing 13 same-table first-print post-transform levels from July 2025 through July 2026 range from 7.300297 million to 7.436689 million, with mean level 7.367648 million. The latest-value persistence prior is 7.300297 million; recent successive changes have mean -0.007882 million, median -0.008843 million, and the 2026 sequence has fallen from 7.369510 million in January to 7.300297 million in July.","Prior/update/interval: prior is selected latest-value persistence at 7.300297 million using the fetched July 2025-July 2026 Table 2 post-transform sample. Adjustment components are -0.007882 million from the trailing mean monthly change, plus +0.010858 million from the fetched 2025 July-to-August same-month seasonal move, damped 25% because persistence won walk-forward MAE, giving final unrounded point 7.301041 million before display rounding to 7.300. Interval method is residual_changes_sigma on the 12 fetched successive monthly changes: sigma = 0.018722 million, so 80% half-width is 1.28*sigma = 1.28*0.018722 = 0.023964 million; 7.300297 - 0.023964 = 7.276333 and 7.300297 + 0.023964 = 7.324261, rounded to 7.276 to 7.324."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this targets SSA SSI Monthly Statistics Table 2, All Federally Administered Payments, the August 2026 row and Total number of recipients column, reported as an end-of-month administrative count and resolved on the first print. The target registry binds resolutionDate 2026-10-04 and resolutionSourceUrl to the July 2026 Table 2 URL; I preserve that bound URL while forecasting the registered August 2026 dataPointId.","Tool call: Inspected records/targets/2026-08-12-9e48da0da68cd2dfb368416d94e9714b1c294f8fcbee6ed27a1720e493ef0300.json and site/src/data/ledger-targets.generated.ts; attempted https://app.thesisinstitute.org/specs.json."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this targets SSA SSI Monthly Statistics Table 2, All Federally Administered Payments, the August 2026 row and Total number of recipients column, reported as an end-of-month administrative count and resolved on the first print. The target registry binds resolutionDate 2026-10-04 and resolutionSourceUrl to the July 2026 Table 2 URL; I preserve that bound URL while forecasting the registered August 2026 dataPointId.","Tool result: Fetched local public target fields: slug ssi-recipients-august-2026, unit millions, dataPointId ssa.ssi.total_recipients.2026-08.first_print, registered resolutionDate 2026-10-04, expectedReleaseWindow 2026-09-26 to 2026-10-04, sourceBinding transform operation multiply factor 0.001, and sourceBinding URL https://www.ssa.gov/policy/docs/statcomps/ssi_monthly/2026-07/table02.html; app specs fetch returned HTTP 404 during this run."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.05, distribution present, forecast step count 1.","evidence":["Tool result: thesis_model_candidate_v1 persistence: point 7.300297, p10 7.276333, p50 7.300297, p90 7.324261, 80% interval 7.276333-7.324261, 90% interval 7.269505-7.331089, interval_method residual_changes_sigma, calibration_n 12, train_cutoff 2026-07, walk_forward_mae 0.014003, walk_forward_rmse 0.018775. Expanding-drift candidate: point 7.292415, p10 7.268451, p50 7.292415, p90 7.316379, 80% interval 7.268451-7.316379, 90% interval 7.261622-7.323208, interval_method residual_changes_sigma, calibration_n 12, train_cutoff 2026-07, walk_forward_mae 0.014051, walk_forward_rmse 0.022720.","Prior/update/interval: prior is selected latest-value persistence at 7.300297 million using the fetched July 2025-July 2026 Table 2 post-transform sample. Adjustment components are -0.007882 million from the trailing mean monthly change, plus +0.010858 million from the fetched 2025 July-to-August same-month seasonal move, damped 25% because persistence won walk-forward MAE, giving final unrounded point 7.301041 million before display rounding to 7.300. Interval method is residual_changes_sigma on the 12 fetched successive monthly changes: sigma = 0.018722 million, so 80% half-width is 1.28*sigma = 1.28*0.018722 = 0.023964 million; 7.300297 - 0.023964 = 7.276333 and 7.300297 + 0.023964 = 7.324261, rounded to 7.276 to 7.324."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: Fetched official timing evidence: the current SSA SSI Monthly Statistics index is July 2026 and says released August 2026; it lists Table 2 as Number of recipients by type of payment, total payments, and average monthly payment; SSA Publishing Schedule lists SSI Monthly Statistics with frequency Monthly; the target bound remains 2026-10-04 because the registry provides a latest expected by-date rather than an exact official day.","Benchmark and update: persistence slightly beats the expanding-drift rule in this short walk-forward window, so it is the selected candidate. Current evidence pulls mildly downward because the January-July 2026 same-source decline is 0.069213 million, while the only directly fetched July-to-August seasonal comparison, 2025-07 to 2025-08, was +0.010858 million; those offset enough that the rounded August forecast stays at 7.300 million."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Benchmark and update: persistence slightly beats the expanding-drift rule in this short walk-forward window, so it is the selected candidate. Current evidence pulls mildly downward because the January-July 2026 same-source decline is 0.069213 million, while the only directly fetched July-to-August seasonal comparison, 2025-07 to 2025-08, was +0.010858 million; those offset enough that the rounded August forecast stays at 7.300 million.","Counter-consideration: upside risk outside the interval would require a rebound above 7.324 million, such as a July drop that fully reverses plus another positive August seasonal intake month like 2025. Downside risk outside the interval would require August to continue the January-July downtrend at more than about two recent-sigma monthly moves, landing below 7.276 million."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for SSA SSI total recipients, August 2026","Framing and exact resolver: this targets SSA SSI Monthly Statistics Table 2, All Federally Administered Payments, the August 2026 row and Total number of recipients column, reported as an end-of-month administrative count and resolved on the first print. The target registry binds resolutionDate 2026-10-04 and resolutionSourceUrl to the July 2026 Table 2 URL; I preserve that bound URL while forecasting the registered August 2026 dataPointId."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: ssi-recipients-august-2026\nrunLabel: Headline\nresolutionDate: 2026-10-04\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.euro-area-unemployment-rate-august-2026.2026-08-12T21-34-14Z.a21de549c4f6899d","runId":"run.euro-area-unemployment-rate-august-2026.2026-08-12T21-34-14Z.a21de549c4f6899d","predictionId":"euro-area-unemployment-rate-august-2026","specId":"spec.euro-area-unemployment-rate-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate / reference class: the last 24 official monthly values have mean 6.296, sample std of levels 0.046, range 6.2-6.4, and latest print 6.3. The 23 successive changes have mean -0.004 pp, range -0.1 to +0.1 pp, and 18 of 23 changes are exactly 0.0 pp, so last-print persistence is the strongest simple prior.","Prior/update/interval: prior is last-print persistence at 6.3 from the 2024-07 through 2026-06 official history. Adjustment components: momentum 0.0 pp because the latest four prints are 6.3 after a 6.4 in 2026-02, one-off/policy/current-signal adjustment 0.0 pp because no direct August-specific signal was fetched, weights 100% persistence prior and 0% inside-view adjustment. For the interval, successive changes have sigma = 0.047 pp, so the normal 80% half-width is 1.28*sigma = 0.061 pp; rounding to Eurostat's one-decimal publication precision gives a practical half-width of 0.1 pp and implied bounds 6.2 to 6.4."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Resolution target is Eurostat une_rt_m/M.SA.TOTAL.PC_ACT.T.EA21: monthly, seasonally adjusted, total age, percentage of the labour force, total sex, euro area 21 countries. The ledger expected release window is 2026-09-27 to 2026-10-05; the official Eurostat calendar fetch this run gives the August 2026 Unemployment event on 2026-10-01, so I keep the forecast tied to the registered target while using the ledger contractual outer date 2026-10-05 as resolutionDate.","Tool result: Official calendar JSON returned recordid 22494146, title Unemployment, period August 2026, start 2026-10-01T11:00Z, datasetCodes une_rt_m, euroind true, preliminary false."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Eurostat August 2026 unemployment first print","Resolution target is Eurostat une_rt_m/M.SA.TOTAL.PC_ACT.T.EA21: monthly, seasonally adjusted, total age, percentage of the labour force, total sex, euro area 21 countries. The ledger expected release window is 2026-09-27 to 2026-10-05; the official Eurostat calendar fetch this run gives the August 2026 Unemployment event on 2026-10-01, so I keep the forecast tied to the registered target while using the ledger contractual outer date 2026-10-05 as resolutionDate."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.2, distribution present, forecast step count 1.","evidence":["Model candidates under thesis_model_candidate_v1: persistence candidate point 6.3, p10 6.2, p50 6.3, p90 6.4, 80% interval [6.2, 6.4], 90% interval [6.2, 6.4], interval_method residual-change sigma rounded to published 0.1 pp, calibration_n 23, train_cutoff 2026-06, walk_forward_MAE 0.022 pp. A trailing-3-month-mean candidate also rounds to 6.3 but has walk_forward_MAE 0.030 pp, so persistence is selected.","Prior/update/interval: prior is last-print persistence at 6.3 from the 2024-07 through 2026-06 official history. Adjustment components: momentum 0.0 pp because the latest four prints are 6.3 after a 6.4 in 2026-02, one-off/policy/current-signal adjustment 0.0 pp because no direct August-specific signal was fetched, weights 100% persistence prior and 0% inside-view adjustment. For the interval, successive changes have sigma = 0.047 pp, so the normal 80% half-width is 1.28*sigma = 0.061 pp; rounding to Eurostat's one-decimal publication precision gives a practical half-width of 0.1 pp and implied bounds 6.2 to 6.4."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: prior is last-print persistence at 6.3 from the 2024-07 through 2026-06 official history. Adjustment components: momentum 0.0 pp because the latest four prints are 6.3 after a 6.4 in 2026-02, one-off/policy/current-signal adjustment 0.0 pp because no direct August-specific signal was fetched, weights 100% persistence prior and 0% inside-view adjustment. For the interval, successive changes have sigma = 0.047 pp, so the normal 80% half-width is 1.28*sigma = 0.061 pp; rounding to Eurostat's one-decimal publication precision gives a practical half-width of 0.1 pp and implied bounds 6.2 to 6.4."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool result: Slug check endpoint fetched this run but returned HTTP/2 404 with date Wed, 12 Aug 2026 21:25:20 GMT, so I used the canonical ledger slug euro-area-unemployment-rate-august-2026 rather than changing it.","Model candidates under thesis_model_candidate_v1: persistence candidate point 6.3, p10 6.2, p50 6.3, p90 6.4, 80% interval [6.2, 6.4], 90% interval [6.2, 6.4], interval_method residual-change sigma rounded to published 0.1 pp, calibration_n 23, train_cutoff 2026-06, walk_forward_MAE 0.022 pp. A trailing-3-month-mean candidate also rounds to 6.3 but has walk_forward_MAE 0.030 pp, so persistence is selected."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Resolution target is Eurostat une_rt_m/M.SA.TOTAL.PC_ACT.T.EA21: monthly, seasonally adjusted, total age, percentage of the labour force, total sex, euro area 21 countries. The ledger expected release window is 2026-09-27 to 2026-10-05; the official Eurostat calendar fetch this run gives the August 2026 Unemployment event on 2026-10-01, so I keep the forecast tied to the registered target while using the ledger contractual outer date 2026-10-05 as resolutionDate.","Tool result: Recent official endpoint values: 2026-02 6.4, 2026-03 6.3, 2026-04 6.3, 2026-05 6.3, 2026-06 6.3; labels confirm PC_ACT is percentage of population in the labour force and SA is seasonally adjusted."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: euro-area-unemployment-rate-august-2026\nrunLabel: Headline\nresolutionDate: 2026-10-05\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-ei-regular-beneficiaries-august-2026.2026-08-12T21-49-55Z.d31e0bba1d00da7a","runId":"run.canada-ei-regular-beneficiaries-august-2026.2026-08-12T21-49-55Z.d31e0bba1d00da7a","predictionId":"canada-ei-regular-beneficiaries-august-2026","specId":"spec.canada-ei-regular-beneficiaries-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the last 24 official WDS values for the exact vector averaged 525.89 thousand, ranged from 479.80 to 568.72 thousand, and the last print was 543.69 thousand for May 2026. For this repeated level series, last-print persistence at 543.69 thousand is the default prior, with recent monthly changes rather than level dispersion used for the interval.","Prior/update/interval: prior = last-print persistence 543.69 thousand from May 2026; historical sample = latest 12 successive WDS monthly changes +19.70, +7.39, +0.18, -1.00, +7.21, +7.24, -1.10, -8.60, -8.67, +0.07, -6.46, -0.27 thousand. Adjustment components = -6.00 thousand for current LFS evidence that unemployment fell to 6.4% in July and was down 0.5 points since April, smaller than the six-month drift because EI rolls lag labour-market conditions and recent negative EI prints may already reflect part of the labour improvement. Point = 543.69 - 6.00 = 537.69 thousand. For the three-unpublished-month horizon, sigma = 8.09 thousand from the latest 12 monthly changes; 80% half-width = 1.28*sigma*sqrt(3) = 1.28*8.09*1.732 = 17.93 thousand, giving 537.69 - 17.93 = 519.76 and 537.69 + 17.93 = 555.62."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The resolver is Statistics Canada Table 14-10-0011-01, vector v64549350: Canada regular Employment Insurance beneficiaries, seasonally adjusted, first print for August 2026, transformed from persons to thousands by multiplying by 0.001. The registered target supplies slug, unit, dataPointId, sourceBinding, expected window ending 2026-10-21, and first-print policy.","Tool result: Fetched official WDS vector v64549350 values in thousands: 2024-06 479.80, 2024-07 489.32, 2024-08 494.67, 2024-09 486.84, 2024-10 489.08, 2024-11 487.51, 2024-12 487.64, 2025-01 489.06, 2025-02 501.49, 2025-03 504.11, 2025-04 526.28, 2025-05 528.00, 2025-06 547.70, 2025-07 555.09, 2025-08 555.27, 2025-09 554.27, 2025-10 561.48, 2025-11 568.72, 2025-12 567.62, 2026-01 559.02, 2026-02 550.35, 2026-03 550.42, 2026-04 543.96, 2026-05 543.69; latest releaseTime entries include 2026-07-23T08:30 for March, April, and May 2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is Statistics Canada Table 14-10-0011-01, vector v64549350: Canada regular Employment Insurance beneficiaries, seasonally adjusted, first print for August 2026, transformed from persons to thousands by multiplying by 0.001. The registered target supplies slug, unit, dataPointId, sourceBinding, expected window ending 2026-10-21, and first-print policy.","Tool result: Fetched official WDS vector v64549350 values in thousands: 2024-06 479.80, 2024-07 489.32, 2024-08 494.67, 2024-09 486.84, 2024-10 489.08, 2024-11 487.51, 2024-12 487.64, 2025-01 489.06, 2025-02 501.49, 2025-03 504.11, 2025-04 526.28, 2025-05 528.00, 2025-06 547.70, 2025-07 555.09, 2025-08 555.27, 2025-09 554.27, 2025-10 561.48, 2025-11 568.72, 2025-12 567.62, 2026-01 559.02, 2026-02 550.35, 2026-03 550.42, 2026-04 543.96, 2026-05 543.69; latest releaseTime entries include 2026-07-23T08:30 for March, April, and May 2026."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 35.86, distribution present, forecast step count 1.","evidence":["Base rate/reference class: the last 24 official WDS values for the exact vector averaged 525.89 thousand, ranged from 479.80 to 568.72 thousand, and the last print was 543.69 thousand for May 2026. For this repeated level series, last-print persistence at 543.69 thousand is the default prior, with recent monthly changes rather than level dispersion used for the interval.","Model candidates under thesis_model_candidate_v1: persistence candidate has point 543.69, p10 525.76, p50 543.69, p90 561.62, 80% interval [525.76, 561.62], 90% interval [520.64, 566.74], interval method residual monthly-change sigma over the latest 12 changes scaled by sqrt(3), calibration_n 12, train cutoff 2026-05. A six-month drift candidate would point lower near 531.18, but it overweights the January-May downshift relative to the 12- and 24-month history and lacks direct EI data for June-August."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: prior = last-print persistence 543.69 thousand from May 2026; historical sample = latest 12 successive WDS monthly changes +19.70, +7.39, +0.18, -1.00, +7.21, +7.24, -1.10, -8.60, -8.67, +0.07, -6.46, -0.27 thousand. Adjustment components = -6.00 thousand for current LFS evidence that unemployment fell to 6.4% in July and was down 0.5 points since April, smaller than the six-month drift because EI rolls lag labour-market conditions and recent negative EI prints may already reflect part of the labour improvement. Point = 543.69 - 6.00 = 537.69 thousand. For the three-unpublished-month horizon, sigma = 8.09 thousand from the latest 12 monthly changes; 80% half-width = 1.28*sigma*sqrt(3) = 1.28*8.09*1.732 = 17.93 thousand, giving 537.69 - 17.93 = 519.76 and 537.69 + 17.93 = 555.62."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Model candidates under thesis_model_candidate_v1: persistence candidate has point 543.69, p10 525.76, p50 543.69, p90 561.62, 80% interval [525.76, 561.62], 90% interval [520.64, 566.74], interval method residual monthly-change sigma over the latest 12 changes scaled by sqrt(3), calibration_n 12, train cutoff 2026-05. A six-month drift candidate would point lower near 531.18, but it overweights the January-May downshift relative to the 12- and 24-month history and lacks direct EI data for June-August.","Counter-consideration: downside risk outside the interval would be continued job-finding gains and falling unemployment causing June-August EI rolls to fall below 519.76 thousand. Upside risk outside the interval would be renewed layoffs, tariff-sensitive sector weakness, or an EI processing/backlog jump pushing the August first print above 555.62 thousand."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast Canada regular Employment Insurance beneficiaries for August 2026","The resolver is Statistics Canada Table 14-10-0011-01, vector v64549350: Canada regular Employment Insurance beneficiaries, seasonally adjusted, first print for August 2026, transformed from persons to thousands by multiplying by 0.001. The registered target supplies slug, unit, dataPointId, sourceBinding, expected window ending 2026-10-21, and first-print policy."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-ei-regular-beneficiaries-august-2026\nrunLabel: Headline\nresolutionDate: 2026-10-21\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-monthly-gdp-growth-august-2026.2026-08-12T21-42-46Z.1596f07c414b7ec6","runId":"run.canada-monthly-gdp-growth-august-2026.2026-08-12T21-42-46Z.1596f07c414b7ec6","predictionId":"canada-monthly-gdp-growth-august-2026","specId":"spec.canada-monthly-gdp-growth-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool call: Compute thesis_model_candidate_v1 baseline candidates from the 23 WDS-derived monthly changes","Base rate / reference class: the 23 recent comparable month-over-month changes computed from the fetched WDS levels have mean 0.128%, median 0.130%, sigma 0.258%, p10 -0.178%, p90 0.520%, and range -0.258% to 0.646%. The rolling-12 mean benchmark point is 0.139%, and it outperformed last-change persistence in walk-forward MAE."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The registered target is StatCan vector v65201210 in Table 36-10-0434-01, all industries, chained 2017 dollars, seasonally adjusted at annual rates. The forecasted value is the first-print August 2026 month-over-month percent change computed from the July and August release-vintage levels. The local public ledger target confirms slug canada-monthly-gdp-growth-august-2026, unit percent_growth, dataPointId statcan.gdp_by_industry.monthly_growth.2026_08.first_print, and resolutionDate 2026-10-30. The app specs endpoint returned a Next.js error page rather than JSON in this run, so app-side slug confirmation was not available.","Tool call: curl -sS 'https://www150.statcan.gc.ca/n1/dai-quo/ssi/homepage/schedule-key_indicators-eng.json' | sed -n '19578,19586p'"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The registered target is StatCan vector v65201210 in Table 36-10-0434-01, all industries, chained 2017 dollars, seasonally adjusted at annual rates. The forecasted value is the first-print August 2026 month-over-month percent change computed from the July and August release-vintage levels. The local public ledger target confirms slug canada-monthly-gdp-growth-august-2026, unit percent_growth, dataPointId statcan.gdp_by_industry.monthly_growth.2026_08.first_print, and resolutionDate 2026-10-30. The app specs endpoint returned a Next.js error page rather than JSON in this run, so app-side slug confirmation was not available.","Point estimate: select the rolling-12 mean benchmark rather than raw last-print persistence because walk-forward MAE was lower, then update modestly toward the official June advance estimate. Computation: 0.75*0.139 + 0.25*0.200 = 0.154, which rounds to 0.2% at one-decimal published precision."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.8, distribution present, forecast step count 1.","evidence":["Tool result: Persistence candidate: point=0.340, p10=-0.18, p50=0.13, p90=0.52, 80%=[-0.18,0.52], 90%=[-0.24,0.61], interval_method=empirical_recent_changes, calibration_n=23, train_cutoff=2026-05, walk_forward_mae=0.340, walk_forward_rmse=0.399. Rolling-12-mean candidate: point=0.139, p10=-0.18, p50=0.13, p90=0.52, 80%=[-0.18,0.52], 90%=[-0.24,0.61], interval_method=empirical_recent_changes, calibration_n=23, train_cutoff=2026-05, walk_forward_mae=0.222, walk_forward_rmse=0.276.","Prior/update/interval: prior=rolling-12 mean model candidate from 23 WDS-derived monthly changes, historical sample=2024-07 through 2026-05 computed changes, adjustment components=0.75 weight on the 0.139% rolling-12 mean and 0.25 weight on the official 0.200% June advance estimate, interval method=realized dispersion widened for a three-month-ahead August target with only May WDS level history and June advance information. For the fetched monthly growth values, sigma = 0.258; 1.28*sigma = 0.330. Widen to 0.4 percentage point half-width for horizon uncertainty: point 0.2 minus/plus 0.4 gives implied bounds [-0.2, 0.6]. This would have covered 9 of the last 10 fetched monthly growth values after rounding."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Point estimate: select the rolling-12 mean benchmark rather than raw last-print persistence because walk-forward MAE was lower, then update modestly toward the official June advance estimate. Computation: 0.75*0.139 + 0.25*0.200 = 0.154, which rounds to 0.2% at one-decimal published precision."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool result: Monthly percent changes from fetched WDS levels: 2026-01=-0.045%, 2026-02=0.192%, 2026-03=-0.155%, 2026-04=0.582%, 2026-05=0.340%; full 23-change distribution mean=0.128, sigma_values=0.258, p10=-0.178, p50=0.130, p90=0.520, min=-0.258, max=0.646.","Prior/update/interval: prior=rolling-12 mean model candidate from 23 WDS-derived monthly changes, historical sample=2024-07 through 2026-05 computed changes, adjustment components=0.75 weight on the 0.139% rolling-12 mean and 0.25 weight on the official 0.200% June advance estimate, interval method=realized dispersion widened for a three-month-ahead August target with only May WDS level history and June advance information. For the fetched monthly growth values, sigma = 0.258; 1.28*sigma = 0.330. Widen to 0.4 percentage point half-width for horizon uncertainty: point 0.2 minus/plus 0.4 gives implied bounds [-0.2, 0.6]. This would have covered 9 of the last 10 fetched monthly growth values after rounding."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The registered target is StatCan vector v65201210 in Table 36-10-0434-01, all industries, chained 2017 dollars, seasonally adjusted at annual rates. The forecasted value is the first-print August 2026 month-over-month percent change computed from the July and August release-vintage levels. The local public ledger target confirms slug canada-monthly-gdp-growth-august-2026, unit percent_growth, dataPointId statcan.gdp_by_industry.monthly_growth.2026_08.first_print, and resolutionDate 2026-10-30. The app specs endpoint returned a Next.js error page rather than JSON in this run, so app-side slug confirmation was not available.","Tool result: Persistence candidate: point=0.340, p10=-0.18, p50=0.13, p90=0.52, 80%=[-0.18,0.52], 90%=[-0.24,0.61], interval_method=empirical_recent_changes, calibration_n=23, train_cutoff=2026-05, walk_forward_mae=0.340, walk_forward_rmse=0.399. Rolling-12-mean candidate: point=0.139, p10=-0.18, p50=0.13, p90=0.52, 80%=[-0.18,0.52], 90%=[-0.24,0.61], interval_method=empirical_recent_changes, calibration_n=23, train_cutoff=2026-05, walk_forward_mae=0.222, walk_forward_rmse=0.276."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-monthly-gdp-growth-august-2026\nrunLabel: Headline\nresolutionDate: 2026-10-30\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-cdfi-assistance-transaction-obligations-fy2026.2026-08-12T20-54-08Z.74eca2fc7028988f","runId":"run.us-cdfi-assistance-transaction-obligations-fy2026.2026-08-12T20-54-08Z.74eca2fc7028988f","predictionId":"us-cdfi-assistance-transaction-obligations-fy2026","specId":"spec.us-cdfi-assistance-transaction-obligations-fy2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 13 historical point(s) and explicit outside-view language.","evidence":["Tool result: Fetched YTD aggregated_amount values: FY2020 317595484.72, FY2021 1424316989.44, FY2022 538207569.27, FY2023 1929177053.00, FY2024 337850749.00, FY2025 311407219.00, FY2026 -7003322.92; historical late additions from Aug 12 to fiscal-year close were 226.745664, 33.269989, 38.830759, 56.888134, 444.191804, and 8.047957 usd_millions.","Base rate/reference class: the last six completed same-query FY prints, FY2020-FY2025, were 544.3, 1457.6, 577.0, 1986.1, 782.0, and 319.5 usd_millions; mean 944.4, median 679.5, sigma 641.9, range 319.5-1986.1. The broader FY2014-FY2025 reference class has mean 596.8, median 420.4, sigma 575.7, and range 3.5-1986.1. Last-print persistence, FY2025 = 319.5, is the default prior because the series is a repeated annual flow and simple year-to-year movements are very noisy."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 6 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The target is not an agency profile total or a press-release headline. It is the registered USAspending POST query for CDFI Fund awarding-subagency financial-assistance award transactions, grouped by fiscal_year, with signed aggregated_amount scaled to usd_millions. The registered expectedReleaseWindow is 2026-10-15 through 2026-10-22, so I use the ledger outer bound 2026-10-22 as the resolutionDate.","Tool result: Fetched aggregated_amount values: FY2014 217237896.00, FY2015 232190329.00, FY2016 3525000.00, FY2017 498977799.00; scaled values are 217.237896, 232.190329, 3.525000, 498.977799 usd_millions."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is not an agency profile total or a press-release headline. It is the registered USAspending POST query for CDFI Fund awarding-subagency financial-assistance award transactions, grouped by fiscal_year, with signed aggregated_amount scaled to usd_millions. The registered expectedReleaseWindow is 2026-10-15 through 2026-10-22, so I use the ledger outer bound 2026-10-22 as the resolutionDate.","Tool result: Fetched target registration: schemaVersion thesis_target_registration_v3, registeredAtUtc 2026-08-11T20:38:09Z, slug us-cdfi-assistance-transaction-obligations-fy2026, unit usd_millions, expectedReleaseWindow end 2026-10-22. The public specs.json check returned a 404 page, so I did not find contrary published slug evidence there."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1643.4, distribution present, forecast step count 1.","evidence":["Tool result: Candidate last_print_persistence: point 319.455, p10 -502.210, p50 319.455, p90 1141.120, 80% interval [-502.210, 1141.120], 90% interval [-736.513, 1375.423], calibration_n 6, trainCutoff FY2025, walk-forward FY2015-FY2025 MAE 568.084 and RMSE 721.007. Candidate six_year_mean: point 944.422, p10 122.756, p50 944.422, p90 1766.087, 80% interval [122.756, 1766.087], calibration_n 6.","Prior/update/interval: Prior is last-print persistence at 319.455176 usd_millions. Current same-query FY2026 YTD is -7.00332292; historical FY2020-FY2025 late additions after Aug 12 averaged 134.6623845, giving a YTD-plus-average-late signal of 127.65906158. Weight the prior 80% and the current timing signal 20% because the direct FY2026 value is informative but CDFI award booking is historically lumpy: point = 0.80*319.455176 + 0.20*127.65906158 = 281.095953116, rounded to 281.1. For the interval, use the last six completed full-year values themselves because this is a flow series: sigma = 641.925991 usd_millions, so 1.28*sigma = 821.665269. The 80% interval is 281.1 +/- 821.7 = [-540.6, 1102.8]. This interval would cover 8 of the last 10 completed FY prints; the misses are the unusually large FY2021 and FY2023 prints."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate/reference class: the last six completed same-query FY prints, FY2020-FY2025, were 544.3, 1457.6, 577.0, 1986.1, 782.0, and 319.5 usd_millions; mean 944.4, median 679.5, sigma 641.9, range 319.5-1986.1. The broader FY2014-FY2025 reference class has mean 596.8, median 420.4, sigma 575.7, and range 3.5-1986.1. Last-print persistence, FY2025 = 319.5, is the default prior because the series is a repeated annual flow and simple year-to-year movements are very noisy.","Prior/update/interval: Prior is last-print persistence at 319.455176 usd_millions. Current same-query FY2026 YTD is -7.00332292; historical FY2020-FY2025 late additions after Aug 12 averaged 134.6623845, giving a YTD-plus-average-late signal of 127.65906158. Weight the prior 80% and the current timing signal 20% because the direct FY2026 value is informative but CDFI award booking is historically lumpy: point = 0.80*319.455176 + 0.20*127.65906158 = 281.095953116, rounded to 281.1. For the interval, use the last six completed full-year values themselves because this is a flow series: sigma = 641.925991 usd_millions, so 1.28*sigma = 821.665269. The 80% interval is 281.1 +/- 821.7 = [-540.6, 1102.8]. This interval would cover 8 of the last 10 completed FY prints; the misses are the unusually large FY2021 and FY2023 prints."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: Prior is last-print persistence at 319.455176 usd_millions. Current same-query FY2026 YTD is -7.00332292; historical FY2020-FY2025 late additions after Aug 12 averaged 134.6623845, giving a YTD-plus-average-late signal of 127.65906158. Weight the prior 80% and the current timing signal 20% because the direct FY2026 value is informative but CDFI award booking is historically lumpy: point = 0.80*319.455176 + 0.20*127.65906158 = 281.095953116, rounded to 281.1. For the interval, use the last six completed full-year values themselves because this is a flow series: sigma = 641.925991 usd_millions, so 1.28*sigma = 821.665269. The 80% interval is 281.1 +/- 821.7 = [-540.6, 1102.8]. This interval would cover 8 of the last 10 completed FY prints; the misses are the unusually large FY2021 and FY2023 prints.","Counter-consideration: upside risk outside the interval would come from a large late FY2026 award round or data catch-up similar to the FY2021/FY2023 high-obligation years. Downside risk outside the interval would require net deobligations materially beyond the current -7.0 million YTD value, because the signed federal_action_obligation field can include negative adjustments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Candidate last_print_persistence: point 319.455, p10 -502.210, p50 319.455, p90 1141.120, 80% interval [-502.210, 1141.120], 90% interval [-736.513, 1375.423], calibration_n 6, trainCutoff FY2025, walk-forward FY2015-FY2025 MAE 568.084 and RMSE 721.007. Candidate six_year_mean: point 944.422, p10 122.756, p50 944.422, p90 1766.087, 80% interval [122.756, 1766.087], calibration_n 6.","Prior/update/interval: Prior is last-print persistence at 319.455176 usd_millions. Current same-query FY2026 YTD is -7.00332292; historical FY2020-FY2025 late additions after Aug 12 averaged 134.6623845, giving a YTD-plus-average-late signal of 127.65906158. Weight the prior 80% and the current timing signal 20% because the direct FY2026 value is informative but CDFI award booking is historically lumpy: point = 0.80*319.455176 + 0.20*127.65906158 = 281.095953116, rounded to 281.1. For the interval, use the last six completed full-year values themselves because this is a flow series: sigma = 641.925991 usd_millions, so 1.28*sigma = 821.665269. The 80% interval is 281.1 +/- 821.7 = [-540.6, 1102.8]. This interval would cover 8 of the last 10 completed FY prints; the misses are the unusually large FY2021 and FY2023 prints."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-cdfi-assistance-transaction-obligations-fy2026\nrunLabel: Headline\nresolutionDate: 2026-10-22\ntraceLineCount: 19\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-ondcp-hidta-al95001-obligations-fy2026.2026-08-12T20-57-24Z.6697348e47132af0","runId":"run.us-ondcp-hidta-al95001-obligations-fy2026.2026-08-12T20-57-24Z.6697348e47132af0","predictionId":"us-ondcp-hidta-al95001-obligations-fy2026","specId":"spec.us-ondcp-hidta-al95001-obligations-fy2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 7 historical point(s) and explicit outside-view language.","evidence":["Base rate / reference class: the last 7 completed fiscal-year registered-query values were 284.14514631, 270.27144368, 268.60530517, 252.76050027, 266.41544691, 273.95994611, and 271.6576756 usd_millions. Their mean was 269.687923, median 270.271444, range 252.760500-284.145146, and the strongest simple benchmark is last-print persistence at FY2025 = 271.6576756 usd_millions.","Prior/update/interval: prior = persistence.last_print candidate from FY2019-FY2025 completed registered-query history, point 271.657676. Adjustment components: 0.000000 for current FY2026 live-query value because 0.26298451 usd_millions is an in-year continuous USAspending value before the registered snapshot window and not a comparable final fiscal-year snapshot; no other direct current signal was fetched. For interval sizing on this annual flow series, sample sigma = 9.397701 from the 7 completed fetched values; 1.28*sigma = 12.029057. I widen the half-width by 1.20x to 14.434868 because USAspending registered_query_snapshot outcomes can move with late-posted/revised transactions between the live query and the October capture window; this is deliberately wider than the residual-quantile candidate's p10-p90 interval upper bound of 282.257399. Final 80% interval = 271.657676 +/- 14.434868 = [257.222807, 286.092545]. This interval would contain 6 of the 7 completed FY2019-FY2025 registered-query values."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Resolution framing: the target is the USAspending API v2 spending_over_time registered query for Assistance Listing 95.001 prime financial-assistance award transactions, fiscal-year grouped, first archived registered-query snapshot for FY2026. The target registration supplies expectedReleaseWindow 2026-10-15 to 2026-10-22, so I use the lab-committed outer bound 2026-10-22 rather than inferring a release day from cadence.","Tool result: Target registration parsed with catalogSlug us-ondcp-hidta-al95001-obligations-fy2026, targetContentHash eb895fc1e680eab66d27b1046b6df148fa4c00829fc42935f4c36fb1c8a4a42a, expectedReleaseWindow.end 2026-10-22, sourceUrl https://api.usaspending.gov/api/v2/search/spending_over_time/. Fetched specs.json size was 11289 bytes; rg found 0 occurrences of us-ondcp-hidta-al95001-obligations-fy2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Resolution framing: the target is the USAspending API v2 spending_over_time registered query for Assistance Listing 95.001 prime financial-assistance award transactions, fiscal-year grouped, first archived registered-query snapshot for FY2026. The target registration supplies expectedReleaseWindow 2026-10-15 to 2026-10-22, so I use the lab-committed outer bound 2026-10-22 rather than inferring a release day from cadence.","Tool result: Target registration parsed with catalogSlug us-ondcp-hidta-al95001-obligations-fy2026, targetContentHash eb895fc1e680eab66d27b1046b6df148fa4c00829fc42935f4c36fb1c8a4a42a, expectedReleaseWindow.end 2026-10-22, sourceUrl https://api.usaspending.gov/api/v2/search/spending_over_time/. Fetched specs.json size was 11289 bytes; rg found 0 occurrences of us-ondcp-hidta-al95001-obligations-fy2026."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 28.87, distribution present, forecast step count 1.","evidence":["Tool result: thesis_model_candidate_v1 persistence.last_print generatedAt 2026-08-12T20:55:30Z: pointEstimate 271.657676, p10 256.798422, p50 271.657676, p90 282.257399, interval80 lower 256.798422 upper 282.257399, interval90 lower 256.305646 upper 283.78501, intervalMethod residual_quantile, calibrationN 6, walk_forward_1_step meanAbsoluteError 9.147727064999989.","Prior/update/interval: prior = persistence.last_print candidate from FY2019-FY2025 completed registered-query history, point 271.657676. Adjustment components: 0.000000 for current FY2026 live-query value because 0.26298451 usd_millions is an in-year continuous USAspending value before the registered snapshot window and not a comparable final fiscal-year snapshot; no other direct current signal was fetched. For interval sizing on this annual flow series, sample sigma = 9.397701 from the 7 completed fetched values; 1.28*sigma = 12.029057. I widen the half-width by 1.20x to 14.434868 because USAspending registered_query_snapshot outcomes can move with late-posted/revised transactions between the live query and the October capture window; this is deliberately wider than the residual-quantile candidate's p10-p90 interval upper bound of 282.257399. Final 80% interval = 271.657676 +/- 14.434868 = [257.222807, 286.092545]. This interval would contain 6 of the 7 completed FY2019-FY2025 registered-query values."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: prior = persistence.last_print candidate from FY2019-FY2025 completed registered-query history, point 271.657676. Adjustment components: 0.000000 for current FY2026 live-query value because 0.26298451 usd_millions is an in-year continuous USAspending value before the registered snapshot window and not a comparable final fiscal-year snapshot; no other direct current signal was fetched. For interval sizing on this annual flow series, sample sigma = 9.397701 from the 7 completed fetched values; 1.28*sigma = 12.029057. I widen the half-width by 1.20x to 14.434868 because USAspending registered_query_snapshot outcomes can move with late-posted/revised transactions between the live query and the October capture window; this is deliberately wider than the residual-quantile candidate's p10-p90 interval upper bound of 282.257399. Final 80% interval = 271.657676 +/- 14.434868 = [257.222807, 286.092545]. This interval would contain 6 of the 7 completed FY2019-FY2025 registered-query values."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-consideration: upside risk outside the interval would be a late FY2026 bulk HIDTA grant obligation or cleanup transaction that pushes the AL 95.001 fiscal-year aggregate above about 286.1 usd_millions. Downside risk outside the interval would land below the interval if FY2026 awards remain unusually delayed, reclassified, or deobligated so that the October registered snapshot stays below about 257.2 usd_millions."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["FY2026 HIDTA AL 95.001 registered-query forecast","Tool result: thesis_model_candidate_v1 persistence.last_print generatedAt 2026-08-12T20:55:30Z: pointEstimate 271.657676, p10 256.798422, p50 271.657676, p90 282.257399, interval80 lower 256.798422 upper 282.257399, interval90 lower 256.305646 upper 283.78501, intervalMethod residual_quantile, calibrationN 6, walk_forward_1_step meanAbsoluteError 9.147727064999989."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-ondcp-hidta-al95001-obligations-fy2026\nrunLabel: Headline\nresolutionDate: 2026-10-22\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-usfs-minnesota-place-of-performance-obligations-fy2026.2026-08-12T21-00-42Z.77172e1d99935d08","runId":"run.us-usfs-minnesota-place-of-performance-obligations-fy2026.2026-08-12T21-00-42Z.77172e1d99935d08","predictionId":"us-usfs-minnesota-place-of-performance-obligations-fy2026","specId":"spec.us-usfs-minnesota-place-of-performance-obligations-fy2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the last five completed same-query fiscal-year totals are 38.291, 34.096, 49.959, 68.718, and 46.833 usd_millions; mean 47.579, median 46.833, range 34.096-68.718. The default repeated-series prior is FY2025 persistence at 46.833 usd_millions; persistence walk-forward absolute errors over FY2022-FY2025 are 4.195, 15.863, 18.759, and 21.885 million, MAE 15.176.","Model candidates (thesis_model_candidate_v1): persistence point 46.833, p10 29.646, p50 46.833, p90 64.019, 80% interval [29.646, 64.019], 90% interval [24.745, 68.920], interval_method annual-value sigma, calibration_n 5, train_cutoff FY2025, walk_forward_mae 15.176; historical-mean candidate point 47.579, p10 30.393, p50 47.579, p90 64.766, 80% interval [30.393, 64.766], 90% interval [25.491, 69.667], interval_method annual-value sigma, calibration_n 5, train_cutoff FY2025; Aug12-catchup candidate point 29.498 = current partial 18.026 + median prior Aug12-to-final catch-up 11.472, p10 12.311, p50 29.498, p90 46.684, 80% interval [12.311, 46.684], 90% interval [7.410, 51.586], interval_method annual-value sigma wrapped around current partial catch-up, calibration_n 5, train_cutoff 2026-08-12."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["USFS Minnesota place-of-performance obligations, FY2026","Framing: the target is the registered USAspending advanced-search query, not an agency profile total or a news summary. It resolves on the first registered-query snapshot for FY2026 prime award transactions with Forest Service as awarding subtier and Minnesota as place of performance, converted from dollars to usd_millions."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing: the target is the registered USAspending advanced-search query, not an agency profile total or a news summary. It resolves on the first registered-query snapshot for FY2026 prime award transactions with Forest Service as awarding subtier and Minnesota as place of performance, converted from dollars to usd_millions.","Tool result: Registered slug us-usfs-minnesota-place-of-performance-obligations-fy2026; unit usd_millions; dataPointId usaspending.usfs.minnesota_place_of_performance_obligations.fy2026.registered_query_snapshot; expectedReleaseWindow start 2026-10-15 end 2026-10-22; sourceBinding factor 0.000001; FY2025 anchor 46.83255679 usd_millions in docket_series."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 34.4, distribution present, forecast step count 1.","evidence":["Model candidates (thesis_model_candidate_v1): persistence point 46.833, p10 29.646, p50 46.833, p90 64.019, 80% interval [29.646, 64.019], 90% interval [24.745, 68.920], interval_method annual-value sigma, calibration_n 5, train_cutoff FY2025, walk_forward_mae 15.176; historical-mean candidate point 47.579, p10 30.393, p50 47.579, p90 64.766, 80% interval [30.393, 64.766], 90% interval [25.491, 69.667], interval_method annual-value sigma, calibration_n 5, train_cutoff FY2025; Aug12-catchup candidate point 29.498 = current partial 18.026 + median prior Aug12-to-final catch-up 11.472, p10 12.311, p50 29.498, p90 46.684, 80% interval [12.311, 46.684], 90% interval [7.410, 51.586], interval_method annual-value sigma wrapped around current partial catch-up, calibration_n 5, train_cutoff 2026-08-12.","Prior/update/interval: prior is FY2025 persistence 46.833 from the FY2021-FY2025 completed full-year registered-query sample. Current update is direct same-query FY2026 partial evidence, not part of the completed historical calibration sample: 18.026 by 2026-08-12 versus prior Aug. 12 partials 20.470-60.039 and median historical catch-up 11.472, giving selected point 18.026 + 11.472 = 29.498, rounded to 29.5. Historical sample for interval is FY2021-FY2025 full-year values themselves because this is an annual flow: sigma = 13.427 usd_millions, half-width = 1.28*sigma = 17.186; selected 80% interval = 29.498 +/- 17.186 = [12.311, 46.684], rounded to [12.3, 46.7]. This is a material move below persistence, justified by the direct FY2026 same-query partial and shrunk upward relative to the pure partial-ratio point of 23.874."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: prior is FY2025 persistence 46.833 from the FY2021-FY2025 completed full-year registered-query sample. Current update is direct same-query FY2026 partial evidence, not part of the completed historical calibration sample: 18.026 by 2026-08-12 versus prior Aug. 12 partials 20.470-60.039 and median historical catch-up 11.472, giving selected point 18.026 + 11.472 = 29.498, rounded to 29.5. Historical sample for interval is FY2021-FY2025 full-year values themselves because this is an annual flow: sigma = 13.427 usd_millions, half-width = 1.28*sigma = 17.186; selected 80% interval = 29.498 +/- 17.186 = [12.311, 46.684], rounded to [12.3, 46.7]. This is a material move below persistence, justified by the direct FY2026 same-query partial and shrunk upward relative to the pure partial-ratio point of 23.874."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool result: Fetched full-year rows: FY2021 aggregated_amount 38291078.07 USD = 38.29107807 usd_millions; FY2022 34095876.20 USD = 34.09587620; FY2023 49958929.09 USD = 49.95892909; FY2024 68717828.09 USD = 68.71782809; FY2025 46832556.79 USD = 46.83255679; FY2026 current same-query row as of run 18026012.00 USD = 18.02601200 but FY2026 is not closed.","Counter-consideration: upside risk outside the interval would come from a large late September obligation batch like FY2023's 20.776 million catch-up plus additional delayed postings that push the registered snapshot above 46.7. Downside risk outside the interval would require unusually little remaining FY2026 Forest Service Minnesota award activity or negative deobligations after 2026-08-12, leaving the registered snapshot below 12.3."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Registered slug us-usfs-minnesota-place-of-performance-obligations-fy2026; unit usd_millions; dataPointId usaspending.usfs.minnesota_place_of_performance_obligations.fy2026.registered_query_snapshot; expectedReleaseWindow start 2026-10-15 end 2026-10-22; sourceBinding factor 0.000001; FY2025 anchor 46.83255679 usd_millions in docket_series.","Model candidates (thesis_model_candidate_v1): persistence point 46.833, p10 29.646, p50 46.833, p90 64.019, 80% interval [29.646, 64.019], 90% interval [24.745, 68.920], interval_method annual-value sigma, calibration_n 5, train_cutoff FY2025, walk_forward_mae 15.176; historical-mean candidate point 47.579, p10 30.393, p50 47.579, p90 64.766, 80% interval [30.393, 64.766], 90% interval [25.491, 69.667], interval_method annual-value sigma, calibration_n 5, train_cutoff FY2025; Aug12-catchup candidate point 29.498 = current partial 18.026 + median prior Aug12-to-final catch-up 11.472, p10 12.311, p50 29.498, p90 46.684, 80% interval [12.311, 46.684], 90% interval [7.410, 51.586], interval_method annual-value sigma wrapped around current partial catch-up, calibration_n 5, train_cutoff 2026-08-12."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-usfs-minnesota-place-of-performance-obligations-fy2026\nrunLabel: Headline\nresolutionDate: 2026-10-22\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.uk-total-trade-balance-june-2026.2026-08-12T16-08-23Z.91791a1a962db0fc","runId":"run.uk-total-trade-balance-june-2026.2026-08-12T16-08-23Z.91791a1a962db0fc","predictionId":"uk-total-trade-balance-june-2026","specId":"spec.uk-total-trade-balance-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Framing and exact resolver: this forecast targets ONS MRET series IKBJ, Total Trade (TT): WW: Balance: BOP: CP: SA, for 2026 JUN, first print. The source page reports units of £m, so the ledger transform is multiply by 0.001 into gbp_billions. Historical anchors below use the same IKBJ current-price seasonally adjusted total trade balance variant.","Tool call: Fetched recent same-month and prior-year IKBJ observations for reference-class context."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this forecast targets ONS MRET series IKBJ, Total Trade (TT): WW: Balance: BOP: CP: SA, for 2026 JUN, first print. The source page reports units of £m, so the ledger transform is multiply by 0.001 into gbp_billions. Historical anchors below use the same IKBJ current-price seasonally adjusted total trade balance variant.","Tool call: Checked the official GOV.UK announcement for UK trade: June 2026 time series release timing."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this forecast targets ONS MRET series IKBJ, Total Trade (TT): WW: Balance: BOP: CP: SA, for 2026 JUN, first print. The source page reports units of £m, so the ledger transform is multiply by 0.001 into gbp_billions. Historical anchors below use the same IKBJ current-price seasonally adjusted total trade balance variant.","Tool call: Checked the official GOV.UK announcement for UK trade: June 2026 time series release timing."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 7.4, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence/reference-class model uses 24 monthly IKBJ values from 2024 JUN to 2026 MAY; base mean = -2.94 gbp_billions, latest May = -1.044, 2026 Jan-May mean = -4.56. Point update = 0.45*(-2.94) + 0.30*(-1.044) + 0.25*(-4.56) = -2.78, then rounded a little more negative to -3.1 because March-April 2026 showed unusually large deficits and May's improvement may partly reverse. For this flow series I size dispersion from the values themselves: sigma = 2.89 gbp_billions over the 24-month sample, so 80% half-width is about 1.28*sigma = 1.28*2.89 = 3.70; final bounds are -3.1 +/- 3.7 = [-6.8, 0.6].","Counter-consideration: upside risk is another unusually strong services surplus or precious-metals-related swing that would land above the interval with a surplus greater than 0.6 gbp_billions. Downside risk is a repeat of March-April weakness in total trade or a goods-import jump not matched by exports, which would land outside the interval below -6.8 gbp_billions."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate / reference class: the recent IKBJ monthly balance reference class from June 2024 through May 2026 has mean -2.94 gbp_billions; the latest five 2026 observations average -4.56 gbp_billions, while May alone was much less negative at -1.044 gbp_billions. I give most weight to regression from May toward the recent deficit base rate, with some weight on weak early-2026 momentum.","Prior/update/interval: persistence/reference-class model uses 24 monthly IKBJ values from 2024 JUN to 2026 MAY; base mean = -2.94 gbp_billions, latest May = -1.044, 2026 Jan-May mean = -4.56. Point update = 0.45*(-2.94) + 0.30*(-1.044) + 0.25*(-4.56) = -2.78, then rounded a little more negative to -3.1 because March-April 2026 showed unusually large deficits and May's improvement may partly reverse. For this flow series I size dispersion from the values themselves: sigma = 2.89 gbp_billions over the 24-month sample, so 80% half-width is about 1.28*sigma = 1.28*2.89 = 3.70; final bounds are -3.1 +/- 3.7 = [-6.8, 0.6]."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-consideration: upside risk is another unusually strong services surplus or precious-metals-related swing that would land above the interval with a surplus greater than 0.6 gbp_billions. Downside risk is a repeat of March-April weakness in total trade or a goods-import jump not matched by exports, which would land outside the interval below -6.8 gbp_billions."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["UK June 2026 Total Trade Balance Forecast","Framing and exact resolver: this forecast targets ONS MRET series IKBJ, Total Trade (TT): WW: Balance: BOP: CP: SA, for 2026 JUN, first print. The source page reports units of £m, so the ledger transform is multiply by 0.001 into gbp_billions. Historical anchors below use the same IKBJ current-price seasonally adjusted total trade balance variant."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: uk-total-trade-balance-june-2026\nrunLabel: Headline\nresolutionDate: 2026-08-13\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.uk-ppi-output-manufactured-products-index-july-2026.2026-08-12T16-06-38Z.eb543a32333d38df","runId":"run.uk-ppi-output-manufactured-products-index-july-2026.2026-08-12T16-06-38Z.eb543a32333d38df","predictionId":"uk-ppi-output-manufactured-products-index-july-2026","specId":"spec.uk-ppi-output-manufactured-products-index-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Reference class/base rate: for this level index, I used recent month-to-month GD6Y changes as the base rate, with the last 29 monthly changes from 2024 JAN to 2026 JUN averaging +0.414 index points and a sample standard deviation of 0.823. This volatility sample excludes the target month by construction. July-only changes from 2016 through 2025 averaged about +0.650, with a sample standard deviation about 0.868.","Prior/update/interval: persistence prior is June GD6Y 153.4 plus the historical July seasonal mean change of +0.65, tempered slightly because the June bulletin showed output PPI annual inflation easing and petroleum output prices falling; level component 153.4, momentum/seasonal component +0.6, one-off petroleum drag about -0.1 relative to spring momentum, policy-mechanism effect 0.0, giving point 154.0. For the interval, using recent level-series successive changes, sigma = 0.823 index points, so 1.28*sigma = 1.054; rounding to a one-decimal first print gives an 80% interval of 154.0 +/- 1.1 = [152.9, 155.1]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this forecast targets ONS series GD6Y, PPI INDEX OUTPUT TOTAL - C Manufactured products, excluding Duty 2015=100, for 2026 JUL, in index_points. The resolving variant is the ONS first-print monthly time-series value from the Producer price inflation UK July 2026 time series release; all anchors below use the same GD6Y manufactured-products excluding-duty index variant.","Tool call: Checked the ONS release calendar for Producer price inflation, UK: July 2026 and its connected time-series release."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["UK GD6Y July 2026 first-print forecast","Framing and exact resolver: this forecast targets ONS series GD6Y, PPI INDEX OUTPUT TOTAL - C Manufactured products, excluding Duty 2015=100, for 2026 JUL, in index_points. The resolving variant is the ONS first-print monthly time-series value from the Producer price inflation UK July 2026 time series release; all anchors below use the same GD6Y manufactured-products excluding-duty index variant."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.2, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is June GD6Y 153.4 plus the historical July seasonal mean change of +0.65, tempered slightly because the June bulletin showed output PPI annual inflation easing and petroleum output prices falling; level component 153.4, momentum/seasonal component +0.6, one-off petroleum drag about -0.1 relative to spring momentum, policy-mechanism effect 0.0, giving point 154.0. For the interval, using recent level-series successive changes, sigma = 0.823 index points, so 1.28*sigma = 1.054; rounding to a one-decimal first print gives an 80% interval of 154.0 +/- 1.1 = [152.9, 155.1].","Counter-consideration: upside risk is a renewed July jump in refined petroleum, metals, or other manufactured-output prices after the Middle East-linked volatility noted by ONS, which would land above the interval if GD6Y rises more than 1.7 points from June. Downside risk is a sharper reversal in petroleum and imported input costs feeding into factory-gate prices, which would land outside the interval below 152.9 if GD6Y falls by more than 0.5 points from June."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior is June GD6Y 153.4 plus the historical July seasonal mean change of +0.65, tempered slightly because the June bulletin showed output PPI annual inflation easing and petroleum output prices falling; level component 153.4, momentum/seasonal component +0.6, one-off petroleum drag about -0.1 relative to spring momentum, policy-mechanism effect 0.0, giving point 154.0. For the interval, using recent level-series successive changes, sigma = 0.823 index points, so 1.28*sigma = 1.054; rounding to a one-decimal first print gives an 80% interval of 154.0 +/- 1.1 = [152.9, 155.1]."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool result: ONS reported producer output factory gate prices rose 3.5% in the year to June 2026, down from 3.7% in May, and monthly output prices were flat in June; input prices rose 7.3% annually and fell 2.0% monthly; coke and refined petroleum output prices rose 43.0% annually but fell 5.9% monthly in June.","Counter-consideration: upside risk is a renewed July jump in refined petroleum, metals, or other manufactured-output prices after the Middle East-linked volatility noted by ONS, which would land above the interval if GD6Y rises more than 1.7 points from June. Downside risk is a sharper reversal in petroleum and imported input costs feeding into factory-gate prices, which would land outside the interval below 152.9 if GD6Y falls by more than 0.5 points from June."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["UK GD6Y July 2026 first-print forecast","Framing and exact resolver: this forecast targets ONS series GD6Y, PPI INDEX OUTPUT TOTAL - C Manufactured products, excluding Duty 2015=100, for 2026 JUL, in index_points. The resolving variant is the ONS first-print monthly time-series value from the Producer price inflation UK July 2026 time series release; all anchors below use the same GD6Y manufactured-products excluding-duty index variant."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: uk-ppi-output-manufactured-products-index-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-19\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-ntia-broadband-al11038-obligations-fy2026.2026-08-11T20-53-14Z.80059204ba3b81ba","runId":"run.us-ntia-broadband-al11038-obligations-fy2026.2026-08-11T20-53-14Z.80059204ba3b81ba","predictionId":"us-ntia-broadband-al11038-obligations-fy2026","specId":"spec.us-ntia-broadband-al11038-obligations-fy2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 3 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: recent official NTIA award-cycle flow proxies are FY2024 about 140.0 and FY2025 409.852 usd_millions, mean 274.9, range 140.0-409.9. Last-print persistence benchmark is 409.9, but the FY2026 current signal is a much smaller and late-year NOFO4 process: $53.0 million estimated total funding, 3 expected awards, applications closing 2026-09-09, with awards expected only after review.","Prior/update/interval: prior = last awarded-cycle persistence 409.9 from FY2025 NOFO2; historical sample = FY2024 140.0 and FY2025 409.852 usd_millions; adjustment components = -310 for the late FY2026 NOFO4 close and no fetched official FY2026 award announcement, -55 for only 3 expected NOFO4 awards, a $53 million funding ceiling, and likely FY2027 slippage, yielding about 45.0. For the flow values, sample sigma = 190.8; 1.28*sigma = 244.2, so an unbounded 80% band around 45 is about -199 to 289. I bound obligations at the nonnegative floor, but use 5 rather than 0 for the lower 80% bound because small FY2026 transaction or amendment obligations remain more likely than exactly zero; the rounded 80% interval is 5-290 usd_millions."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["NTIA Assistance Listing 11.038 FY2026 obligations","The registered target is the USAspending spending_over_time query for financial-assistance award transactions under Assistance Listing 11.038, transformed to usd_millions. The target is a registered query snapshot, so I use the lab-committed 2026-10-22 outer bound rather than inferring a release day."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The registered target is the USAspending spending_over_time query for financial-assistance award transactions under Assistance Listing 11.038, transformed to usd_millions. The target is a registered query snapshot, so I use the lab-committed 2026-10-22 outer bound rather than inferring a release day.","Tool call: Search official NTIA first-NOFO award page for Wireless Innovation Fund award totals."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 285, distribution present, forecast step count 1.","evidence":["Model candidates under thesis_model_candidate_v1, sparse-flow version: persistence candidate point=409.9, p10=165.7, p50=409.9, p90=654.1, 80% interval 165.7-654.1, 90% interval 91.1-728.7, interval_method=sparse annual flow sigma, calibration_n=2, train_cutoff=FY2025, walk_forward_score unavailable because only two comparable award cycles. Current-NOFO candidate point=45.0, p10=5.0, p50=45.0, p90=90.0, 80% interval 5.0-90.0, 90% interval 0.0-120.0, interval_method=NOFO4 timing, award-count cap, and $53 million funding ceiling, calibration_n=3 public program facts, train_cutoff=2026-08-11. I select the current-NOFO candidate but retain the persistence sigma for tail width because obligations are lumpy.","Prior/update/interval: prior = last awarded-cycle persistence 409.9 from FY2025 NOFO2; historical sample = FY2024 140.0 and FY2025 409.852 usd_millions; adjustment components = -310 for the late FY2026 NOFO4 close and no fetched official FY2026 award announcement, -55 for only 3 expected NOFO4 awards, a $53 million funding ceiling, and likely FY2027 slippage, yielding about 45.0. For the flow values, sample sigma = 190.8; 1.28*sigma = 244.2, so an unbounded 80% band around 45 is about -199 to 289. I bound obligations at the nonnegative floor, but use 5 rather than 0 for the lower 80% bound because small FY2026 transaction or amendment obligations remain more likely than exactly zero; the rounded 80% interval is 5-290 usd_millions."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Model candidates under thesis_model_candidate_v1, sparse-flow version: persistence candidate point=409.9, p10=165.7, p50=409.9, p90=654.1, 80% interval 165.7-654.1, 90% interval 91.1-728.7, interval_method=sparse annual flow sigma, calibration_n=2, train_cutoff=FY2025, walk_forward_score unavailable because only two comparable award cycles. Current-NOFO candidate point=45.0, p10=5.0, p50=45.0, p90=90.0, 80% interval 5.0-90.0, 90% interval 0.0-120.0, interval_method=NOFO4 timing, award-count cap, and $53 million funding ceiling, calibration_n=3 public program facts, train_cutoff=2026-08-11. I select the current-NOFO candidate but retain the persistence sigma for tail width because obligations are lumpy.","Prior/update/interval: prior = last awarded-cycle persistence 409.9 from FY2025 NOFO2; historical sample = FY2024 140.0 and FY2025 409.852 usd_millions; adjustment components = -310 for the late FY2026 NOFO4 close and no fetched official FY2026 award announcement, -55 for only 3 expected NOFO4 awards, a $53 million funding ceiling, and likely FY2027 slippage, yielding about 45.0. For the flow values, sample sigma = 190.8; 1.28*sigma = 244.2, so an unbounded 80% band around 45 is about -199 to 289. I bound obligations at the nonnegative floor, but use 5 rather than 0 for the lower 80% bound because small FY2026 transaction or amendment obligations remain more likely than exactly zero; the rounded 80% interval is 5-290 usd_millions."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: recent official NTIA award-cycle flow proxies are FY2024 about 140.0 and FY2025 409.852 usd_millions, mean 274.9, range 140.0-409.9. Last-print persistence benchmark is 409.9, but the FY2026 current signal is a much smaller and late-year NOFO4 process: $53.0 million estimated total funding, 3 expected awards, applications closing 2026-09-09, with awards expected only after review.","Model candidates under thesis_model_candidate_v1, sparse-flow version: persistence candidate point=409.9, p10=165.7, p50=409.9, p90=654.1, 80% interval 165.7-654.1, 90% interval 91.1-728.7, interval_method=sparse annual flow sigma, calibration_n=2, train_cutoff=FY2025, walk_forward_score unavailable because only two comparable award cycles. Current-NOFO candidate point=45.0, p10=5.0, p50=45.0, p90=90.0, 80% interval 5.0-90.0, 90% interval 0.0-120.0, interval_method=NOFO4 timing, award-count cap, and $53 million funding ceiling, calibration_n=3 public program facts, train_cutoff=2026-08-11. I select the current-NOFO candidate but retain the persistence sigma for tail width because obligations are lumpy."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: Open USAspending API endpoint documentation and endpoint index for /api/v2/search/spending_over_time/.","Tool result: Fetched USAspending API docs: endpoints do not require authorization; status codes listed include 200, 400, and 500; /api/v2/search/spending_over_time/ is a POST endpoint returning transaction aggregated amounts."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-ntia-broadband-al11038-obligations-fy2026\nrunLabel: Headline\nresolutionDate: 2026-10-22\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-dod-prime-award-obligations-fy2026.2026-08-11T18-17-53Z.4a0b94ec8eaf5ebd","runId":"run.us-dod-prime-award-obligations-fy2026.2026-08-11T18-17-53Z.4a0b94ec8eaf5ebd","predictionId":"us-dod-prime-award-obligations-fy2026","specId":"spec.us-dod-prime-award-obligations-fy2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 3 historical point(s) and explicit outside-view language.","evidence":["Base rate / reference class: the directly fetched target endpoint gives 245.1B through latest_action_date 2026-07-10, while the fetched FY2024 DoD top-six subagency proxy sums to 427.5B. Complete prior-year observations from the same agency 097 awards endpoint were unavailable in the draft evidence, so the FY2024 top-six figure is a weak public proxy rather than target-series history.","Model candidates: incomplete-YTD run-rate = 245.063 * 365 / 283 = 316.1B, but this underweights late reporting and DoD publication lag; FY2024 top-six proxy = 427.5B before smaller subagencies. Selected benchmark prior = 455.0B, reflecting the proxy scale plus a modest residual for the other 30 DoD subagencies visible in the agency overview. No current fetched signal justifies a large move above that scale, so no positive inside-view adjustment is added."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["USAspending DoD FY2026 Prime Award Obligations","Resolution target is the registered USAspending API v2 agency 097 awards endpoint, fiscal_year=2026, obligations field, converted to billions USD. This is a registered query snapshot target with expectedReleaseWindow 2026-10-15 to 2026-10-22, so I use the ledger outer deadline 2026-10-22 rather than inferring a release-calendar day."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Resolution target is the registered USAspending API v2 agency 097 awards endpoint, fiscal_year=2026, obligations field, converted to billions USD. This is a registered query snapshot target with expectedReleaseWindow 2026-10-15 to 2026-10-22, so I use the ledger outer deadline 2026-10-22 rather than inferring a release-calendar day."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 150, distribution present, forecast step count 1.","evidence":["Prior/update/interval: prior = 455.0B from the FY2024 top-six public proxy plus smaller-subagency residual; historical sample is not a complete target-series sample, only the fetched FY2026 YTD target endpoint and fetched FY2024 DoD subagency proxy. Adjustment components = 0.0B net because FY2026 YTD is incomplete and lagged. Interval method is deliberately wide fallback-prior uncertainty, not realized target volatility: judgmental sigma = 58.6B, half-width = 1.28*sigma = 75.0B, so 80% interval = 455.0 +/- 75.0 = [380.0, 530.0]B.","Downside risk outside the interval: if the registered October snapshot still misses a large share of late-FY DoD contract or IDV awards because of the 90-day publication delay, the API obligations field could land below 380B. Upside risk outside the interval: if late-FY contract awards and IDVs post faster than the current latest_action_date pattern, or FY2026 procurement obligations materially exceed the FY2024 proxy scale, the snapshot could land above 530B."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: prior = 455.0B from the FY2024 top-six public proxy plus smaller-subagency residual; historical sample is not a complete target-series sample, only the fetched FY2026 YTD target endpoint and fetched FY2024 DoD subagency proxy. Adjustment components = 0.0B net because FY2026 YTD is incomplete and lagged. Interval method is deliberately wide fallback-prior uncertainty, not realized target volatility: judgmental sigma = 58.6B, half-width = 1.28*sigma = 75.0B, so 80% interval = 455.0 +/- 75.0 = [380.0, 530.0]B.","Downside risk outside the interval: if the registered October snapshot still misses a large share of late-FY DoD contract or IDV awards because of the 90-day publication delay, the API obligations field could land below 380B. Upside risk outside the interval: if late-FY contract awards and IDVs post faster than the current latest_action_date pattern, or FY2026 procurement obligations materially exceed the FY2024 proxy scale, the snapshot could land above 530B."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool result: Fetched endpoint contract: fiscal_year is an optional number parameter; response attributes include toptier_code, fiscal_year, latest_action_date, transaction_count, obligations, and messages; sample response shows fiscal_year 2021, transaction_count 2, obligations 90000.0.","Model candidates: incomplete-YTD run-rate = 245.063 * 365 / 283 = 316.1B, but this underweights late reporting and DoD publication lag; FY2024 top-six proxy = 427.5B before smaller subagencies. Selected benchmark prior = 455.0B, reflecting the proxy scale plus a modest residual for the other 30 DoD subagencies visible in the agency overview. No current fetched signal justifies a large move above that scale, so no positive inside-view adjustment is added."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Resolution target is the registered USAspending API v2 agency 097 awards endpoint, fiscal_year=2026, obligations field, converted to billions USD. This is a registered query snapshot target with expectedReleaseWindow 2026-10-15 to 2026-10-22, so I use the ledger outer deadline 2026-10-22 rather than inferring a release-calendar day.","Tool result: Fetched agency 097 awards endpoint: fiscal_year 2026, latest_action_date 2026-07-10T00:00:00, transaction_count 2205913, obligations 245063144206.58 USD = 245.063 billion USD."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-dod-prime-award-obligations-fy2026\nrunLabel: Headline\nresolutionDate: 2026-10-22\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-dod-prime-contract-obligations-fy2026.2026-08-11T18-21-59Z.4f494508c4cccf03","runId":"run.us-dod-prime-contract-obligations-fy2026.2026-08-11T18-21-59Z.4f494508c4cccf03","predictionId":"us-dod-prime-contract-obligations-fy2026","specId":"spec.us-dod-prime-contract-obligations-fy2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.51,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base rate / reference class: the recent public FPDS defense-contract proxy totals are FY2022 415, FY2023 456, FY2024 445, FY2025 491 billions. Last-print persistence is 491.0. The simple one-year-change history is +41, -11, +46, so recent realized changes have mean +25.3 and a wide range from -11 to +46. The draft evidence did not include successful FY2022-FY2025 same-endpoint USAspending history fetches, so this proxy is not treated as the resolver series; I carry extra uncertainty for proxy mismatch and first-snapshot timing.","Prior/update/interval: prior=last-print persistence 491.0 from FY2025 GAO FPDS defense services+products proxy; historical sample=FY2022-FY2025 values 415,456,445,491; adjustment components=+14.0 for FY2026 acquisition funding support and mandatory reconciliation availability, shrunk because enacted base procurement/RDT&E is not uniformly above FY2025 and funds are available through 2029; point=491.0+14.0=505.0. For uncertainty, successive changes are +41,-11,+46, mean change 25.3, sigma = 31.6; 80% half-width roughly 1.28*sigma = 40.4, widened by 20% to 48.5 for GAO-proxy-to-USAspending-target mismatch and October registered-snapshot reporting lag, so interval is 505.0-48.5=456.5 to 505.0+48.5=553.5."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 9 source-context item(s), activity log present.","evidence":["FY2026 DoD prime contract obligations","The registered target is the USAspending API v2 agency 097 obligations_by_award_category contracts row for fiscal_year=2026. The unit, slug, dataPointId, and 2026-10-22 outer-bound resolution date are taken from the canonical ledger target. I attempted the required specs.json check; the hosted fetch returned no visible body, so I kept the ledger-provided slug rather than inventing a replacement."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Base rate / reference class: the recent public FPDS defense-contract proxy totals are FY2022 415, FY2023 456, FY2024 445, FY2025 491 billions. Last-print persistence is 491.0. The simple one-year-change history is +41, -11, +46, so recent realized changes have mean +25.3 and a wide range from -11 to +46. The draft evidence did not include successful FY2022-FY2025 same-endpoint USAspending history fetches, so this proxy is not treated as the resolver series; I carry extra uncertainty for proxy mismatch and first-snapshot timing.","Review disposition: accepted the critique that the draft prior used a GAO FPDS proxy rather than same-endpoint USAspending history, so the final trace labels it as a proxy instead of the resolver series, clarifies the FY2026 API fetch was not used as an amount input, and widens the interval 20% for proxy-definition and first-snapshot timing risk. I did not replace the history with unfetched USAspending values."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 97, distribution present, forecast step count 1.","evidence":["Base rate / reference class: the recent public FPDS defense-contract proxy totals are FY2022 415, FY2023 456, FY2024 445, FY2025 491 billions. Last-print persistence is 491.0. The simple one-year-change history is +41, -11, +46, so recent realized changes have mean +25.3 and a wide range from -11 to +46. The draft evidence did not include successful FY2022-FY2025 same-endpoint USAspending history fetches, so this proxy is not treated as the resolver series; I carry extra uncertainty for proxy mismatch and first-snapshot timing.","Model candidates under thesis_model_candidate_v1, computed from fetched history: persistence candidate point=491.0, p10=450.6, p50=491.0, p90=531.4, 80% interval 450.6-531.4, 90% interval 439.0-543.0, interval_method=successive-change residual normal, calibration_n=3, train_cutoff=FY2025; mean-change candidate point=516.3, p10=475.9, p50=516.3, p90=556.7, 80% interval 475.9-556.7, calibration_n=3. I select persistence-plus-current-budget-update because the sample is short and FY2026 budget evidence supports only a modest upward move, not the full mean-change rule."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Model candidates under thesis_model_candidate_v1, computed from fetched history: persistence candidate point=491.0, p10=450.6, p50=491.0, p90=531.4, 80% interval 450.6-531.4, 90% interval 439.0-543.0, interval_method=successive-change residual normal, calibration_n=3, train_cutoff=FY2025; mean-change candidate point=516.3, p10=475.9, p50=516.3, p90=556.7, 80% interval 475.9-556.7, calibration_n=3. I select persistence-plus-current-budget-update because the sample is short and FY2026 budget evidence supports only a modest upward move, not the full mean-change rule.","Prior/update/interval: prior=last-print persistence 491.0 from FY2025 GAO FPDS defense services+products proxy; historical sample=FY2022-FY2025 values 415,456,445,491; adjustment components=+14.0 for FY2026 acquisition funding support and mandatory reconciliation availability, shrunk because enacted base procurement/RDT&E is not uniformly above FY2025 and funds are available through 2029; point=491.0+14.0=505.0. For uncertainty, successive changes are +41,-11,+46, mean change 25.3, sigma = 31.6; 80% half-width roughly 1.28*sigma = 40.4, widened by 20% to 48.5 for GAO-proxy-to-USAspending-target mismatch and October registered-snapshot reporting lag, so interval is 505.0-48.5=456.5 to 505.0+48.5=553.5."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate / reference class: the recent public FPDS defense-contract proxy totals are FY2022 415, FY2023 456, FY2024 445, FY2025 491 billions. Last-print persistence is 491.0. The simple one-year-change history is +41, -11, +46, so recent realized changes have mean +25.3 and a wide range from -11 to +46. The draft evidence did not include successful FY2022-FY2025 same-endpoint USAspending history fetches, so this proxy is not treated as the resolver series; I carry extra uncertainty for proxy mismatch and first-snapshot timing.","Prior/update/interval: prior=last-print persistence 491.0 from FY2025 GAO FPDS defense services+products proxy; historical sample=FY2022-FY2025 values 415,456,445,491; adjustment components=+14.0 for FY2026 acquisition funding support and mandatory reconciliation availability, shrunk because enacted base procurement/RDT&E is not uniformly above FY2025 and funds are available through 2029; point=491.0+14.0=505.0. For uncertainty, successive changes are +41,-11,+46, mean change 25.3, sigma = 31.6; 80% half-width roughly 1.28*sigma = 40.4, widened by 20% to 48.5 for GAO-proxy-to-USAspending-target mismatch and October registered-snapshot reporting lag, so interval is 505.0-48.5=456.5 to 505.0+48.5=553.5."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The registered target is the USAspending API v2 agency 097 obligations_by_award_category contracts row for fiscal_year=2026. The unit, slug, dataPointId, and 2026-10-22 outer-bound resolution date are taken from the canonical ledger target. I attempted the required specs.json check; the hosted fetch returned no visible body, so I kept the ledger-provided slug rather than inventing a replacement.","Tool call: Fetched USAspending API endpoint index for /api/v2/agency/<TOPTIER_AGENCY_CODE>/obligations_by_award_category/ and target code 097 with fiscal_year=2026."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-dod-prime-contract-obligations-fy2026\nrunLabel: Headline\nresolutionDate: 2026-10-22\ntraceLineCount: 19\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: resolution clarity (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.nonfarm-payrolls-august-2026.2026-08-11T12-59-29Z.75b6e92e82d8dda0","runId":"run.nonfarm-payrolls-august-2026.2026-08-11T12-59-29Z.75b6e92e82d8dda0","predictionId":"nonfarm-payrolls-august-2026","specId":"spec.nonfarm-payrolls-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool result: Fetched July 2026 first-print total nonfarm payroll employment change of -23,000, unemployment rate 4.1 percent, prior-12-month average payroll gain 34,000, May revised to +63,000, June revised to +20,000, and combined May-June revision of -103,000.","Base rate/reference class: using current-vintage CES0000000001 changes from January 2024 through July 2026 gives a mean near +61k, but the more relevant recent state is much weaker: the latest three revised changes are +63k, +20k, and -23k, averaging +20k, while the BLS release itself reports a +34k prior-12-month average."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["August 2026 BLS total nonfarm payrolls first print","Resolver: use BLS CES total nonfarm, all employees, seasonally adjusted, first-print month-over-month change for August 2026, in thousands, from Employment Situation Table B-1. The ledger window ending 2026-09-11 conflicts with the official BLS Employment Situation schedule, which states August 2026 is released on 2026-09-04 at 08:30 ET; I keep the same slug and dataPointId but use the official scheduled release day as the resolution date."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["August 2026 BLS total nonfarm payrolls first print","Resolver: use BLS CES total nonfarm, all employees, seasonally adjusted, first-print month-over-month change for August 2026, in thousands, from Employment Situation Table B-1. The ledger window ending 2026-09-11 conflicts with the official BLS Employment Situation schedule, which states August 2026 is released on 2026-09-04 at 08:30 ET; I keep the same slug and dataPointId but use the official scheduled release day as the resolution date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 254, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is the recent three-month average of +20k, cross-checked against the BLS stated prior-12-month average of +34k and the 2024-2026 current-vintage reference class mean near +61k. I adjust +15k from the +20k recent pace for expected partial rebound from July's local-government-education and retail drag, but cap the point at +35k because May-June revisions were -103k and private July hiring was only +30k. For dispersion, I used 30 fetched current-vintage monthly changes from 2024 M02 through 2026 M07 as a proxy rather than a first-print-only volatility sample: sigma = 99 thousand; 1.28*sigma = 127 thousand, so 35 +/- 127 gives an 80% interval of -92 to +162 thousand.","Counter-considerations: upside risk is a rebound in state/local education seasonal adjustment, continued health-care hiring, and stronger construction/manufacturing that would land above the interval if the first print exceeds +162k. Downside risk is another broad hiring stall, additional retail/government losses, or a low survey response first print; that would land below the interval if payrolls fall by more than 92k."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior is the recent three-month average of +20k, cross-checked against the BLS stated prior-12-month average of +34k and the 2024-2026 current-vintage reference class mean near +61k. I adjust +15k from the +20k recent pace for expected partial rebound from July's local-government-education and retail drag, but cap the point at +35k because May-June revisions were -103k and private July hiring was only +30k. For dispersion, I used 30 fetched current-vintage monthly changes from 2024 M02 through 2026 M07 as a proxy rather than a first-print-only volatility sample: sigma = 99 thousand; 1.28*sigma = 127 thousand, so 35 +/- 127 gives an 80% interval of -92 to +162 thousand."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Resolver: use BLS CES total nonfarm, all employees, seasonally adjusted, first-print month-over-month change for August 2026, in thousands, from Employment Situation Table B-1. The ledger window ending 2026-09-11 conflicts with the official BLS Employment Situation schedule, which states August 2026 is released on 2026-09-04 at 08:30 ET; I keep the same slug and dataPointId but use the official scheduled release day as the resolution date.","Base rate/reference class: using current-vintage CES0000000001 changes from January 2024 through July 2026 gives a mean near +61k, but the more relevant recent state is much weaker: the latest three revised changes are +63k, +20k, and -23k, averaging +20k, while the BLS release itself reports a +34k prior-12-month average."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Resolver: use BLS CES total nonfarm, all employees, seasonally adjusted, first-print month-over-month change for August 2026, in thousands, from Employment Situation Table B-1. The ledger window ending 2026-09-11 conflicts with the official BLS Employment Situation schedule, which states August 2026 is released on 2026-09-04 at 08:30 ET; I keep the same slug and dataPointId but use the official scheduled release day as the resolution date.","Prior/update/interval: persistence prior is the recent three-month average of +20k, cross-checked against the BLS stated prior-12-month average of +34k and the 2024-2026 current-vintage reference class mean near +61k. I adjust +15k from the +20k recent pace for expected partial rebound from July's local-government-education and retail drag, but cap the point at +35k because May-June revisions were -103k and private July hiring was only +30k. For dispersion, I used 30 fetched current-vintage monthly changes from 2024 M02 through 2026 M07 as a proxy rather than a first-print-only volatility sample: sigma = 99 thousand; 1.28*sigma = 127 thousand, so 35 +/- 127 gives an 80% interval of -92 to +162 thousand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: nonfarm-payrolls-august-2026\nrunLabel: Headline\nresolutionDate: 2026-09-04\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.unemployment-rate-august-2026.2026-08-11T13-01-38Z.d23a0a0453de0603","runId":"run.unemployment-rate-august-2026.2026-08-11T13-01-38Z.d23a0a0453de0603","predictionId":"unemployment-rate-august-2026","specId":"spec.unemployment-rate-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool result: The July 2026 summary reports nonfarm payroll employment -23,000, unemployment rate 4.1 percent, unemployed people 6.9 million, labor force participation rate 61.4 percent, and prior May/June payroll revisions totaling -103,000.","Tool result: The DOL claims report shows seasonally adjusted initial claims of 199,000 in the latest week used for this forecast, prior-week claims of 208,000, and a 4-week moving average of 207,500."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Resolver framing: this targets the BLS Current Population Survey total U-3 unemployment rate, seasonally adjusted, series LNS14000000 as displayed in Employment Situation Table A-1 for August 2026, first print only. The registered resolving source is the first-print Employment Situation release page; Table A-1 is the extracting table within that release.","Tool call: Checked the BLS Employment Situation release schedule for the August 2026 reference month."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Resolver framing: this targets the BLS Current Population Survey total U-3 unemployment rate, seasonally adjusted, series LNS14000000 as displayed in Employment Situation Table A-1 for August 2026, first print only. The registered resolving source is the first-print Employment Situation release page; Table A-1 is the extracting table within that release.","Tool call: Checked the BLS Employment Situation release schedule for the August 2026 reference month."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.3, distribution present, forecast step count 1.","evidence":["Tool call: Read BLS Table A-1 for the seasonally adjusted total unemployment rate and labor-force details.","Prior/update/interval: persistence prior is July 2026 unemployment rate 4.1. Historical sample is monthly changes from the BLS chart from Jan. 2024 through July 2026, using available published monthly observations and omitting no value as an outcome estimate when it is not shown in the fetched chart table. sigma = 0.11 percentage point from successive monthly changes. Update components: +0.06 for weak July payrolls and downward payroll revisions, +0.03 for the participation-rate decline being unlikely to keep lowering U-3 at the same pace, and -0.04 for still-low claims/no layoff surge context, giving an unrounded mean near 4.15. Interval method: 80 percent half-width is roughly 1.28*sigma = 1.28*0.11 = 0.14, so 4.15 +/- 0.14 gives about 4.01 to 4.29, rounded to the target display as 4.0 to 4.3 with point 4.2."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Read the official Department of Labor Unemployment Insurance Weekly Claims report used for the layoff-pressure cross-check."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: for a one-month-ahead level forecast of a rounded unemployment rate, the strongest base rate is persistence plus the empirical monthly-change distribution. Recent values have sat in a narrow 4.1 to 4.4 percent range in 2026, so large moves are possible but not the central case.","Counter-considerations: upside risk is an August household-survey employment drop or rebound in participation that would push unemployment to 4.4 or higher, outside the interval. Downside risk is another participation decline or noisy drop in unemployed workers that would keep the rate at 3.9 or below, also outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["US CPS unemployment rate forecast for August 2026","Tool result: The DOL claims report shows seasonally adjusted initial claims of 199,000 in the latest week used for this forecast, prior-week claims of 208,000, and a 4-week moving average of 207,500."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: unemployment-rate-august-2026\nrunLabel: Headline\nresolutionDate: 2026-09-04\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-telework-rate-august-2026.2026-08-11T13-11-04Z.a27a8814f8283d06","runId":"run.us-telework-rate-august-2026.2026-08-11T13-11-04Z.a27a8814f8283d06","predictionId":"us-telework-rate-august-2026","specId":"spec.us-telework-rate-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate and reference class: I use the official monthly LNU0201B46B series since October 2022, emphasizing 2024-2026 because the series has settled into a post-pandemic plateau. The base rate is persistence around the recent 21.7-22.7 percent band rather than a trend extrapolation from the 2022-2024 rise.","Prior/update/interval: persistence prior = July 2026 LNU0201B46B level 22.2, historical sample = official LNU0201B46B recent monthly changes Feb-Jul 2026 of -0.3, -0.1, -0.9, +0.1, -0.1, +0.5 percentage points plus August seasonal changes of -0.4, -0.2, and 0.0 from 2023-2025; adjustment components = -0.1 for August seasonality and no material structural policy shock, giving point 22.1. For interval sizing on recent successive changes, sigma = RMS recent monthly change volatility = sqrt((0.09+0.01+0.81+0.01+0.01+0.25)/6) = 0.44 percentage point, so 1.28*sigma = 0.57; rounded around 22.1 gives an 80% interval of 21.5 to 22.7."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this targets the BLS CPS telework rate, series LNU0201B46B, for August 2026 on CPS Table A-41. The variant is not seasonally adjusted and national, measured as people who teleworked or worked at home for pay as a percent of total people at work, Total, 16 years and over.","Tool call: Opened BLS Employment Situation CPS Table A-41 current table at https://www.bls.gov/web/empsit/cpseea41.htm."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["US CPS telework share, August 2026 first print","Tool call: Checked BLS Schedule of Releases for the Employment Situation at https://www.bls.gov/schedule/news_release/empsit.htm?categoryId=1&orient=1."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.2, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = July 2026 LNU0201B46B level 22.2, historical sample = official LNU0201B46B recent monthly changes Feb-Jul 2026 of -0.3, -0.1, -0.9, +0.1, -0.1, +0.5 percentage points plus August seasonal changes of -0.4, -0.2, and 0.0 from 2023-2025; adjustment components = -0.1 for August seasonality and no material structural policy shock, giving point 22.1. For interval sizing on recent successive changes, sigma = RMS recent monthly change volatility = sqrt((0.09+0.01+0.81+0.01+0.01+0.25)/6) = 0.44 percentage point, so 1.28*sigma = 0.57; rounded around 22.1 gives an 80% interval of 21.5 to 22.7.","Counter-considerations: upside risk is a survey mix or white-collar employment composition shift that keeps July's rebound and would land above the interval if the first print is above 22.7. Downside risk is a vacation/reference-week or composition effect similar to April 2026 that would land below the interval if the first print is below 21.5. Outside the interval would most likely indicate sampling noise or a genuine change in who was at work during the August CPS reference week, not a slow trend."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate and reference class: I use the official monthly LNU0201B46B series since October 2022, emphasizing 2024-2026 because the series has settled into a post-pandemic plateau. The base rate is persistence around the recent 21.7-22.7 percent band rather than a trend extrapolation from the 2022-2024 rise.","Level and momentum: July 2026 printed 22.2 after 21.7 in June and 21.8 in May. The 2026 year-to-date average through July is about 22.24, but April-July average is about 21.85, so I center just below July at 22.1 rather than chasing the one-month rebound."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool result: Fetched July 2026 Table A-41 row Total, 16 years and over: total people at work 153,406 thousand; people who teleworked or worked at home for pay 34,079 thousand; teleworked some hours 17,134 thousand; teleworked all hours 16,946 thousand; percent distribution teleworked 22.2, some hours 11.2, all hours 11.0, did not telework 77.8.","Level and momentum: July 2026 printed 22.2 after 21.7 in June and 21.8 in May. The 2026 year-to-date average through July is about 22.24, but April-July average is about 21.85, so I center just below July at 22.1 rather than chasing the one-month rebound."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: persistence prior = July 2026 LNU0201B46B level 22.2, historical sample = official LNU0201B46B recent monthly changes Feb-Jul 2026 of -0.3, -0.1, -0.9, +0.1, -0.1, +0.5 percentage points plus August seasonal changes of -0.4, -0.2, and 0.0 from 2023-2025; adjustment components = -0.1 for August seasonality and no material structural policy shock, giving point 22.1. For interval sizing on recent successive changes, sigma = RMS recent monthly change volatility = sqrt((0.09+0.01+0.81+0.01+0.01+0.25)/6) = 0.44 percentage point, so 1.28*sigma = 0.57; rounded around 22.1 gives an 80% interval of 21.5 to 22.7.","Counter-considerations: upside risk is a survey mix or white-collar employment composition shift that keeps July's rebound and would land above the interval if the first print is above 22.7. Downside risk is a vacation/reference-week or composition effect similar to April 2026 that would land below the interval if the first print is below 21.5. Outside the interval would most likely indicate sampling noise or a genuine change in who was at work during the August CPS reference week, not a slow trend."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-telework-rate-august-2026\nrunLabel: Headline\nresolutionDate: 2026-09-04\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-cpi-u-mom-august-2026.2026-08-11T12-54-47Z.9631ff28a123e02c","runId":"run.us-cpi-u-mom-august-2026.2026-08-11T12-54-47Z.9631ff28a123e02c","predictionId":"us-cpi-u-mom-august-2026","specId":"spec.us-cpi-u-mom-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: using the official first-print rounded monthly changes available from January 2025 through June 2026, excluding missing October-November 2025, the reference class is 0.6, 0.4, 0.2, 0.3, 0.2, 0.3, 0.2, 0.4, 0.3, 0.3, 0.2, 0.3, 0.9, 0.6, 0.5, -0.4. The base rate mean is about 0.33 percent and the median is 0.3 percent. No July 2026 CPI first print was available at the draft run time, before the scheduled August 12, 2026 release.","Prior/update/interval: persistence/base-rate model uses the 16 observed official rounded CPI-U all-items SA MoM prints from Jan. 2025-Jun. 2026 as the historical sample; mean = 5.3/16 = 0.331 percent, sample sigma = 0.27 percentage points from the values themselves for this change series, and 1.28*sigma = 1.28*0.27 = 0.35 percentage points. Adjustment components: June's -0.4 headline was dominated by energy at -5.7 and core at 0.0, so I pull the August point below the 0.33 base rate only slightly because two months ahead likely mean-reverts energy while shelter/food keep positive pressure. I use point 0.28 and widen modestly to a 0.40 half-width because the 2026 energy regime produced March 0.9, April 0.6, May 0.5, June -0.4; implied 80 percent interval is 0.28 - 0.40 = -0.12 to 0.28 + 0.40 = 0.68."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Resolver framing: the target is the BLS CPI-U all items, U.S. city average, seasonally adjusted one-month percent change for August 2026, first print only. The BLS series code for the seasonally adjusted all-items index is CUSR0000SA0; FRED mirrors the same BLS source as CPIAUCSL, but final resolution should use the BLS news release URL.","Tool call: Checked BLS CPI release calendar and September 2026 selected-release schedule for the August 2026 CPI release date."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Resolver framing: the target is the BLS CPI-U all items, U.S. city average, seasonally adjusted one-month percent change for August 2026, first print only. The BLS series code for the seasonally adjusted all-items index is CUSR0000SA0; FRED mirrors the same BLS source as CPIAUCSL, but final resolution should use the BLS news release URL.","Tool call: Checked BLS CPI release calendar and September 2026 selected-release schedule for the August 2026 CPI release date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.8, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence/base-rate model uses the 16 observed official rounded CPI-U all-items SA MoM prints from Jan. 2025-Jun. 2026 as the historical sample; mean = 5.3/16 = 0.331 percent, sample sigma = 0.27 percentage points from the values themselves for this change series, and 1.28*sigma = 1.28*0.27 = 0.35 percentage points. Adjustment components: June's -0.4 headline was dominated by energy at -5.7 and core at 0.0, so I pull the August point below the 0.33 base rate only slightly because two months ahead likely mean-reverts energy while shelter/food keep positive pressure. I use point 0.28 and widen modestly to a 0.40 half-width because the 2026 energy regime produced March 0.9, April 0.6, May 0.5, June -0.4; implied 80 percent interval is 0.28 - 0.40 = -0.12 to 0.28 + 0.40 = 0.68.","Counter-considerations: upside risk is a renewed gasoline or utility-energy rebound plus sticky shelter, which would land above the interval if headline CPI prints around 0.7 percent or higher. Downside risk is another broad energy decline combined with flat core goods, which would land outside the interval below -0.12 percent. A policy or methodology surprise is not the resolver; only the first BLS CPI-U all-items SA August print matters."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: BLS Table A for December 2025 shows all-items seasonally adjusted monthly changes of 0.3 percent in June 2025, 0.2 in July 2025, 0.4 in August 2025, 0.3 in September 2025, and 0.3 in December 2025; the same release notes Oct. and Nov. 2025 all-items data values were unavailable because of the 2025 appropriations lapse.","Prior/update/interval: persistence/base-rate model uses the 16 observed official rounded CPI-U all-items SA MoM prints from Jan. 2025-Jun. 2026 as the historical sample; mean = 5.3/16 = 0.331 percent, sample sigma = 0.27 percentage points from the values themselves for this change series, and 1.28*sigma = 1.28*0.27 = 0.35 percentage points. Adjustment components: June's -0.4 headline was dominated by energy at -5.7 and core at 0.0, so I pull the August point below the 0.33 base rate only slightly because two months ahead likely mean-reverts energy while shelter/food keep positive pressure. I use point 0.28 and widen modestly to a 0.40 half-width because the 2026 energy regime produced March 0.9, April 0.6, May 0.5, June -0.4; implied 80 percent interval is 0.28 - 0.40 = -0.12 to 0.28 + 0.40 = 0.68."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Resolver framing: the target is the BLS CPI-U all items, U.S. city average, seasonally adjusted one-month percent change for August 2026, first print only. The BLS series code for the seasonally adjusted all-items index is CUSR0000SA0; FRED mirrors the same BLS source as CPIAUCSL, but final resolution should use the BLS news release URL.","Counter-considerations: upside risk is a renewed gasoline or utility-energy rebound plus sticky shelter, which would land above the interval if headline CPI prints around 0.7 percent or higher. Downside risk is another broad energy decline combined with flat core goods, which would land outside the interval below -0.12 percent. A policy or methodology surprise is not the resolver; only the first BLS CPI-U all-items SA August print matters."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["US CPI-U Headline MoM Forecast For August 2026","Prior/update/interval: persistence/base-rate model uses the 16 observed official rounded CPI-U all-items SA MoM prints from Jan. 2025-Jun. 2026 as the historical sample; mean = 5.3/16 = 0.331 percent, sample sigma = 0.27 percentage points from the values themselves for this change series, and 1.28*sigma = 1.28*0.27 = 0.35 percentage points. Adjustment components: June's -0.4 headline was dominated by energy at -5.7 and core at 0.0, so I pull the August point below the 0.33 base rate only slightly because two months ahead likely mean-reverts energy while shelter/food keep positive pressure. I use point 0.28 and widen modestly to a 0.40 half-width because the 2026 energy regime produced March 0.9, April 0.6, May 0.5, June -0.4; implied 80 percent interval is 0.28 - 0.40 = -0.12 to 0.28 + 0.40 = 0.68."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-cpi-u-mom-august-2026\nrunLabel: Headline\nresolutionDate: 2026-09-11\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-core-cpi-mom-august-2026.2026-08-11T12-56-34Z.efd5189a764a2bff","runId":"run.us-core-cpi-mom-august-2026.2026-08-11T12-56-34Z.efd5189a764a2bff","predictionId":"us-core-cpi-mom-august-2026","specId":"spec.us-core-cpi-mom-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: for this change-flow target I anchor on the recent official BLS core CPI-U SA monthly changes themselves. The seven-month reference class average from Dec. 2025 through Jun. 2026 is 1.5 / 7 = 0.214 percent, and the 12-month core rate of 2.6 percent is consistent with a monthly pace near 0.21 percent.","Prior/update/interval: persistence prior is the recent BLS Table A reference class, Dec. 2025-Jun. 2026 core monthly values [0.2, 0.3, 0.2, 0.2, 0.4, 0.2, 0.0], mean 0.214. No separate formal time-series model was used because the short same-variant official Table A persistence prior is transparent and directly matched to this first-print monthly-change target. Adjustment components: +0.04 for mean reversion after June's unusually soft 0.0 and several one-off category declines, -0.02 for shelter cooling to 0.1 and soft core goods, net point about 0.24. Interval method uses the sample dispersion of those fetched monthly change values: sigma = 0.12, so 1.28*sigma = 0.15. Applying a roughly symmetric 80% band around 0.24 gives 0.24 - 0.16 = 0.08 and 0.24 + 0.16 = 0.40."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 2 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this is CPI-U U.S. city average, all items less food and energy, seasonally adjusted, percent change from the preceding month for August 2026. The ledger window is 2026-09-08 to 2026-09-16; the BLS CPI release calendar gives the concrete August 2026 CPI release date as September 11, 2026 at 08:30 ET, which is inside that window, so I use 2026-09-11 as the resolution date.","Tool call: Checked the BLS CPI release schedule page for the August 2026 reference month."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["US core CPI-U month-over-month forecast for August 2026 first print","Framing and exact resolver: this is CPI-U U.S. city average, all items less food and energy, seasonally adjusted, percent change from the preceding month for August 2026. The ledger window is 2026-09-08 to 2026-09-16; the BLS CPI release calendar gives the concrete August 2026 CPI release date as September 11, 2026 at 08:30 ET, which is inside that window, so I use 2026-09-11 as the resolution date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.32, distribution present, forecast step count 1.","evidence":["Tool result: Fetched June 2026 details: all items less food and energy was 0.0; shelter rose 0.1; owners' equivalent rent rose 0.2; rent rose 0.1; lodging away from home fell 2.3; motor vehicle insurance fell 2.0; communication fell 1.5; apparel fell 0.6; used cars and trucks fell 0.2.","Prior/update/interval: persistence prior is the recent BLS Table A reference class, Dec. 2025-Jun. 2026 core monthly values [0.2, 0.3, 0.2, 0.2, 0.4, 0.2, 0.0], mean 0.214. No separate formal time-series model was used because the short same-variant official Table A persistence prior is transparent and directly matched to this first-print monthly-change target. Adjustment components: +0.04 for mean reversion after June's unusually soft 0.0 and several one-off category declines, -0.02 for shelter cooling to 0.1 and soft core goods, net point about 0.24. Interval method uses the sample dispersion of those fetched monthly change values: sigma = 0.12, so 1.28*sigma = 0.15. Applying a roughly symmetric 80% band around 0.24 gives 0.24 - 0.16 = 0.08 and 0.24 + 0.16 = 0.40."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Read the BLS June 2026 release narrative for component momentum.","Prior/update/interval: persistence prior is the recent BLS Table A reference class, Dec. 2025-Jun. 2026 core monthly values [0.2, 0.3, 0.2, 0.2, 0.4, 0.2, 0.0], mean 0.214. No separate formal time-series model was used because the short same-variant official Table A persistence prior is transparent and directly matched to this first-print monthly-change target. Adjustment components: +0.04 for mean reversion after June's unusually soft 0.0 and several one-off category declines, -0.02 for shelter cooling to 0.1 and soft core goods, net point about 0.24. Interval method uses the sample dispersion of those fetched monthly change values: sigma = 0.12, so 1.28*sigma = 0.15. Applying a roughly symmetric 80% band around 0.24 gives 0.24 - 0.16 = 0.08 and 0.24 + 0.16 = 0.40."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-considerations: upside risk is a rebound in motor vehicle insurance, lodging, communication, or tariff-sensitive core goods that would land above the interval if August core runs over 0.40. Downside risk is another month of shelter deceleration plus falling medical care, apparel, or used vehicles that would land below the interval if August core is under 0.08. An outside the interval outcome is most likely from broad services reacceleration or a second unusually weak one-off month."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["US core CPI-U month-over-month forecast for August 2026 first print","Prior/update/interval: persistence prior is the recent BLS Table A reference class, Dec. 2025-Jun. 2026 core monthly values [0.2, 0.3, 0.2, 0.2, 0.4, 0.2, 0.0], mean 0.214. No separate formal time-series model was used because the short same-variant official Table A persistence prior is transparent and directly matched to this first-print monthly-change target. Adjustment components: +0.04 for mean reversion after June's unusually soft 0.0 and several one-off category declines, -0.02 for shelter cooling to 0.1 and soft core goods, net point about 0.24. Interval method uses the sample dispersion of those fetched monthly change values: sigma = 0.12, so 1.28*sigma = 0.15. Applying a roughly symmetric 80% band around 0.24 gives 0.24 - 0.16 = 0.08 and 0.24 + 0.16 = 0.40."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-core-cpi-mom-august-2026\nrunLabel: Headline\nresolutionDate: 2026-09-11\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-real-avg-hourly-earnings-mom-august-2026.2026-08-11T13-08-57Z.285af2fa1f4570d5","runId":"run.us-real-avg-hourly-earnings-mom-august-2026.2026-08-11T13-08-57Z.285af2fa1f4570d5","predictionId":"us-real-avg-hourly-earnings-mom-august-2026","specId":"spec.us-real-avg-hourly-earnings-mom-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Resolver is the all-employees, private nonfarm payrolls, seasonally adjusted variant in BLS Real Earnings Table A-1. The target is the first-print over-the-month percent change for August 2026, not later revised CES or CPI database values.","Base rate/reference class: the selected recent official real-hourly-earnings MoM sample is centered near zero, with a mean around -0.03 percent and median -0.10 percent. Because this is already a change series, the sample values themselves are the realized dispersion input."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 9 source-context item(s), activity log present.","evidence":["Forecast for BLS real average hourly earnings MoM, August 2026","Resolver is the all-employees, private nonfarm payrolls, seasonally adjusted variant in BLS Real Earnings Table A-1. The target is the first-print over-the-month percent change for August 2026, not later revised CES or CPI database values."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Resolver is the all-employees, private nonfarm payrolls, seasonally adjusted variant in BLS Real Earnings Table A-1. The target is the first-print over-the-month percent change for August 2026, not later revised CES or CPI database values.","Tool call: BLS Real Earnings release schedule lookup for August 2026 reference month"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence/reference-class prior is the selected recent BLS Table A-1 monthly real average hourly earnings change sample [0.2, -0.1, -0.1, -0.3, 0.3, 0.2, -0.6, -0.5, -0.2, 0.8], mean = -0.03 and median = -0.10. Update components: July nominal AHE was only +2 cents to 37.62, suggesting softer wage momentum; for August I assume nominal AHE about +0.25 percent and CPI-U about +0.30 percent, so real hourly earnings is approximately 0.25 - 0.30 = -0.05 percent, rounded to -0.1. The point remains anchored near the prior median, so the wage/CPI inside-view adjustment is directional but not a large move. Sample dispersion gives sigma = 0.42 percentage points, and 1.28*sigma = 0.54 percentage points; applying that to -0.1 gives about -0.64 to 0.44, rounded to an 80 percent interval of -0.6 to 0.4.","Upside risk is a soft August CPI print or a rebound in hourly earnings after July's +2 cents, which would land above the interval if real hourly earnings rose more than 0.4 percent. Downside risk is another hot CPI print or weak mix-adjusted wages, which would land below the interval if the published real change is less than -0.6 percent. Outside the interval would most likely require an energy-driven CPI surprise or a large composition shock in payroll earnings."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate/reference class: the selected recent official real-hourly-earnings MoM sample is centered near zero, with a mean around -0.03 percent and median -0.10 percent. Because this is already a change series, the sample values themselves are the realized dispersion input.","Prior/update/interval: persistence/reference-class prior is the selected recent BLS Table A-1 monthly real average hourly earnings change sample [0.2, -0.1, -0.1, -0.3, 0.3, 0.2, -0.6, -0.5, -0.2, 0.8], mean = -0.03 and median = -0.10. Update components: July nominal AHE was only +2 cents to 37.62, suggesting softer wage momentum; for August I assume nominal AHE about +0.25 percent and CPI-U about +0.30 percent, so real hourly earnings is approximately 0.25 - 0.30 = -0.05 percent, rounded to -0.1. The point remains anchored near the prior median, so the wage/CPI inside-view adjustment is directional but not a large move. Sample dispersion gives sigma = 0.42 percentage points, and 1.28*sigma = 0.54 percentage points; applying that to -0.1 gives about -0.64 to 0.44, rounded to an 80 percent interval of -0.6 to 0.4."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence/reference-class prior is the selected recent BLS Table A-1 monthly real average hourly earnings change sample [0.2, -0.1, -0.1, -0.3, 0.3, 0.2, -0.6, -0.5, -0.2, 0.8], mean = -0.03 and median = -0.10. Update components: July nominal AHE was only +2 cents to 37.62, suggesting softer wage momentum; for August I assume nominal AHE about +0.25 percent and CPI-U about +0.30 percent, so real hourly earnings is approximately 0.25 - 0.30 = -0.05 percent, rounded to -0.1. The point remains anchored near the prior median, so the wage/CPI inside-view adjustment is directional but not a large move. Sample dispersion gives sigma = 0.42 percentage points, and 1.28*sigma = 0.54 percentage points; applying that to -0.1 gives about -0.64 to 0.44, rounded to an 80 percent interval of -0.6 to 0.4.","Upside risk is a soft August CPI print or a rebound in hourly earnings after July's +2 cents, which would land above the interval if real hourly earnings rose more than 0.4 percent. Downside risk is another hot CPI print or weak mix-adjusted wages, which would land below the interval if the published real change is less than -0.6 percent. Outside the interval would most likely require an energy-driven CPI surprise or a large composition shock in payroll earnings."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for BLS real average hourly earnings MoM, August 2026","Prior/update/interval: persistence/reference-class prior is the selected recent BLS Table A-1 monthly real average hourly earnings change sample [0.2, -0.1, -0.1, -0.3, 0.3, 0.2, -0.6, -0.5, -0.2, 0.8], mean = -0.03 and median = -0.10. Update components: July nominal AHE was only +2 cents to 37.62, suggesting softer wage momentum; for August I assume nominal AHE about +0.25 percent and CPI-U about +0.30 percent, so real hourly earnings is approximately 0.25 - 0.30 = -0.05 percent, rounded to -0.1. The point remains anchored near the prior median, so the wage/CPI inside-view adjustment is directional but not a large move. Sample dispersion gives sigma = 0.42 percentage points, and 1.28*sigma = 0.54 percentage points; applying that to -0.1 gives about -0.64 to 0.44, rounded to an 80 percent interval of -0.6 to 0.4."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-real-avg-hourly-earnings-mom-august-2026\nrunLabel: Headline\nresolutionDate: 2026-09-11\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-mts-deficit-august-2026.2026-08-11T13-17-20Z.f218c2ff920c1c86","runId":"run.us-mts-deficit-august-2026.2026-08-11T13-17-20Z.f218c2ff920c1c86","predictionId":"us-mts-deficit-august-2026","specId":"spec.us-mts-deficit-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool call: Checked official/public FY2026 current-budget context from CBO Monthly Budget Review for June 2026 and congressional fiscal update based on Treasury data.","Tool result: Fetched CBO estimate that the FY2026 deficit through June was 1.4 trillion, 35 billion more than the same FY2025 period, and JEC/Treasury-based June 2026 monthly deficit of 120.305 billion with FY2026-to-date deficit of 1.367 trillion."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 9 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this forecast targets the U.S. Treasury Bureau of the Fiscal Service Monthly Treasury Statement Table 1 first print for August 2026, using the monthly Total Surplus (+) or Deficit (-) line and expressing deficits as positive USD billions while the official line is surplus-positive and deficit-negative. The specific FiscalData summary URL is the resolving Table 1 under the registered Monthly Treasury Statement dataset URL, and the registered expectedReleaseWindow is 2026-09-13 to 2026-09-21.","Tool result: Fetched August 2025 receipts 344,315 million, outlays 689,107 million, and Total Surplus (+) or Deficit (-) -344,792 million; deficit-positive value is 344.792 USD billions."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this forecast targets the U.S. Treasury Bureau of the Fiscal Service Monthly Treasury Statement Table 1 first print for August 2026, using the monthly Total Surplus (+) or Deficit (-) line and expressing deficits as positive USD billions while the official line is surplus-positive and deficit-negative. The specific FiscalData summary URL is the resolving Table 1 under the registered Monthly Treasury Statement dataset URL, and the registered expectedReleaseWindow is 2026-09-13 to 2026-09-21.","Reference class and base rate: recent August MTS monthly deficits are the best base rate because August has no major tax due dates and strong calendar-payment effects. The last five August first prints are 170.635, 219.596, -89.256, 380.080, and 344.792 USD billions, averaging about 205.2 billion before calendar and FY2026 adjustments."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 430, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is the recent-August reference class mean 205.2 from 2021-2025 first-print August deficits; adjustment components are judgmental shrinkage adjustments anchored to the fetched record and current fiscal run rate: +45 for higher FY2026 outlay/net-interest levels versus the lower 2021-2022 Augusts, -35 for no September-payment acceleration into August relative to the high 2024-2025 prints, and +15 for nominal scale plus FY2026 deficit running about 35 billion above FY2025 through June, giving about 230. The interval method uses realized dispersion of the same August flow values despite the small sample because August deficits are dominated by volatile payment-timing effects; sigma = 166.3 USD billions; 1.28*sigma = 212.9, rounded to an about 215 billion half-width, so the wide interval is retained even after the 2026 calendar adjustment: 230 +/- 215 implies an 80% interval of 15 to 445 USD billions.","Counter-consideration: upside risk is a larger deficit if late-August benefit, defense, or interest payments bunch into the month or receipts are weaker than recent August patterns, which would land above the interval if the deficit exceeds 445 billion. Downside risk is another 2023-like outlay suppression, accounting shift, or unusually strong receipts month; a surplus or deficit below 15 billion would land outside the interval on the low side."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Reference class and base rate: recent August MTS monthly deficits are the best base rate because August has no major tax due dates and strong calendar-payment effects. The last five August first prints are 170.635, 219.596, -89.256, 380.080, and 344.792 USD billions, averaging about 205.2 billion before calendar and FY2026 adjustments.","Calendar and mechanism update: August 2024 and 2025 were unusually high because September 1 payments were accelerated into August when September 1 was nonbusiness or a holiday; September 1, 2026 is a Tuesday, so that boost should be absent. August 1, 2026 is a Saturday, so some normal first-of-month payments shift into July, pulling August down. Higher interest and general outlay levels versus 2021-2022 pull the estimate back upward, while elevated receipts/tariff collections limit the deficit."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-consideration: upside risk is a larger deficit if late-August benefit, defense, or interest payments bunch into the month or receipts are weaker than recent August patterns, which would land above the interval if the deficit exceeds 445 billion. Downside risk is another 2023-like outlay suppression, accounting shift, or unusually strong receipts month; a surplus or deficit below 15 billion would land outside the interval on the low side."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["US Monthly Treasury Statement August 2026 Deficit Forecast","Framing and exact resolver: this forecast targets the U.S. Treasury Bureau of the Fiscal Service Monthly Treasury Statement Table 1 first print for August 2026, using the monthly Total Surplus (+) or Deficit (-) line and expressing deficits as positive USD billions while the official line is surplus-positive and deficit-negative. The specific FiscalData summary URL is the resolving Table 1 under the registered Monthly Treasury Statement dataset URL, and the registered expectedReleaseWindow is 2026-09-13 to 2026-09-21."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-mts-deficit-august-2026\nrunLabel: Headline\nresolutionDate: 2026-09-21\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.jolts-quits-rate-august-2026.2026-08-11T13-05-53Z.10b75f9e771a1e0a","runId":"run.jolts-quits-rate-august-2026.2026-08-11T13-05-53Z.10b75f9e771a1e0a","predictionId":"jolts-quits-rate-august-2026","specId":"spec.jolts-quits-rate-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: for a low-volatility rate series like Total nonfarm quits, the strongest base rate is persistence around the latest official BLS Table 4 level. The recent official reference class averages about 2.0 percent across June 2025 and March-June 2026, with the sequential 2026 observations centered just under 2.0.","Prior/update/interval: persistence model prior = latest official June 2026 rate of 2.0 percent, historical sample = BLS Table 4 seasonally adjusted Total rates for March-June 2026 of 2.0, 1.9, 2.0, 2.0; adjustment components = -0.05 for weaker July payrolls and downward revisions, -0.02 for lower participation/worker-confidence pressure, +0.02 for still-stable JOLTS openings and hires, rounded to a -0.1 point net forecast adjustment over July-August; interval method = sample sigma of monthly changes from March-June changes (-0.1, +0.1, 0.0) is sigma = 0.10 for one month, two-month sigma = sqrt(2)*0.10 = 0.14, 80 percent half-width = 1.28*0.14 = 0.18, rounded to 0.2; final implied bounds are 1.9 - 0.2 = 1.7 and 1.9 + 0.2 = 2.1."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Forecast for BLS JOLTS quits rate, August 2026 first print","Framing and exact resolver: this is BLS JOLTS Table 4, seasonally adjusted Total nonfarm quits rate, series JTSQUR in FRED mirror terms, for August 2026. The resolver is the BLS first print on the Table 4 release page, not FRED, not Total private, and not the not-seasonally-adjusted Table 11 variant."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast for BLS JOLTS quits rate, August 2026 first print","Framing and exact resolver: this is BLS JOLTS Table 4, seasonally adjusted Total nonfarm quits rate, series JTSQUR in FRED mirror terms, for August 2026. The resolver is the BLS first print on the Table 4 release page, not FRED, not Total private, and not the not-seasonally-adjusted Table 11 variant."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.4, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence model prior = latest official June 2026 rate of 2.0 percent, historical sample = BLS Table 4 seasonally adjusted Total rates for March-June 2026 of 2.0, 1.9, 2.0, 2.0; adjustment components = -0.05 for weaker July payrolls and downward revisions, -0.02 for lower participation/worker-confidence pressure, +0.02 for still-stable JOLTS openings and hires, rounded to a -0.1 point net forecast adjustment over July-August; interval method = sample sigma of monthly changes from March-June changes (-0.1, +0.1, 0.0) is sigma = 0.10 for one month, two-month sigma = sqrt(2)*0.10 = 0.14, 80 percent half-width = 1.28*0.14 = 0.18, rounded to 0.2; final implied bounds are 1.9 - 0.2 = 1.7 and 1.9 + 0.2 = 2.1.","Counter-considerations: upside risk would come from a July or August rebound in labor demand that lifts quits back above 2.1, especially in leisure, retail, or professional services. Downside risk would come from a clearer labor-market break after the -23,000 July payroll print; a broad pullback in voluntary separations would land below the interval if the first-print rate is under 1.7."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence model prior = latest official June 2026 rate of 2.0 percent, historical sample = BLS Table 4 seasonally adjusted Total rates for March-June 2026 of 2.0, 1.9, 2.0, 2.0; adjustment components = -0.05 for weaker July payrolls and downward revisions, -0.02 for lower participation/worker-confidence pressure, +0.02 for still-stable JOLTS openings and hires, rounded to a -0.1 point net forecast adjustment over July-August; interval method = sample sigma of monthly changes from March-June changes (-0.1, +0.1, 0.0) is sigma = 0.10 for one month, two-month sigma = sqrt(2)*0.10 = 0.14, 80 percent half-width = 1.28*0.14 = 0.18, rounded to 0.2; final implied bounds are 1.9 - 0.2 = 1.7 and 1.9 + 0.2 = 2.1.","Review disposition: accepted the optional resolver-clarity suggestion by stating that the verified Sep. 29, 2026 release date falls within the registered Sep. 27-Oct. 5, 2026 expected window; kept the small rounded -0.1 inside-view adjustment because it remains directionally grounded and internally coherent."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-considerations: upside risk would come from a July or August rebound in labor demand that lifts quits back above 2.1, especially in leisure, retail, or professional services. Downside risk would come from a clearer labor-market break after the -23,000 July payroll print; a broad pullback in voluntary separations would land below the interval if the first-print rate is under 1.7."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for BLS JOLTS quits rate, August 2026 first print","Prior/update/interval: persistence model prior = latest official June 2026 rate of 2.0 percent, historical sample = BLS Table 4 seasonally adjusted Total rates for March-June 2026 of 2.0, 1.9, 2.0, 2.0; adjustment components = -0.05 for weaker July payrolls and downward revisions, -0.02 for lower participation/worker-confidence pressure, +0.02 for still-stable JOLTS openings and hires, rounded to a -0.1 point net forecast adjustment over July-August; interval method = sample sigma of monthly changes from March-June changes (-0.1, +0.1, 0.0) is sigma = 0.10 for one month, two-month sigma = sqrt(2)*0.10 = 0.14, 80 percent half-width = 1.28*0.14 = 0.18, rounded to 0.2; final implied bounds are 1.9 - 0.2 = 1.7 and 1.9 + 0.2 = 2.1."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: jolts-quits-rate-august-2026\nrunLabel: Headline\nresolutionDate: 2026-09-29\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-core-pce-mom-august-2026.2026-08-11T13-13-19Z.1646b5aa18373261","runId":"run.us-core-pce-mom-august-2026.2026-08-11T13-13-19Z.1646b5aa18373261","predictionId":"us-core-pce-mom-august-2026","specId":"spec.us-core-pce-mom-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["The target is the BEA PCE price index excluding food and energy, seasonally adjusted, percent change from the preceding month, for August 2026. All historical anchors below use that same core PCE MoM SA variant, not headline PCE, CPI, market-based PCE, year-over-year inflation, or later revised vintages.","Reference class/base rate: the Jan-Jun 2026 official first-print core PCE MoM SA sample has values 0.4, 0.4, 0.3, 0.3, 0.3, and 0.1, with a mean base rate of 0.30 percent growth. The latest June print is below that base rate, but a two-month-ahead August forecast should not fully chase one soft month."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 9 source-context item(s), activity log present.","evidence":["Tool call: Checked the BLS June 2026 CPI release for contemporaneous price momentum relevant to PCE source data.","Tool result: BLS fetched June 2026 values: CPI-U all items -0.4 month-over-month, all items less food and energy 0.0, shelter 0.1, owners' equivalent rent 0.2, energy -5.7, and 12-month core CPI 2.6."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Tool call: Checked the BEA full release schedule and BEA 26-34 schedule node for the August 2026 Personal Income and Outlays release.","Tool result: BEA schedule fetched: Personal Income and Outlays, August 2026 is scheduled for September 30, 2026 at 8:30 AM; the preceding July 2026 PIO release is scheduled for August 26, 2026 at 8:30 AM."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.28, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is the Jan-Jun 2026 BEA first-print mean of 0.30 from the historical sample 0.4, 0.4, 0.3, 0.3, 0.3, 0.1; adjustment components are -0.02 for June core CPI at 0.0 and soft shelter at 0.1, -0.02 for latest BEA core PCE momentum at 0.1, and +0.01 for sticky services and two-month mean reversion, giving 0.30 - 0.02 - 0.02 + 0.01 = 0.27. Interval method uses realized dispersion of the fetched core PCE MoM values themselves: sample sigma = 0.11 percentage point, so 1.28*sigma = 0.14; final 80% bounds are 0.27 - 0.14 = 0.13 and 0.27 + 0.14 = 0.41. This sigma estimate is fragile because it uses only six one-decimal first-print observations.","Upside risk is that July and August services prices rebound after June's flat CPI core reading, pushing core PCE to 0.4 or higher; downside risk is another month of weak medical, apparel, vehicles, or communication prices plus soft shelter, which would land below the interval near 0.1 or less. An outside the interval high outcome would likely require broad services acceleration rather than energy, because food and energy are excluded."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Checked the BLS June 2026 CPI release for contemporaneous price momentum relevant to PCE source data.","Tool call: Checked BEA's 2026 annual update notice because the August 2026 first print is scheduled on the same day as the annual update."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Reference class/base rate: the Jan-Jun 2026 official first-print core PCE MoM SA sample has values 0.4, 0.4, 0.3, 0.3, 0.3, and 0.1, with a mean base rate of 0.30 percent growth. The latest June print is below that base rate, but a two-month-ahead August forecast should not fully chase one soft month.","Upside risk is that July and August services prices rebound after June's flat CPI core reading, pushing core PCE to 0.4 or higher; downside risk is another month of weak medical, apparel, vehicles, or communication prices plus soft shelter, which would land below the interval near 0.1 or less. An outside the interval high outcome would likely require broad services acceleration rather than energy, because food and energy are excluded."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["US core PCE month-over-month forecast for August 2026","Reference class/base rate: the Jan-Jun 2026 official first-print core PCE MoM SA sample has values 0.4, 0.4, 0.3, 0.3, 0.3, and 0.1, with a mean base rate of 0.30 percent growth. The latest June print is below that base rate, but a two-month-ahead August forecast should not fully chase one soft month."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-core-pce-mom-august-2026\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.jolts-openings-august-2026.2026-08-11T13-04-08Z.d90651894c1a4910","runId":"run.jolts-openings-august-2026.2026-08-11T13-04-08Z.d90651894c1a4910","predictionId":"jolts-openings-august-2026","specId":"spec.jolts-openings-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: for a two-month-ahead forecast of a level series, the strongest outside-view prior is persistence around the latest official JOLTS level. The recent official reference class is January-June 2026 total job openings around 6.9-7.6 million, with a current value of 7.359 million and no evidence of a large layoff shock.","Prior/update/interval: persistence prior starts at June 2026 current-vintage 7.359 million. Updates are -0.18 million for the June down move continuing, -0.12 million for weak July payrolls and downward revisions, +0.04 million because openings are noisy and layoffs remain contained, giving 7.359 - 0.18 - 0.12 + 0.04 = 7.099, rounded to 7.10 million. Historical sample uses successive changes in current/official 2026 levels: Jan 7.240, Feb 6.882, Mar 6.887, Apr 7.585, May 7.537, Jun 7.359 million, so changes are -0.358, +0.005, +0.698, -0.048, -0.178 and sigma = 0.40 million. The one-month 80% half-width is 1.28*sigma = 1.28*0.40 = 0.51 million; I widen to 0.65 million for the two-month horizon to August because one additional unobserved month and first-print volatility add risk, giving 7.10 +/- 0.65 = [6.45, 7.75]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["Resolver framing: this is BLS JOLTS seasonally adjusted Total job openings, levels in thousands converted to millions. The official BLS JOLTS release schedule fetched this run lists August 2026 for September 29, 2026 at 10:00 AM, while the registered ledger target supplied here binds the cell to the window end 2026-10-05 and source URL https://www.bls.gov/news.release/jolts.nr0.htm; I preserve the registered target fields and state the calendar discrepancy explicitly.","Tool call: BLS JOLTS release schedule lookup for reference month August 2026"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Resolver framing: this is BLS JOLTS seasonally adjusted Total job openings, levels in thousands converted to millions. The official BLS JOLTS release schedule fetched this run lists August 2026 for September 29, 2026 at 10:00 AM, while the registered ledger target supplied here binds the cell to the window end 2026-10-05 and source URL https://www.bls.gov/news.release/jolts.nr0.htm; I preserve the registered target fields and state the calendar discrepancy explicitly.","Tool call: BLS JOLTS release schedule lookup for reference month August 2026"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.3, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior starts at June 2026 current-vintage 7.359 million. Updates are -0.18 million for the June down move continuing, -0.12 million for weak July payrolls and downward revisions, +0.04 million because openings are noisy and layoffs remain contained, giving 7.359 - 0.18 - 0.12 + 0.04 = 7.099, rounded to 7.10 million. Historical sample uses successive changes in current/official 2026 levels: Jan 7.240, Feb 6.882, Mar 6.887, Apr 7.585, May 7.537, Jun 7.359 million, so changes are -0.358, +0.005, +0.698, -0.048, -0.178 and sigma = 0.40 million. The one-month 80% half-width is 1.28*sigma = 1.28*0.40 = 0.51 million; I widen to 0.65 million for the two-month horizon to August because one additional unobserved month and first-print volatility add risk, giving 7.10 +/- 0.65 = [6.45, 7.75].","Upside risk: a rebound in professional services, retail, or transportation postings after June's drop would land above the interval if openings print above 7.75 million. Downside risk: the July payroll contraction and weak revisions could mark a sharper employer retrenchment, and an August openings fall below 6.45 million would land outside the interval on the low side."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior starts at June 2026 current-vintage 7.359 million. Updates are -0.18 million for the June down move continuing, -0.12 million for weak July payrolls and downward revisions, +0.04 million because openings are noisy and layoffs remain contained, giving 7.359 - 0.18 - 0.12 + 0.04 = 7.099, rounded to 7.10 million. Historical sample uses successive changes in current/official 2026 levels: Jan 7.240, Feb 6.882, Mar 6.887, Apr 7.585, May 7.537, Jun 7.359 million, so changes are -0.358, +0.005, +0.698, -0.048, -0.178 and sigma = 0.40 million. The one-month 80% half-width is 1.28*sigma = 1.28*0.40 = 0.51 million; I widen to 0.65 million for the two-month horizon to August because one additional unobserved month and first-print volatility add risk, giving 7.10 +/- 0.65 = [6.45, 7.75].","Review disposition: accepted the blocking resolver critique by using the registered target contract's resolutionDate/window end and source URL while explicitly noting the official BLS calendar date discrepancy; retained the point forecast and interval because the critique did not identify an evidence or calibration error."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence prior starts at June 2026 current-vintage 7.359 million. Updates are -0.18 million for the June down move continuing, -0.12 million for weak July payrolls and downward revisions, +0.04 million because openings are noisy and layoffs remain contained, giving 7.359 - 0.18 - 0.12 + 0.04 = 7.099, rounded to 7.10 million. Historical sample uses successive changes in current/official 2026 levels: Jan 7.240, Feb 6.882, Mar 6.887, Apr 7.585, May 7.537, Jun 7.359 million, so changes are -0.358, +0.005, +0.698, -0.048, -0.178 and sigma = 0.40 million. The one-month 80% half-width is 1.28*sigma = 1.28*0.40 = 0.51 million; I widen to 0.65 million for the two-month horizon to August because one additional unobserved month and first-print volatility add risk, giving 7.10 +/- 0.65 = [6.45, 7.75].","Upside risk: a rebound in professional services, retail, or transportation postings after June's drop would land above the interval if openings print above 7.75 million. Downside risk: the July payroll contraction and weak revisions could mark a sharper employer retrenchment, and an August openings fall below 6.45 million would land outside the interval on the low side."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Base rate/reference class: for a two-month-ahead forecast of a level series, the strongest outside-view prior is persistence around the latest official JOLTS level. The recent official reference class is January-June 2026 total job openings around 6.9-7.6 million, with a current value of 7.359 million and no evidence of a large layoff shock.","Prior/update/interval: persistence prior starts at June 2026 current-vintage 7.359 million. Updates are -0.18 million for the June down move continuing, -0.12 million for weak July payrolls and downward revisions, +0.04 million because openings are noisy and layoffs remain contained, giving 7.359 - 0.18 - 0.12 + 0.04 = 7.099, rounded to 7.10 million. Historical sample uses successive changes in current/official 2026 levels: Jan 7.240, Feb 6.882, Mar 6.887, Apr 7.585, May 7.537, Jun 7.359 million, so changes are -0.358, +0.005, +0.698, -0.048, -0.178 and sigma = 0.40 million. The one-month 80% half-width is 1.28*sigma = 1.28*0.40 = 0.51 million; I widen to 0.65 million for the two-month horizon to August because one additional unobserved month and first-print volatility add risk, giving 7.10 +/- 0.65 = [6.45, 7.75]."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: jolts-openings-august-2026\nrunLabel: Headline\nresolutionDate: 2026-10-05\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.wic-participation-august-2026.2026-08-11T13-22-29Z.dab44b219e44a91b","runId":"run.wic-participation-august-2026.2026-08-11T13-22-29Z.dab44b219e44a91b","predictionId":"wic-participation-august-2026","specId":"spec.wic-participation-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: for a monthly level series like WIC total participation, the base rate is persistence in the same USDA FNS WIC table plus recent monthly-change dispersion. The updated ERS FY 2025 average of about 6.9 million is higher than the Apr 2025 first print, so I move the prior modestly upward from the draft rather than holding only the April 2025 level.","Prior/update/interval: persistence prior starts from the official FY 2025 rounded average of about 6.9 million and the Apr 2025 first print of 6.856889 million; seasonal update uses the Apr-to-Aug 2024 gain of 6.830287 - 6.722042 = 0.108245 million, but the FY 2025 average already captures later-2025 strength, so I add only about 0.08 million to the April anchor and subtract about 0.01 million for slower birth/caseload normalization, giving point 6.99 million. For the interval, the same-series monthly-change sample from Nov 2023 through Apr 2025 has typical changes around 0.05 million; sigma = 0.049 million. A one-month 80% half-width is 1.28*sigma = 0.063 million; I widen to 0.16 million, about 2.5x, because the target is a first print more than a year beyond the last exact monthly total captured in the draft while newer official context is rounded, yielding 6.83 to 7.15 million."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this is the USDA FNS WIC total participation series for August 2026, first print only, not seasonally adjusted. The target uses the national total in the WIC monthly participation table and is expressed in millions of participants.","Tool result: The official FNS release-calendar window for this August 2026 WIC target is 2026-11-18 to 2026-11-26; the ledger target sets the bound resolution date to 2026-11-26."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this is the USDA FNS WIC total participation series for August 2026, first print only, not seasonally adjusted. The target uses the national total in the WIC monthly participation table and is expressed in millions of participants.","Tool call: Checked the FNS release calendar and registered WIC source window for the first-print date basis."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.32, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior starts from the official FY 2025 rounded average of about 6.9 million and the Apr 2025 first print of 6.856889 million; seasonal update uses the Apr-to-Aug 2024 gain of 6.830287 - 6.722042 = 0.108245 million, but the FY 2025 average already captures later-2025 strength, so I add only about 0.08 million to the April anchor and subtract about 0.01 million for slower birth/caseload normalization, giving point 6.99 million. For the interval, the same-series monthly-change sample from Nov 2023 through Apr 2025 has typical changes around 0.05 million; sigma = 0.049 million. A one-month 80% half-width is 1.28*sigma = 0.063 million; I widen to 0.16 million, about 2.5x, because the target is a first print more than a year beyond the last exact monthly total captured in the draft while newer official context is rounded, yielding 6.83 to 7.15 million.","Counter-consideration: upside risk would come from continued FY 2025-style growth, stronger outreach, or higher eligibility take-up lifting August 2026 above about 7.15 million. Downside risk would come from funding disruption, administrative churn, or a sharper decline in the infant and young-child eligible population pushing the first print below 6.83 million. Outside the interval would require a miss of roughly 0.16 million from the persistence-plus-seasonality path."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior starts from the official FY 2025 rounded average of about 6.9 million and the Apr 2025 first print of 6.856889 million; seasonal update uses the Apr-to-Aug 2024 gain of 6.830287 - 6.722042 = 0.108245 million, but the FY 2025 average already captures later-2025 strength, so I add only about 0.08 million to the April anchor and subtract about 0.01 million for slower birth/caseload normalization, giving point 6.99 million. For the interval, the same-series monthly-change sample from Nov 2023 through Apr 2025 has typical changes around 0.05 million; sigma = 0.049 million. A one-month 80% half-width is 1.28*sigma = 0.063 million; I widen to 0.16 million, about 2.5x, because the target is a first print more than a year beyond the last exact monthly total captured in the draft while newer official context is rounded, yielding 6.83 to 7.15 million.","Review disposition: accepted the critique to refresh public context and moved the prior from an April 2025-only anchor toward the newer official FY 2025 average and July 2026 program-data availability; accepted the interval critique by using a longer same-series monthly-change sample and a wider horizon adjustment; kept the resolver, unit conversion, dataPointId, and 2026-11-26 bound date because they match the ledger contract."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence prior starts from the official FY 2025 rounded average of about 6.9 million and the Apr 2025 first print of 6.856889 million; seasonal update uses the Apr-to-Aug 2024 gain of 6.830287 - 6.722042 = 0.108245 million, but the FY 2025 average already captures later-2025 strength, so I add only about 0.08 million to the April anchor and subtract about 0.01 million for slower birth/caseload normalization, giving point 6.99 million. For the interval, the same-series monthly-change sample from Nov 2023 through Apr 2025 has typical changes around 0.05 million; sigma = 0.049 million. A one-month 80% half-width is 1.28*sigma = 0.063 million; I widen to 0.16 million, about 2.5x, because the target is a first print more than a year beyond the last exact monthly total captured in the draft while newer official context is rounded, yielding 6.83 to 7.15 million.","Counter-consideration: upside risk would come from continued FY 2025-style growth, stronger outreach, or higher eligibility take-up lifting August 2026 above about 7.15 million. Downside risk would come from funding disruption, administrative churn, or a sharper decline in the infant and young-child eligible population pushing the first print below 6.83 million. Outside the interval would require a miss of roughly 0.16 million from the persistence-plus-seasonality path."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for August 2026 WIC total participation","Prior/update/interval: persistence prior starts from the official FY 2025 rounded average of about 6.9 million and the Apr 2025 first print of 6.856889 million; seasonal update uses the Apr-to-Aug 2024 gain of 6.830287 - 6.722042 = 0.108245 million, but the FY 2025 average already captures later-2025 strength, so I add only about 0.08 million to the April anchor and subtract about 0.01 million for slower birth/caseload normalization, giving point 6.99 million. For the interval, the same-series monthly-change sample from Nov 2023 through Apr 2025 has typical changes around 0.05 million; sigma = 0.049 million. A one-month 80% half-width is 1.28*sigma = 0.063 million; I widen to 0.16 million, about 2.5x, because the target is a first print more than a year beyond the last exact monthly total captured in the draft while newer official context is rounded, yielding 6.83 to 7.15 million."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: wic-participation-august-2026\nrunLabel: Headline\nresolutionDate: 2026-11-26\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-participation-august-2026.2026-08-11T13-24-58Z.3b0f27c9c9579711","runId":"run.snap-participation-august-2026.2026-08-11T13-24-58Z.3b0f27c9c9579711","predictionId":"snap-participation-august-2026","specId":"spec.snap-participation-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Reference class/base rate: for an official-source level series with monthly administrative reporting, I start from persistence plus recent monthly change, not from the long pandemic/disaster period. The cleanest recent reference class is FY 2025 through FY 2026 national monthly Persons, with special caution that FY 2023 included unusually high and volatile values such as Aug 2023 = 53.518725 million.","Prior/update/interval: persistence prior = Apr 2026 official Persons of 37.011096 million; historical sample = recent official monthly changes from Sep 2025 through Apr 2026; adjustment components = -0.25 million/month underlying caseload normalization, no separate quantified policy/friction drag, and no positive August seasonal offset because 2025 Apr-to-Aug was -0.515774 million. Point = 37.011096 + 4*(-0.25) = 36.011096, rounded to 36.01. Monthly change dispersion from the seven fetched changes is about 0.249 million; four-month propagated sigma = sqrt(4)*0.249 = 0.498 million, widened for policy uncertainty to sigma = 0.574 million; 1.28*sigma = 0.735 million, giving 36.011096 +/- 0.735 = [35.28, 36.75]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: the target is the USDA FNS national SNAP monthly table, Participation Persons, for August 2026, first print, converted to millions. The registered contract sets a resolve-by-bound resolution date of 2027-01-11 within the expected 2027-01-03 to 2027-01-11 release window; the USDA FNS data page itself showed the monthly table and latest-data timestamp but I did not find a separate date-specific public release calendar page in this run.","Tool call: Opened the USDA FNS national SNAP monthly PDF table for FY 2023 through FY 2026 and read recent Persons values."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: the target is the USDA FNS national SNAP monthly table, Participation Persons, for August 2026, first print, converted to millions. The registered contract sets a resolve-by-bound resolution date of 2027-01-11 within the expected 2027-01-03 to 2027-01-11 release window; the USDA FNS data page itself showed the monthly table and latest-data timestamp but I did not find a separate date-specific public release calendar page in this run.","Counter-consideration: upside risk is a faster-than-expected halt in recertification losses or disaster-assistance additions, which would land above the interval if August participation stays above 36.75 million. Downside risk is broader eligibility/work-rule implementation or administrative churn, which would land below the interval if August participation falls below 35.28 million. A major reporting reclassification would also be outside the interval but should still resolve on the same first-print Persons field."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.47, distribution present, forecast step count 1.","evidence":["Policy and one-off effects: FY 2026 eligibility and allotment settings are already in force for August 2026, so I do not add a mechanical October COLA break. Because the draft did not anchor a specific public work-rule source with numbers, I treat additional policy or administrative friction as downside risk around the forecast rather than a quantified central drag.","Prior/update/interval: persistence prior = Apr 2026 official Persons of 37.011096 million; historical sample = recent official monthly changes from Sep 2025 through Apr 2026; adjustment components = -0.25 million/month underlying caseload normalization, no separate quantified policy/friction drag, and no positive August seasonal offset because 2025 Apr-to-Aug was -0.515774 million. Point = 37.011096 + 4*(-0.25) = 36.011096, rounded to 36.01. Monthly change dispersion from the seven fetched changes is about 0.249 million; four-month propagated sigma = sqrt(4)*0.249 = 0.498 million, widened for policy uncertainty to sigma = 0.574 million; 1.28*sigma = 0.735 million, giving 36.011096 +/- 0.735 = [35.28, 36.75]."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level and momentum: Apr 2026 was 37.011096 million. Recent sequential changes from the current FNS table for Sep 2025 through Apr 2026 were -0.540454, -1.096770, -0.791992, -0.731547, -0.600518, -0.437785, and -0.426952 million, so the decline was still large but easing by March-April.","Policy and one-off effects: FY 2026 eligibility and allotment settings are already in force for August 2026, so I do not add a mechanical October COLA break. Because the draft did not anchor a specific public work-rule source with numbers, I treat additional policy or administrative friction as downside risk around the forecast rather than a quantified central drag."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Framing and exact resolver: the target is the USDA FNS national SNAP monthly table, Participation Persons, for August 2026, first print, converted to millions. The registered contract sets a resolve-by-bound resolution date of 2027-01-11 within the expected 2027-01-03 to 2027-01-11 release window; the USDA FNS data page itself showed the monthly table and latest-data timestamp but I did not find a separate date-specific public release calendar page in this run.","Level and momentum: Apr 2026 was 37.011096 million. Recent sequential changes from the current FNS table for Sep 2025 through Apr 2026 were -0.540454, -1.096770, -0.791992, -0.731547, -0.600518, -0.437785, and -0.426952 million, so the decline was still large but easing by March-April."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["SNAP national participation forecast for August 2026","Policy and one-off effects: FY 2026 eligibility and allotment settings are already in force for August 2026, so I do not add a mechanical October COLA break. Because the draft did not anchor a specific public work-rule source with numbers, I treat additional policy or administrative friction as downside risk around the forecast rather than a quantified central drag."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-participation-august-2026\nrunLabel: Headline\nresolutionDate: 2027-01-11\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.sba-disaster-loan-program-charge-off-amount-fy2026.2026-08-08T10-33-07Z.e8ccebd76875e8eb","runId":"run.sba-disaster-loan-program-charge-off-amount-fy2026.2026-08-08T10-33-07Z.e8ccebd76875e8eb","predictionId":"sba-disaster-loan-program-charge-off-amount-fy2026","specId":"spec.sba-disaster-loan-program-charge-off-amount-fy2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Reference class/base rate: I use the current official SBA vintage available to the draft, not FRED or a catalog forecast, because no later revised-methodology print for this registered target was part of the admissible evidence used here. The completed FY2016-FY2024 Disaster / Disaster charge-off sample has 9 annual observations and spans 18405594 to 322632623, with the most relevant recent completed values 180342594, 322632623, and 299971326; FY2025 is only a partial value at 107714599 through June 30, 2025.","Variant discipline: every historical anchor is the Disaster / Disaster row, excluding COVID EIDL and excluding the Disaster subtotal, because the resolver field is Disaster / Disaster rather than aggregate Disaster programs."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing and exact resolver: the target is SBA Loan Program Performance Table 5 - Charge Off Amount by Program, row Disaster under the Disaster section, fiscal year 2026 first print, unit dollars. I keep resolutionSourceUrl byte-equal to the registered methodology announcement URL and use 2028-12-31 as the Thesis lab resolve-by bound, not as an inferred SBA release date.","Tool call: fetch_official_announcement exact registered URL https://legacy.sba.gov/document/report-small-business-administration-loan-program-performance"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["SBA Disaster loan charge-off amount FY2026 first print","Framing and exact resolver: the target is SBA Loan Program Performance Table 5 - Charge Off Amount by Program, row Disaster under the Disaster section, fiscal year 2026 first print, unit dollars. I keep resolutionSourceUrl byte-equal to the registered methodology announcement URL and use 2028-12-31 as the Thesis lab resolve-by bound, not as an inferred SBA release date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 489285714, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is the recent completed official reference class centered near the FY2022-FY2024 values 180342594, 322632623, and 299971326. A formal time-series model is downweighted because the completed same-row sample is short, structurally affected by disaster cohorts, and the FY2025 observation is partial rather than a completed annual print. Level effect is positive from UPB rising to 11976493088 in partial FY2025; momentum effect is mixed because FY2025 charge-offs are only 107714599 through three quarters while FY2024 was 299971326; one-off/policy effect allows large disaster-cohort charge-offs but excludes COVID EIDL; interval method is threshold-ladder interpolation anchored by the FY2016-FY2024 completed range and the FY2025 partial print. I put the median below FY2023-FY2024 but above FY2022, with 80% bounds at 85714286 and 575000000 covering a low normalization year and a high stress year.","Counter-considerations: upside risk is a delayed charge-off wave from the larger FY2025 Disaster approval and UPB base, which would land above the interval if FY2026 charge-off rates resemble or exceed FY2023-FY2024 while balances keep expanding. Downside risk is continued low observed FY2025 runoff and recoverability improvements, which would land below the interval if FY2026 resembles FY2021 or the early FY2025 pace. An outside the interval outcome is most plausible from a major disaster-loan cohort accounting change or unexpectedly severe liquidation cycle."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Reference class/base rate: I use the current official SBA vintage available to the draft, not FRED or a catalog forecast, because no later revised-methodology print for this registered target was part of the admissible evidence used here. The completed FY2016-FY2024 Disaster / Disaster charge-off sample has 9 annual observations and spans 18405594 to 322632623, with the most relevant recent completed values 180342594, 322632623, and 299971326; FY2025 is only a partial value at 107714599 through June 30, 2025.","Variant discipline: every historical anchor is the Disaster / Disaster row, excluding COVID EIDL and excluding the Disaster subtotal, because the resolver field is Disaster / Disaster rather than aggregate Disaster programs."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence prior is the recent completed official reference class centered near the FY2022-FY2024 values 180342594, 322632623, and 299971326. A formal time-series model is downweighted because the completed same-row sample is short, structurally affected by disaster cohorts, and the FY2025 observation is partial rather than a completed annual print. Level effect is positive from UPB rising to 11976493088 in partial FY2025; momentum effect is mixed because FY2025 charge-offs are only 107714599 through three quarters while FY2024 was 299971326; one-off/policy effect allows large disaster-cohort charge-offs but excludes COVID EIDL; interval method is threshold-ladder interpolation anchored by the FY2016-FY2024 completed range and the FY2025 partial print. I put the median below FY2023-FY2024 but above FY2022, with 80% bounds at 85714286 and 575000000 covering a low normalization year and a high stress year.","Counter-considerations: upside risk is a delayed charge-off wave from the larger FY2025 Disaster approval and UPB base, which would land above the interval if FY2026 charge-off rates resemble or exceed FY2023-FY2024 while balances keep expanding. Downside risk is continued low observed FY2025 runoff and recoverability improvements, which would land below the interval if FY2026 resembles FY2021 or the early FY2025 pace. An outside the interval outcome is most plausible from a major disaster-loan cohort accounting change or unexpectedly severe liquidation cycle."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Reference class/base rate: I use the current official SBA vintage available to the draft, not FRED or a catalog forecast, because no later revised-methodology print for this registered target was part of the admissible evidence used here. The completed FY2016-FY2024 Disaster / Disaster charge-off sample has 9 annual observations and spans 18405594 to 322632623, with the most relevant recent completed values 180342594, 322632623, and 299971326; FY2025 is only a partial value at 107714599 through June 30, 2025.","Prior/update/interval: persistence prior is the recent completed official reference class centered near the FY2022-FY2024 values 180342594, 322632623, and 299971326. A formal time-series model is downweighted because the completed same-row sample is short, structurally affected by disaster cohorts, and the FY2025 observation is partial rather than a completed annual print. Level effect is positive from UPB rising to 11976493088 in partial FY2025; momentum effect is mixed because FY2025 charge-offs are only 107714599 through three quarters while FY2024 was 299971326; one-off/policy effect allows large disaster-cohort charge-offs but excludes COVID EIDL; interval method is threshold-ladder interpolation anchored by the FY2016-FY2024 completed range and the FY2025 partial print. I put the median below FY2023-FY2024 but above FY2022, with 80% bounds at 85714286 and 575000000 covering a low normalization year and a high stress year."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: sba-disaster-loan-program-charge-off-amount-fy2026\nrunLabel: Headline\nresolutionDate: 2028-12-31\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.sba-disaster-loan-program-charge-off-rate-upb-fy2026.2026-08-08T10-35-56Z.14687da29c38eb59","runId":"run.sba-disaster-loan-program-charge-off-rate-upb-fy2026.2026-08-08T10-35-56Z.14687da29c38eb59","predictionId":"sba-disaster-loan-program-charge-off-rate-upb-fy2026","specId":"spec.sba-disaster-loan-program-charge-off-rate-upb-fy2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: the current official SBA Table 9 vintage through 2025-06-30 is the admissible base rate because no separate revised/backcast official print was found. The 2016-2024 full-year Disaster / Disaster history has a median of 1.46%, with a recent elevated cluster at 1.97%, 3.44%, and 3.06% in FY2022-FY2024, while the FY2025 partial-year print is much lower at 0.90%.","Prior/update/interval: persistence prior is the 2016-2024 full-year reference class centered near the 1.46% median, updated downward from the FY2022-FY2024 high-rate cluster by the FY2025 Q3 0.90% rate and larger 2025 UPB denominator, then nudged upward for lagged disaster-loan credit stress; the CRS default and recovery assumptions are directional context, not direct inputs to the Table 9 charge-off-rate calculation. Interval method is the elicited threshold ladder anchored by the fetched 0.90%, 1.46%, 1.97%, 3.06%, and 3.44% values, with the announced methodology-transition/regime consideration handled by widening the upper tail rather than applying any fabricated revision adjustment."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing: the target is the first official FY2026 SBA Loan Program Performance Table 9 print for the Disaster program row labeled Disaster, not the separate COVID EIDL row. The resolution date byte-echoes the Thesis resolve-by-bound of 2028-12-31; this is an outer bound, not an inferred SBA release date. The resolutionSourceUrl byte-echoes the registered methodology-announcement URL, and the required official announcement fetch returned HTTP 200 for 37099 bytes with response SHA-256 5a77a6bb8e74afdefcffd588fb37cab831ca69385b69d6911b900a99efaede64.","Tool result: CRS table values for FY2025 disaster-loan assumptions included a 3.16% borrower interest rate, 29.39% default rate, and 29.17% post-default recovery rate; FY2024 values were 2.93%, 28.22%, and 27.76% respectively."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Framing: the target is the first official FY2026 SBA Loan Program Performance Table 9 print for the Disaster program row labeled Disaster, not the separate COVID EIDL row. The resolution date byte-echoes the Thesis resolve-by-bound of 2028-12-31; this is an outer bound, not an inferred SBA release date. The resolutionSourceUrl byte-echoes the registered methodology-announcement URL, and the required official announcement fetch returned HTTP 200 for 37099 bytes with response SHA-256 5a77a6bb8e74afdefcffd588fb37cab831ca69385b69d6911b900a99efaede64."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.53, distribution present, forecast step count 1.","evidence":["Tool call: Checked CRS disaster-loan program context for forward-looking credit risk in the disaster account.","Prior/update/interval: persistence prior is the 2016-2024 full-year reference class centered near the 1.46% median, updated downward from the FY2022-FY2024 high-rate cluster by the FY2025 Q3 0.90% rate and larger 2025 UPB denominator, then nudged upward for lagged disaster-loan credit stress; the CRS default and recovery assumptions are directional context, not direct inputs to the Table 9 charge-off-rate calculation. Interval method is the elicited threshold ladder anchored by the fetched 0.90%, 1.46%, 1.97%, 3.06%, and 3.44% values, with the announced methodology-transition/regime consideration handled by widening the upper tail rather than applying any fabricated revision adjustment."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Reference class and base rate: the current official SBA Table 9 vintage through 2025-06-30 is the admissible base rate because no separate revised/backcast official print was found. The 2016-2024 full-year Disaster / Disaster history has a median of 1.46%, with a recent elevated cluster at 1.97%, 3.44%, and 3.06% in FY2022-FY2024, while the FY2025 partial-year print is much lower at 0.90%.","Variant control: all numeric anchors above are the SBA Table 9 charge-off rate as a percent of UPB for Disaster / Disaster. I excluded COVID EIDL values even though they appear under Disaster, because COVID EIDL is a separate row and the target field is Disaster / Disaster."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool call: Checked CRS disaster-loan program context for forward-looking credit risk in the disaster account.","Counter-considerations: upside risk for the rate is a delayed wave of default determinations on older disaster loans or a smaller-than-expected FY2026 UPB denominator, which would land above the interval if charge-offs resembled FY2023 while UPB stopped growing. Downside risk is continuation of FY2025's low run rate or unusually high recoverability, which could land below the interval if annual charge-offs stay near the 2025 Q3 pace against a large UPB base."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["SBA Disaster / Disaster FY2026 charge-off rate forecast","Prior/update/interval: persistence prior is the 2016-2024 full-year reference class centered near the 1.46% median, updated downward from the FY2022-FY2024 high-rate cluster by the FY2025 Q3 0.90% rate and larger 2025 UPB denominator, then nudged upward for lagged disaster-loan credit stress; the CRS default and recovery assumptions are directional context, not direct inputs to the Table 9 charge-off-rate calculation. Interval method is the elicited threshold ladder anchored by the fetched 0.90%, 1.46%, 1.97%, 3.06%, and 3.44% values, with the announced methodology-transition/regime consideration handled by widening the upper tail rather than applying any fabricated revision adjustment."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: sba-disaster-loan-program-charge-off-rate-upb-fy2026\nrunLabel: Headline\nresolutionDate: 2028-12-31\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.sba-disaster-loan-program-post-charge-off-recovery-fy2026.2026-08-08T10-38-51Z.2cdb59f4451b6ef7","runId":"run.sba-disaster-loan-program-post-charge-off-recovery-fy2026.2026-08-08T10-38-51Z.2cdb59f4451b6ef7","predictionId":"sba-disaster-loan-program-post-charge-off-recovery-fy2026","specId":"spec.sba-disaster-loan-program-post-charge-off-recovery-fy2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate / reference class: while no official print under a revised methodology exists, the current official SBA series is the admissible base rate. The most relevant current-vintage history is the Disaster / Disaster row, not COVID EIDL: $96.56 million in FY2023, $126.51 million in FY2024, and $85.43 million through FY2025 Q3. The announced transition is a regime consideration, so I widen the interval rather than fabricating a revision adjustment.","Prior/update/interval: persistence prior is the current official Disaster / Disaster reference class centered on FY2023-FY2025Q3, with FY2025Q3 annualized only as a noisy momentum guide ($85,429,990 over three quarters implies about $113.9 million if linear). Level component anchors near $100-$120 million; momentum pulls slightly below FY2024's $126.51 million; charge-off flow of $107.71 million through FY2025Q3 and UPB of $11.98 billion support ongoing recoveries; methodology-transition risk widens both tails. The uncertainty method is the elicited threshold ladder over the FY2021-FY2025Q3 current-vintage sample, with the ladder-derived 10th and 90th percentiles used directly as the 80% interval."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this forecast is tied to the registered resolve-by-bound target. ResolutionDate byte-echoes the Thesis bound 2028-12-31, not an inferred SBA release day. ResolutionSourceUrl byte-echoes the official announcement URL. The resolving field is Table 7 - Post-Charge Off Recovery Amount by Program, Disaster section, Disaster row, FY2026 column, first official print, whole dollars.","Tool call: fetch_official_announcement({\"url\":\"https://legacy.sba.gov/document/report-small-business-administration-loan-program-performance\"})"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this forecast is tied to the registered resolve-by-bound target. ResolutionDate byte-echoes the Thesis bound 2028-12-31, not an inferred SBA release day. ResolutionSourceUrl byte-echoes the official announcement URL. The resolving field is Table 7 - Post-Charge Off Recovery Amount by Program, Disaster section, Disaster row, FY2026 column, first official print, whole dollars.","Tool result: Fetched exact registered announcement URL with statusCode 200, responseBytes 37099, and responseSha256 5a77a6bb8e74afdefcffd588fb37cab831ca69385b69d6911b900a99efaede64. That page authenticates the SBA Loan Program Performance source identity only; it does not establish the lab-committed release window or bound."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 86666667, distribution present, forecast step count 1.","evidence":["Base rate / reference class: while no official print under a revised methodology exists, the current official SBA series is the admissible base rate. The most relevant current-vintage history is the Disaster / Disaster row, not COVID EIDL: $96.56 million in FY2023, $126.51 million in FY2024, and $85.43 million through FY2025 Q3. The announced transition is a regime consideration, so I widen the interval rather than fabricating a revision adjustment.","Prior/update/interval: persistence prior is the current official Disaster / Disaster reference class centered on FY2023-FY2025Q3, with FY2025Q3 annualized only as a noisy momentum guide ($85,429,990 over three quarters implies about $113.9 million if linear). Level component anchors near $100-$120 million; momentum pulls slightly below FY2024's $126.51 million; charge-off flow of $107.71 million through FY2025Q3 and UPB of $11.98 billion support ongoing recoveries; methodology-transition risk widens both tails. The uncertainty method is the elicited threshold ladder over the FY2021-FY2025Q3 current-vintage sample, with the ladder-derived 10th and 90th percentiles used directly as the 80% interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior is the current official Disaster / Disaster reference class centered on FY2023-FY2025Q3, with FY2025Q3 annualized only as a noisy momentum guide ($85,429,990 over three quarters implies about $113.9 million if linear). Level component anchors near $100-$120 million; momentum pulls slightly below FY2024's $126.51 million; charge-off flow of $107.71 million through FY2025Q3 and UPB of $11.98 billion support ongoing recoveries; methodology-transition risk widens both tails. The uncertainty method is the elicited threshold ladder over the FY2021-FY2025Q3 current-vintage sample, with the ladder-derived 10th and 90th percentiles used directly as the 80% interval."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence prior is the current official Disaster / Disaster reference class centered on FY2023-FY2025Q3, with FY2025Q3 annualized only as a noisy momentum guide ($85,429,990 over three quarters implies about $113.9 million if linear). Level component anchors near $100-$120 million; momentum pulls slightly below FY2024's $126.51 million; charge-off flow of $107.71 million through FY2025Q3 and UPB of $11.98 billion support ongoing recoveries; methodology-transition risk widens both tails. The uncertainty method is the elicited threshold ladder over the FY2021-FY2025Q3 current-vintage sample, with the ladder-derived 10th and 90th percentiles used directly as the 80% interval.","Counter-considerations: upside risk comes from unusually strong Treasury Cross Servicing receipts or catch-up recoveries from older disaster charge-offs and would land above the interval if FY2026 exceeds $150,000,000. Downside risk comes from a rapid decline in collectible charged-off Disaster balances, timing slippage of recoveries after FY2025 Q3, or methodology changes that allocate less to the Disaster row and would land below the interval if FY2026 is under $63,333,333. A COVID EIDL surge is outside the interval only if it is reclassified into the Disaster / Disaster row, which the current table structure does not do."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["SBA Disaster / Disaster FY2026 post-charge-off recovery forecast","Framing and exact resolver: this forecast is tied to the registered resolve-by-bound target. ResolutionDate byte-echoes the Thesis bound 2028-12-31, not an inferred SBA release day. ResolutionSourceUrl byte-echoes the official announcement URL. The resolving field is Table 7 - Post-Charge Off Recovery Amount by Program, Disaster section, Disaster row, FY2026 column, first official print, whole dollars."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: sba-disaster-loan-program-post-charge-off-recovery-fy2026\nrunLabel: Headline\nresolutionDate: 2028-12-31\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.initial-claims-week-2026-08-08.2026-08-07T19-01-52Z.252874073cc9281a","runId":"run.initial-claims-week-2026-08-08.2026-08-07T19-01-52Z.252874073cc9281a","predictionId":"initial-claims-week-2026-08-08","specId":"spec.initial-claims-week-2026-08-08","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool result: The August 6, 2026 DOL release reported week ending August 1 initial claims SA at 199,000, prior week revised to 198,000, July 18 at 189,000, and the 4-week moving average at 198,750.","Reference class and base rate: using the DOL/ICSA 2026 seasonally adjusted weekly initial-claims table from January 3 through August 1, values mostly sit in a 190k-230k range, with recent levels 217k, 209k, 189k, 198k, and 199k. The immediate base rate is a 199k persistence prior before a small upward update, rather than the higher June level around 224k."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing and exact resolver: the target is the DOL advance seasonally adjusted initial claims figure for the week ending August 8, 2026, not NSA claims, continuing claims, or a later revised vintage. The registered resolver uses ALFRED/FRED series ICSA as the advance-vintage source binding for the first official DOL print, converted to thousands.","Tool call: Opened the DOL current UI Weekly Claims PDF for the latest official release and recent table values."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: the target is the DOL advance seasonally adjusted initial claims figure for the week ending August 8, 2026, not NSA claims, continuing claims, or a later revised vintage. The registered resolver uses ALFRED/FRED series ICSA as the advance-vintage source binding for the first official DOL print, converted to thousands.","Tool call: Opened the DOL current UI Weekly Claims PDF for the latest official release and recent table values."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 28, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is latest SA level 199k, historical sample is DOL/ICSA 2026 weekly SA initial claims from January 3 through August 1 using available latest-public values as a proxy for first-print volatility, adjustment components are +2k mean reversion from the July 18 low and late-July rebound, +0k for seasonal translation because the target is SA, and +0k for policy/mechanism shock because continuing claims and IUR do not show a break. The 30 successive weekly changes have sigma = 10.6k; 1.28*sigma = 13.6k, so an 80% interval around a 201k point is 201 +/- 13.6 = 187.4k to 214.6k, rounded to 187k-215k.","Upside risk: a renewed layoff cluster, delayed claims after summer plant shutdowns, or a state-processing catch-up would land above the interval if the advance SA print is above 215k. Downside risk: another holiday/auto-seasonality overadjustment or continued unusually low layoffs would land below the interval if the first print is under 187k."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior is latest SA level 199k, historical sample is DOL/ICSA 2026 weekly SA initial claims from January 3 through August 1 using available latest-public values as a proxy for first-print volatility, adjustment components are +2k mean reversion from the July 18 low and late-July rebound, +0k for seasonal translation because the target is SA, and +0k for policy/mechanism shock because continuing claims and IUR do not show a break. The 30 successive weekly changes have sigma = 10.6k; 1.28*sigma = 13.6k, so an 80% interval around a 201k point is 201 +/- 13.6 = 187.4k to 214.6k, rounded to 187k-215k."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Upside risk: a renewed layoff cluster, delayed claims after summer plant shutdowns, or a state-processing catch-up would land above the interval if the advance SA print is above 215k. Downside risk: another holiday/auto-seasonality overadjustment or continued unusually low layoffs would land below the interval if the first print is under 187k."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for U.S. initial claims, week ending August 8, 2026","Prior/update/interval: persistence prior is latest SA level 199k, historical sample is DOL/ICSA 2026 weekly SA initial claims from January 3 through August 1 using available latest-public values as a proxy for first-print volatility, adjustment components are +2k mean reversion from the July 18 low and late-July rebound, +0k for seasonal translation because the target is SA, and +0k for policy/mechanism shock because continuing claims and IUR do not show a break. The 30 successive weekly changes have sigma = 10.6k; 1.28*sigma = 13.6k, so an 80% interval around a 201k point is 201 +/- 13.6 = 187.4k to 214.6k, rounded to 187k-215k."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: initial-claims-week-2026-08-08\nrunLabel: Headline\nresolutionDate: 2026-08-15\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.continued-claims-week-2026-08-08.2026-08-07T19-04-35Z.3dcda4ea36276603","runId":"run.continued-claims-week-2026-08-08.2026-08-07T19-04-35Z.3dcda4ea36276603","predictionId":"continued-claims-week-2026-08-08","specId":"spec.continued-claims-week-2026-08-08","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate / reference class: over the latest 53 DOL weekly changes from July 26, 2025 through July 25, 2026, SA insured unemployment stayed mostly in a narrow band and the recent 2026 values clustered around 1.79-1.81 million. The same variant is used throughout: seasonally adjusted insured unemployment, not NSA state claims or all-program continued weeks claimed.","Prior/update/interval: persistence prior starts at the latest 1.801 million; historical sample is the DOL weekly SA insured-unemployment one-week change list from July 26, 2025 to July 25, 2026, with sigma computed as the standard deviation of those one-week changes. Adjustment components: level +0.000 from latest, momentum -0.006 because the 4-week average is 1.791 million and initial claims are low at 199,000, one-off +0.000 because no holiday distortion is scheduled for August 20, policy-mechanism +0.000 because no extended-benefit trigger is material at the national SA level. Point = 1.801 - 0.006 = 1.795 million. Weekly change dispersion gives sigma = 0.0215 million; for the two-week horizon I use sqrt(2)*sigma = 0.0304 million, and 1.28*sigma = 0.039 million, giving 1.795 +/- 0.039 = [1.756, 1.834]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this targets DOL ETA advance seasonally adjusted insured unemployment, also described as continued claims, for the week ending August 8, 2026. The registered resolver uses ALFRED/FRED series CCSA advance vintage as the mechanical source binding; the underlying official print is the DOL ETA UI Weekly Claims News Release. The exact scheduled release date is August 20, 2026, inside the registered August 18-22 expected release window.","Tool call: Checked the DOL ETA UI claims archive publication schedule page for the release rule and exceptions."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast for first-print seasonally adjusted continued claims","Framing and exact resolver: this targets DOL ETA advance seasonally adjusted insured unemployment, also described as continued claims, for the week ending August 8, 2026. The registered resolver uses ALFRED/FRED series CCSA advance vintage as the mechanical source binding; the underlying official print is the DOL ETA UI Weekly Claims News Release. The exact scheduled release date is August 20, 2026, inside the registered August 18-22 expected release window."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.08, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior starts at the latest 1.801 million; historical sample is the DOL weekly SA insured-unemployment one-week change list from July 26, 2025 to July 25, 2026, with sigma computed as the standard deviation of those one-week changes. Adjustment components: level +0.000 from latest, momentum -0.006 because the 4-week average is 1.791 million and initial claims are low at 199,000, one-off +0.000 because no holiday distortion is scheduled for August 20, policy-mechanism +0.000 because no extended-benefit trigger is material at the national SA level. Point = 1.801 - 0.006 = 1.795 million. Weekly change dispersion gives sigma = 0.0215 million; for the two-week horizon I use sqrt(2)*sigma = 0.0304 million, and 1.28*sigma = 0.039 million, giving 1.795 +/- 0.039 = [1.756, 1.834].","Counter-considerations: upside risk is a sudden rise in claim duration after the late-July 24,000 increase, which would land above the interval if the next two weekly SA changes sum to more than about +33,000 from the latest 1.801 million. Downside risk is continued low initial claims feeding through quickly, which would land below the interval if the next two weekly SA changes sum to less than about -45,000."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior starts at the latest 1.801 million; historical sample is the DOL weekly SA insured-unemployment one-week change list from July 26, 2025 to July 25, 2026, with sigma computed as the standard deviation of those one-week changes. Adjustment components: level +0.000 from latest, momentum -0.006 because the 4-week average is 1.791 million and initial claims are low at 199,000, one-off +0.000 because no holiday distortion is scheduled for August 20, policy-mechanism +0.000 because no extended-benefit trigger is material at the national SA level. Point = 1.801 - 0.006 = 1.795 million. Weekly change dispersion gives sigma = 0.0215 million; for the two-week horizon I use sqrt(2)*sigma = 0.0304 million, and 1.28*sigma = 0.039 million, giving 1.795 +/- 0.039 = [1.756, 1.834]."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-considerations: upside risk is a sudden rise in claim duration after the late-July 24,000 increase, which would land above the interval if the next two weekly SA changes sum to more than about +33,000 from the latest 1.801 million. Downside risk is continued low initial claims feeding through quickly, which would land below the interval if the next two weekly SA changes sum to less than about -45,000."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for first-print seasonally adjusted continued claims","Prior/update/interval: persistence prior starts at the latest 1.801 million; historical sample is the DOL weekly SA insured-unemployment one-week change list from July 26, 2025 to July 25, 2026, with sigma computed as the standard deviation of those one-week changes. Adjustment components: level +0.000 from latest, momentum -0.006 because the 4-week average is 1.791 million and initial claims are low at 199,000, one-off +0.000 because no holiday distortion is scheduled for August 20, policy-mechanism +0.000 because no extended-benefit trigger is material at the national SA level. Point = 1.801 - 0.006 = 1.795 million. Weekly change dispersion gives sigma = 0.0215 million; for the two-week horizon I use sqrt(2)*sigma = 0.0304 million, and 1.28*sigma = 0.039 million, giving 1.795 +/- 0.039 = [1.756, 1.834]."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: continued-claims-week-2026-08-08\nrunLabel: Headline\nresolutionDate: 2026-08-20\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-dod-new-prime-awards-fy2026.2026-08-07T19-16-18Z.f5240e48131ac70e","runId":"run.us-dod-new-prime-awards-fy2026.2026-08-07T19-16-18Z.f5240e48131ac70e","predictionId":"us-dod-new-prime-awards-fy2026","specId":"spec.us-dod-new-prime-awards-fy2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.51,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Tool call: USAspending API v2 agency 097 awards new count historical fiscal-year pulls for FY2021-FY2025 using the same resolver endpoint pattern and default agency_type=awarding, award_type_codes=null parameters","Base rate and reference class: the FY2021-FY2025 annual level prior is centered near 1.495 million, with FY2024-FY2025 closer to 1.55 million. The current FY2026 count of 1.068328 million is through latest_action_date 2026-07-10, so a simple elapsed-year annualization based on FY2026 progress through that action date gives about 1.38 million before allowing for end-year and reporting-window backfill."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing and exact resolver: the target is USAspending API v2 agency 097, field new_award_count, fiscal_year=2026, transformed to millions. The official agency overview identifies toptier_code 097 as Department of Defense and states that DoD contract and IDV data are subject to a 90-day publication delay while other DoD data are not; that matters because the 2026-10-22 registered snapshot may still be a policy-defined snapshot rather than a fully final all-contract vintage.","Tool result: Fetched official current FY2026 response: toptier_code=097, fiscal_year=2026, agency_type=awarding, award_type_codes=null, new_award_count=1068328, equal to 1.068328 million after the registered factor 1e-6."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior/update/interval: persistence prior = FY2021-FY2025 official annual new_award_count values in millions [1.765, 1.285, 1.332, 1.505, 1.588], mean = 1.495. Current-release update = 1.068328 / about 0.775 of FY2026 elapsed through latest_action_date 2026-07-10 = 1.379 annualized, plus +0.05 million for late-fiscal-year/backfill flow and no separate policy shock, giving point = 1.43. Interval method = sample dispersion of the five annual flow values; sigma = 0.195 million, so 1.28*sigma = 0.250 million, yielding 1.43 +/- 0.25 = [1.18, 1.68].","Counter-considerations: upside risk is a larger-than-usual DoD/DLA late-year contract and assistance backfill, which would land above the interval if the 2026-10-22 snapshot exceeds 1.68 million. Downside risk is continued missing delayed procurement records or weaker DLA micro-award volume, which would land below the interval if the snapshot remains under 1.18 million. Outside the interval would mainly signal either a release-policy/backfill timing surprise or an actual count-regime break, not ordinary year-to-year noise."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.5, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = FY2021-FY2025 official annual new_award_count values in millions [1.765, 1.285, 1.332, 1.505, 1.588], mean = 1.495. Current-release update = 1.068328 / about 0.775 of FY2026 elapsed through latest_action_date 2026-07-10 = 1.379 annualized, plus +0.05 million for late-fiscal-year/backfill flow and no separate policy shock, giving point = 1.43. Interval method = sample dispersion of the five annual flow values; sigma = 0.195 million, so 1.28*sigma = 0.250 million, yielding 1.43 +/- 0.25 = [1.18, 1.68].","Counter-considerations: upside risk is a larger-than-usual DoD/DLA late-year contract and assistance backfill, which would land above the interval if the 2026-10-22 snapshot exceeds 1.68 million. Downside risk is continued missing delayed procurement records or weaker DLA micro-award volume, which would land below the interval if the snapshot remains under 1.18 million. Outside the interval would mainly signal either a release-policy/backfill timing surprise or an actual count-regime break, not ordinary year-to-year noise."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Framing and exact resolver: the target is USAspending API v2 agency 097, field new_award_count, fiscal_year=2026, transformed to millions. The official agency overview identifies toptier_code 097 as Department of Defense and states that DoD contract and IDV data are subject to a 90-day publication delay while other DoD data are not; that matters because the 2026-10-22 registered snapshot may still be a policy-defined snapshot rather than a fully final all-contract vintage."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-considerations: upside risk is a larger-than-usual DoD/DLA late-year contract and assistance backfill, which would land above the interval if the 2026-10-22 snapshot exceeds 1.68 million. Downside risk is continued missing delayed procurement records or weaker DLA micro-award volume, which would land below the interval if the snapshot remains under 1.18 million. Outside the interval would mainly signal either a release-policy/backfill timing surprise or an actual count-regime break, not ordinary year-to-year noise."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["DoD FY2026 New Prime Awards Forecast","Tool result: Fetched official schedule/update context: awards last_updated=08/07/2026; FY2026 fiscal month 9 submission_due_date=2026-07-31 and certification_due_date=2026-08-15; FY2025 fiscal month 12 had submission_start_date=2025-10-21, certification_due_date=2025-11-18, and submission_reveal_date=2025-12-06T02:57:27.169269Z. I found no official future FY2026 period-12 exact reveal date in the available endpoint, so I keep the ledger-registered resolve-by-bound date 2026-10-22 and state this discrepancy rather than changing the target."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-dod-new-prime-awards-fy2026\nrunLabel: Headline\nresolutionDate: 2026-10-22\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-dod-prime-award-transactions-fy2026.2026-08-07T19-19-30Z.d78365a0b89060f6","runId":"run.us-dod-prime-award-transactions-fy2026.2026-08-07T19-19-30Z.d78365a0b89060f6","predictionId":"us-dod-prime-award-transactions-fy2026","specId":"spec.us-dod-prime-award-transactions-fy2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.51,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the same-source annual flow reference class is FY2021-FY2025 DoD prime award transaction counts, current official API readings rather than known first registered snapshots, ranging from 3.786 million to 4.566 million, with a mean of 4.144 million and a downward drift of about 0.195 million per year over the last four year-to-year steps.","Level and momentum: a linear trend/extrapolation prior was considered but only partially used because the decline from FY2021 through FY2025 appears to be flattening; I therefore anchor on FY2025 persistence rather than extending the full trend mechanically."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 7 source-context item(s), activity log present.","evidence":["Forecast DoD FY2026 Prime Award Transactions","Framing and exact resolver: this is the USAspending API v2 agency 097 awards endpoint, fiscal_year=2026, field transaction_count, transformed to millions. The registered target uses a resolve-by-bound window ending 2026-10-22; the official submission-period endpoint visible this run lists recent reveal and certification dates but not yet the future FY2026 fiscal-month-12 row, so I keep the ledger resolutionDate and note that the exact future reveal row was not observable yet."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Base rate/reference class: the same-source annual flow reference class is FY2021-FY2025 DoD prime award transaction counts, current official API readings rather than known first registered snapshots, ranging from 3.786 million to 4.566 million, with a mean of 4.144 million and a downward drift of about 0.195 million per year over the last four year-to-year steps.","Prior/update/interval: persistence prior is FY2025 at 3.786 million; historical sample is FY2021-FY2025 same USAspending API annual values of 4.566, 4.318, 4.084, 3.965, and 3.786 million; adjustment components are +0.04 million for stabilization after the FY2021-FY2025 decline and +0.03 million for FY2026 late-year defense award/modification flow, giving point 3.786 + 0.074 = 3.860 million. For this annual flow-series interval I use dispersion of the annual values themselves: sigma = 0.305 million, so 80% half-width is about 1.28*sigma = 1.28*0.305 = 0.390 million, implying 3.860 +/- 0.390 = 3.470 to 4.250 million. The level-based sigma is intentionally conservative relative to recent year-to-year change volatility because the first registered snapshot can be affected by reporting lag and late procurement transaction clearing."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.78, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is FY2025 at 3.786 million; historical sample is FY2021-FY2025 same USAspending API annual values of 4.566, 4.318, 4.084, 3.965, and 3.786 million; adjustment components are +0.04 million for stabilization after the FY2021-FY2025 decline and +0.03 million for FY2026 late-year defense award/modification flow, giving point 3.786 + 0.074 = 3.860 million. For this annual flow-series interval I use dispersion of the annual values themselves: sigma = 0.305 million, so 80% half-width is about 1.28*sigma = 1.28*0.305 = 0.390 million, implying 3.860 +/- 0.390 = 3.470 to 4.250 million. The level-based sigma is intentionally conservative relative to recent year-to-year change volatility because the first registered snapshot can be affected by reporting lag and late procurement transaction clearing.","Counter-considerations: upside risk is a heavier-than-usual late FY2026 modification surge or delayed FY2025-FY2026 procurement data clearing into the first snapshot, which would land above the interval if the count exceeds 4.25 million. Downside risk is a reporting lag, shutdown-related processing disruption, or sustained simplification of award actions, which would land below the interval if the count is under 3.47 million."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level and momentum: a linear trend/extrapolation prior was considered but only partially used because the decline from FY2021 through FY2025 appears to be flattening; I therefore anchor on FY2025 persistence rather than extending the full trend mechanically.","Prior/update/interval: persistence prior is FY2025 at 3.786 million; historical sample is FY2021-FY2025 same USAspending API annual values of 4.566, 4.318, 4.084, 3.965, and 3.786 million; adjustment components are +0.04 million for stabilization after the FY2021-FY2025 decline and +0.03 million for FY2026 late-year defense award/modification flow, giving point 3.786 + 0.074 = 3.860 million. For this annual flow-series interval I use dispersion of the annual values themselves: sigma = 0.305 million, so 80% half-width is about 1.28*sigma = 1.28*0.305 = 0.390 million, implying 3.860 +/- 0.390 = 3.470 to 4.250 million. The level-based sigma is intentionally conservative relative to recent year-to-year change volatility because the first registered snapshot can be affected by reporting lag and late procurement transaction clearing."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Framing and exact resolver: this is the USAspending API v2 agency 097 awards endpoint, fiscal_year=2026, field transaction_count, transformed to millions. The registered target uses a resolve-by-bound window ending 2026-10-22; the official submission-period endpoint visible this run lists recent reveal and certification dates but not yet the future FY2026 fiscal-month-12 row, so I keep the ledger resolutionDate and note that the exact future reveal row was not observable yet.","Level and momentum: a linear trend/extrapolation prior was considered but only partially used because the decline from FY2021 through FY2025 appears to be flattening; I therefore anchor on FY2025 persistence rather than extending the full trend mechanically."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast DoD FY2026 Prime Award Transactions","Framing and exact resolver: this is the USAspending API v2 agency 097 awards endpoint, fiscal_year=2026, field transaction_count, transformed to millions. The registered target uses a resolve-by-bound window ending 2026-10-22; the official submission-period endpoint visible this run lists recent reveal and certification dates but not yet the future FY2026 fiscal-month-12 row, so I keep the ledger resolutionDate and note that the exact future reveal row was not observable yet."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-dod-prime-award-transactions-fy2026\nrunLabel: Headline\nresolutionDate: 2026-10-22\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: resolution clarity (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-dod-unique-prime-contract-recipients-fy2026.2026-08-07T19-24-07Z.1a95330a97b8e06a","runId":"run.us-dod-unique-prime-contract-recipients-fy2026.2026-08-07T19-24-07Z.1a95330a97b8e06a","predictionId":"us-dod-unique-prime-contract-recipients-fy2026","specId":"spec.us-dod-unique-prime-contract-recipients-fy2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 8 historical point(s) and explicit outside-view language.","evidence":["Tool call: Fetched audited same-query historical recipient counts from the USAspending API registered-query shape for DoD A-D contract transactions by fiscal year.","Base rate/reference class: the reference class is the same official USAspending grouped-recipient query over recent complete fiscal years. The FY2019-FY2025 seven-year level average is 56.2 thousand and the latest complete year is 54.2 thousand, so the base rate says to expect a value in the mid-50-thousands with some rebound toward the recent mean."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this targets the USAspending API v2 Advanced Search spending_by_category/recipient endpoint, grouped by recipient_id, for Department of Defense awarding agency, prime contract award type codes A-D, fiscal year 2026. The ledger uses the registered_query_snapshot rule with an expected release window of 2026-10-15 to 2026-10-22; I keep that resolver and do not add correction-day grace.","Tool call: Fetched audited same-query historical recipient counts from the USAspending API registered-query shape for DoD A-D contract transactions by fiscal year."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this targets the USAspending API v2 Advanced Search spending_by_category/recipient endpoint, grouped by recipient_id, for Department of Defense awarding agency, prime contract award type codes A-D, fiscal year 2026. The ledger uses the registered_query_snapshot rule with an expected release window of 2026-10-15 to 2026-10-22; I keep that resolver and do not add correction-day grace.","Tool call: Checked USAspending submission-statistics methodology and public data timing notes for release-date basis."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.8, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = FY2025 official same-query count 54.2 thousand; historical sample = one audited same-query complete-year sequence, FY2019-FY2025 values 55.6, 55.9, 57.2, 58.5, 56.8, 55.1, 54.2. Adjustment components = +1.4 thousand mean reversion toward the 56.2 thousand seven-year base rate, +0.6 thousand from defense-budget and procurement-breadth support, 0.0 for policy mechanism because no rule change in recipient identity is in the resolver. Point = 54.2 + 1.4 + 0.6 = 56.2. Successive changes are +0.3, +1.3, +1.3, -1.7, -1.7, -0.9 thousand, giving sigma = 1.40 thousand; 1.28*sigma = 1.79 thousand. I widen to a 2.4 thousand half-width, 1.34x the mechanical half-width, because late DoD visibility and UEI/recipient normalization can move a distinct-recipient count more than ordinary year-to-year procurement activity. Final 80% interval = 56.2 +/- 2.4 = 53.8 to 58.6 thousand.","Counter-consideration: upside risk would be broader low-dollar procurement or unusually successful small-business outreach, which would land above the interval if the snapshot exceeds 58.6 thousand. Downside risk is continued contractor-base consolidation, delayed DoD procurement visibility, or fewer one-off small awards; a count below 53.8 thousand would land outside the interval on the low side."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level and momentum: FY2026 year-to-date at 43.7 thousand through visible July data is not mechanically comparable with a full fiscal year because late actions and delayed DoD visibility arrive after fiscal year close. Still, 43.7 thousand is close enough to the recent run-rate that I do not impose a large contraction.","Prior/update/interval: persistence prior = FY2025 official same-query count 54.2 thousand; historical sample = one audited same-query complete-year sequence, FY2019-FY2025 values 55.6, 55.9, 57.2, 58.5, 56.8, 55.1, 54.2. Adjustment components = +1.4 thousand mean reversion toward the 56.2 thousand seven-year base rate, +0.6 thousand from defense-budget and procurement-breadth support, 0.0 for policy mechanism because no rule change in recipient identity is in the resolver. Point = 54.2 + 1.4 + 0.6 = 56.2. Successive changes are +0.3, +1.3, +1.3, -1.7, -1.7, -0.9 thousand, giving sigma = 1.40 thousand; 1.28*sigma = 1.79 thousand. I widen to a 2.4 thousand half-width, 1.34x the mechanical half-width, because late DoD visibility and UEI/recipient normalization can move a distinct-recipient count more than ordinary year-to-year procurement activity. Final 80% interval = 56.2 +/- 2.4 = 53.8 to 58.6 thousand."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-consideration: upside risk would be broader low-dollar procurement or unusually successful small-business outreach, which would land above the interval if the snapshot exceeds 58.6 thousand. Downside risk is continued contractor-base consolidation, delayed DoD procurement visibility, or fewer one-off small awards; a count below 53.8 thousand would land outside the interval on the low side."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["DoD FY2026 unique prime-recipient forecast","Framing and exact resolver: this targets the USAspending API v2 Advanced Search spending_by_category/recipient endpoint, grouped by recipient_id, for Department of Defense awarding agency, prime contract award type codes A-D, fiscal year 2026. The ledger uses the registered_query_snapshot rule with an expected release window of 2026-10-15 to 2026-10-22; I keep that resolver and do not add correction-day grace."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-dod-unique-prime-contract-recipients-fy2026\nrunLabel: Headline\nresolutionDate: 2026-10-22\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-dod-small-business-contract-obligation-share-fy2026.2026-08-07T19-28-47Z.d75b907eb4fadd09","runId":"run.us-dod-small-business-contract-obligation-share-fy2026.2026-08-07T19-28-47Z.d75b907eb4fadd09","predictionId":"us-dod-small-business-contract-obligation-share-fy2026","specId":"spec.us-dod-small-business-contract-obligation-share-fy2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool call: Opened the DoD Office of Industrial Base Growth goals and performance page for small-business prime-contract history and current goals context.","Tool result: Fetched DoD historical prime-contract small-business performance points: FY2020 Total Awards $165.2B, SB Awards $55.1B, share 33.4 percent; FY2019 Total Awards $161.5B, SB Awards $62.3B, share 38.6 percent; FY2018 Total Awards $124.5B, SB Awards $41.7B, share 33.5 percent. Fetched DoD prime-contracting goal row: FY2023 goal 22.43 percent, FY2024 goal 22.43 percent, FY2025 goal 23.17 percent."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["Framing and exact resolver: the target is the USAspending API v2 registered-query snapshot for Department of Defense FY2026 prime-contract obligations, not the SBA eligible-dollar scorecard. The numerator is recipient_type_names=[small_business]; the denominator is the same A/B/C/D DoD prime-contract query without recipient type restriction. The registered target sets the bounded snapshot resolutionDate to 2026-10-22; the official USAspending submission-period endpoint currently shows published periods only through FY2026 fiscal month 9, so the exact FY2026 year-end period was not yet visible there during this run.","Tool result: Fetched FY2025 DoD all-prime dollars: Small Business Concerns in aggregate = $103,824,203,209.59 from 2,365,483 contracts; Other Than Small Business Concerns in aggregate without exclusions = $420,887,508,061.02 from 57,454,020 contracts; computed small-business share = 103.82420320959 / (103.82420320959 + 420.88750806102) * 100 = 19.79 percent."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: the target is the USAspending API v2 registered-query snapshot for Department of Defense FY2026 prime-contract obligations, not the SBA eligible-dollar scorecard. The numerator is recipient_type_names=[small_business]; the denominator is the same A/B/C/D DoD prime-contract query without recipient type restriction. The registered target sets the bounded snapshot resolutionDate to 2026-10-22; the official USAspending submission-period endpoint currently shows published periods only through FY2026 fiscal month 9, so the exact FY2026 year-end period was not yet visible there during this run."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3.2, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = average of fetched exact-variant all-prime FY2024 and FY2025 shares = (20.81 + 19.79) / 2 = 20.30 percent; quantitative historical sample = GSA FPDS all-prime FY2024-FY2025 only, while the older DoD performance points are non-comparable regime checks and are not used in the prior or volatility estimate; adjustment components = -0.3 percentage point for FY2025 downward momentum and large non-small defense obligation growth, +0.2 percentage point for DoD small-business goal pressure and program continuity, net -0.1; point = 20.30 - 0.10 = 20.20 percent. For the exact-variant fetched successive change, sigma = 1.02 percentage points as a one-change persistence error proxy, not a multi-year standard deviation; 1.28*sigma = 1.31 percentage points. I widen to a 1.60 percentage point half-width because the USAspending registered-query recipient-type filter may not exactly match the GSA FPDS report classification, giving 20.2 - 1.6 = 18.6 and 20.2 + 1.6 = 21.8.","Policy and mechanism: upside risk is a stronger FY2026 small-business set-aside mix or slower growth in major-prime obligations, which could move the registered USAspending share toward or above 21.8 percent. Downside risk is a surge in large weapons, IT, construction, or services obligations to non-small primes, which would land below the interval. Outside the interval would require either a larger denominator-mix shock than FY2025 or a material query-classification mismatch between USAspending recipient_type_names and FPDS small-business status."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate/reference class: the best exact-variant recent base rate is the GSA all-prime FPDS Department of Defense ratio, because it uses all prime procurements without the SBA goaling exclusions and is closer to the USAspending denominator than the SBA eligible-dollar scorecard. The two fetched exact-variant observations average 20.30 percent, with FY2025 at 19.79 percent and FY2024 at 20.81 percent.","Prior/update/interval: persistence prior = average of fetched exact-variant all-prime FY2024 and FY2025 shares = (20.81 + 19.79) / 2 = 20.30 percent; quantitative historical sample = GSA FPDS all-prime FY2024-FY2025 only, while the older DoD performance points are non-comparable regime checks and are not used in the prior or volatility estimate; adjustment components = -0.3 percentage point for FY2025 downward momentum and large non-small defense obligation growth, +0.2 percentage point for DoD small-business goal pressure and program continuity, net -0.1; point = 20.30 - 0.10 = 20.20 percent. For the exact-variant fetched successive change, sigma = 1.02 percentage points as a one-change persistence error proxy, not a multi-year standard deviation; 1.28*sigma = 1.31 percentage points. I widen to a 1.60 percentage point half-width because the USAspending registered-query recipient-type filter may not exactly match the GSA FPDS report classification, giving 20.2 - 1.6 = 18.6 and 20.2 + 1.6 = 21.8."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level and momentum: the FY2025 all-prime DoD share fell about 1.02 percentage points from FY2024 even though small-business dollars increased by about $3.93B, because the other-than-small denominator increased by about $40.66B. That argues for a point below the two-year average but not a break far below 20 percent.","Policy and mechanism: upside risk is a stronger FY2026 small-business set-aside mix or slower growth in major-prime obligations, which could move the registered USAspending share toward or above 21.8 percent. Downside risk is a surge in large weapons, IT, construction, or services obligations to non-small primes, which would land below the interval. Outside the interval would require either a larger denominator-mix shock than FY2025 or a material query-classification mismatch between USAspending recipient_type_names and FPDS small-business status."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Framing and exact resolver: the target is the USAspending API v2 registered-query snapshot for Department of Defense FY2026 prime-contract obligations, not the SBA eligible-dollar scorecard. The numerator is recipient_type_names=[small_business]; the denominator is the same A/B/C/D DoD prime-contract query without recipient type restriction. The registered target sets the bounded snapshot resolutionDate to 2026-10-22; the official USAspending submission-period endpoint currently shows published periods only through FY2026 fiscal month 9, so the exact FY2026 year-end period was not yet visible there during this run.","Tool call: Opened USAspending API endpoint index and endpoint documentation for /api/v2/search/spending_over_time/ and /api/v2/references/submission_periods/."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-dod-small-business-contract-obligation-share-fy2026\nrunLabel: Headline\nresolutionDate: 2026-10-22\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-dhs-title-vi-award-transaction-obligations-fy2026.2026-08-07T19-32-23Z.98f452f97797868c","runId":"run.us-dhs-title-vi-award-transaction-obligations-fy2026.2026-08-07T19-32-23Z.98f452f97797868c","predictionId":"us-dhs-title-vi-award-transaction-obligations-fy2026","specId":"spec.us-dhs-title-vi-award-transaction-obligations-fy2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate / reference class: this is a lumpy multiyear appropriation drawdown target. The best outside-view anchor is the already-observed CBP drawdown pace: $11.3 billion in obligations by December 2025 from a $64.7-$64.8 billion account family, with other registered accounts adding smaller but still material grant/reimbursement channels. I do not use a same-series time-series prior because the exact FY2026 Title VI registered-account snapshot is a new policy-funded flow, so earlier fiscal years are not comparable to the FY2026 first-print obligation level.","Prior/update/interval: base prior is the observed CBP drawdown scale, not a direct persistence forecast. Historical/reference sample is $11.3B already obligated on CBP OBBA accounts, $64.8B CBP authority, $10.0B State Border authority, $2.58B FEMA assistance authority, and $0.75B FLETC authority. Adjustment components are CBP awards 15.0B + State Border 6.5B + FEMA assistance 2.3B + FLETC 0.5B + other first-print timing/rounding 0.5B = 24.8B. Interval method is an explicit component-error model for this lumpy first-print flow: CBP procurement uncertainty 4.0B, State Border timing uncertainty 3.0B, FEMA grant uncertainty 0.8B, FLETC uncertainty 0.2B, USAspending first-print reporting-lag uncertainty 1.0B; sigma = sqrt(4.0^2 + 3.0^2 + 0.8^2 + 0.2^2 + 1.0^2) = 5.19B, and 1.28*sigma = 6.64B. Therefore 24.8B +/- 6.64B gives 18.16B to 31.44B."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 6 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["Forecast for FY2026 DHS Title VI USAspending award transaction obligations","The resolver is the registered USAspending spending_over_time POST query, not a budget-account table: the resolving value is the FY2026 aggregated_amount for prime award transaction obligations across the registered DHS Treasury accounts 070-2025/2029-0530, 070-2025/2029-0532, 070-2025/2029-0509, 070-2025/2029-0510, 070-2025/2029-0413, and 070-0722. Public references sometimes describe 070-0722 as a 2025/2034 State Border Security Reinforcement Fund account; I keep the forecast tied to the registered 070-0722 target contract."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool result: The official submission_periods endpoint showed the 2026-06-01 to 2026-06-30 period with submission_start_date 2026-07-21, submission_due_date 2026-07-31, and certification_due_date 2026-08-15; the registered FY2026 P12 target resolves at the conservative 2026-10-22 bound for the October first-print snapshot.","Base rate / reference class: this is a lumpy multiyear appropriation drawdown target. The best outside-view anchor is the already-observed CBP drawdown pace: $11.3 billion in obligations by December 2025 from a $64.7-$64.8 billion account family, with other registered accounts adding smaller but still material grant/reimbursement channels. I do not use a same-series time-series prior because the exact FY2026 Title VI registered-account snapshot is a new policy-funded flow, so earlier fiscal years are not comparable to the FY2026 first-print obligation level."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 13280000000, distribution present, forecast step count 1.","evidence":["Prior/update/interval: base prior is the observed CBP drawdown scale, not a direct persistence forecast. Historical/reference sample is $11.3B already obligated on CBP OBBA accounts, $64.8B CBP authority, $10.0B State Border authority, $2.58B FEMA assistance authority, and $0.75B FLETC authority. Adjustment components are CBP awards 15.0B + State Border 6.5B + FEMA assistance 2.3B + FLETC 0.5B + other first-print timing/rounding 0.5B = 24.8B. Interval method is an explicit component-error model for this lumpy first-print flow: CBP procurement uncertainty 4.0B, State Border timing uncertainty 3.0B, FEMA grant uncertainty 0.8B, FLETC uncertainty 0.2B, USAspending first-print reporting-lag uncertainty 1.0B; sigma = sqrt(4.0^2 + 3.0^2 + 0.8^2 + 0.2^2 + 1.0^2) = 5.19B, and 1.28*sigma = 6.64B. Therefore 24.8B +/- 6.64B gives 18.16B to 31.44B.","Upside risk: rapid border-wall, screening-technology, or state reimbursement awards could add more than about $10B beyond the CBP base and push total obligations above 31.44B. Downside risk: procurement delays, low 070-0722 award execution, or October first-print reporting gaps could keep the CBP-plus-grants total below 18.16B, outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate / reference class: this is a lumpy multiyear appropriation drawdown target. The best outside-view anchor is the already-observed CBP drawdown pace: $11.3 billion in obligations by December 2025 from a $64.7-$64.8 billion account family, with other registered accounts adding smaller but still material grant/reimbursement channels. I do not use a same-series time-series prior because the exact FY2026 Title VI registered-account snapshot is a new policy-funded flow, so earlier fiscal years are not comparable to the FY2026 first-print obligation level."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate / reference class: this is a lumpy multiyear appropriation drawdown target. The best outside-view anchor is the already-observed CBP drawdown pace: $11.3 billion in obligations by December 2025 from a $64.7-$64.8 billion account family, with other registered accounts adding smaller but still material grant/reimbursement channels. I do not use a same-series time-series prior because the exact FY2026 Title VI registered-account snapshot is a new policy-funded flow, so earlier fiscal years are not comparable to the FY2026 first-print obligation level.","Prior/update/interval: base prior is the observed CBP drawdown scale, not a direct persistence forecast. Historical/reference sample is $11.3B already obligated on CBP OBBA accounts, $64.8B CBP authority, $10.0B State Border authority, $2.58B FEMA assistance authority, and $0.75B FLETC authority. Adjustment components are CBP awards 15.0B + State Border 6.5B + FEMA assistance 2.3B + FLETC 0.5B + other first-print timing/rounding 0.5B = 24.8B. Interval method is an explicit component-error model for this lumpy first-print flow: CBP procurement uncertainty 4.0B, State Border timing uncertainty 3.0B, FEMA grant uncertainty 0.8B, FLETC uncertainty 0.2B, USAspending first-print reporting-lag uncertainty 1.0B; sigma = sqrt(4.0^2 + 3.0^2 + 0.8^2 + 0.2^2 + 1.0^2) = 5.19B, and 1.28*sigma = 6.64B. Therefore 24.8B +/- 6.64B gives 18.16B to 31.44B."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for FY2026 DHS Title VI USAspending award transaction obligations","The resolver is the registered USAspending spending_over_time POST query, not a budget-account table: the resolving value is the FY2026 aggregated_amount for prime award transaction obligations across the registered DHS Treasury accounts 070-2025/2029-0530, 070-2025/2029-0532, 070-2025/2029-0509, 070-2025/2029-0510, 070-2025/2029-0413, and 070-0722. Public references sometimes describe 070-0722 as a 2025/2034 State Border Security Reinforcement Fund account; I keep the forecast tied to the registered 070-0722 target contract."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-dhs-title-vi-award-transaction-obligations-fy2026\nrunLabel: Headline\nresolutionDate: 2026-10-22\ntraceLineCount: 19\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.spm-child-poverty-rate-cy2027-threshold-one-dollar.2026-08-06T00-32-20Z.303cd844f1cc2e0d","runId":"run.spm-child-poverty-rate-cy2027-threshold-one-dollar.2026-08-06T00-32-20Z.303cd844f1cc2e0d","predictionId":"spm-child-poverty-rate-cy2027-threshold-one-dollar","specId":"spec.spm-child-poverty-rate-cy2027-threshold-one-dollar","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Tool result: PolicyEngine API policy 85587 sets gov.irs.credits.ctc.refundable.phase_in.threshold to 0 from 2026 onward, an economic approximation to statutory $1; baseline policy 2 is labeled Current law. The live 2027 economy request returned status=computing, so it supplies no finished 2027 estimate and increases uncertainty. The public 2026 model artifact (policyengine-us 1.764.6) reports child poverty 0.1701733 baseline versus 0.1682073 reform: change -0.001966, or -0.1966 percentage points; budgetary impact was -$1.8261 billion.","Base rate/reference class: the admissible current-method 2019–2024 Census first-print vector is 12.6%, 9.7%, 5.2%, 12.4%, 13.7%, and 13.4%; mean 11.17%, range 5.2%–13.7%. No official revised-methodology print or backcast was available, so the current-method vintage is used without fabricating a revision. The strongest benchmark is 2024 last-print persistence at 13.4%; the policy update is small relative to the historical dispersion."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["CY2027 Census child Supplemental Poverty Measure conditional forecast","Framing: the target is the first revised-methodology Census annual print for CY2027, Table B-2, ALL RACES, Under 18 years / Below Poverty / Percent. This annual household measure is not seasonally adjusted. The registered 2028-12-31 resolutionDate is a Thesis resolve-by bound, not a claimed release day."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing: the target is the first revised-methodology Census annual print for CY2027, Table B-2, ALL RACES, Under 18 years / Below Poverty / Percent. This annual household measure is not seasonally adjusted. The registered 2028-12-31 resolutionDate is a Thesis resolve-by bound, not a claimed release day.","Tool call: fetch_official_announcement({\"url\":\"https://www.census.gov/newsroom/press-releases/2026/statement-on-supplemental-poverty-measure.html\"})"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 12.8, distribution present, forecast step count 1.","evidence":["Tool result: {\"schemaVersion\":\"thesis_model_candidate_v1\",\"model\":\"persistence\",\"point\":13.4,\"p10\":7.6,\"p50\":13.4,\"p90\":19.2,\"ci80\":[7.6,19.2],\"ci90\":[5.9,20.9],\"intervalMethod\":\"empirical successive-change normal approximation\",\"calibration_n\":5,\"trainCutoff\":\"2024\",\"walkForwardScore\":{\"metric\":\"MAE\",\"value\":3.24}}. Fetched-history changes were -2.9, -4.5, +7.2, +1.3, and -0.3 percentage points.","Tool result: PolicyEngine API policy 85587 sets gov.irs.credits.ctc.refundable.phase_in.threshold to 0 from 2026 onward, an economic approximation to statutory $1; baseline policy 2 is labeled Current law. The live 2027 economy request returned status=computing, so it supplies no finished 2027 estimate and increases uncertainty. The public 2026 model artifact (policyengine-us 1.764.6) reports child poverty 0.1701733 baseline versus 0.1682073 reform: change -0.001966, or -0.1966 percentage points; budgetary impact was -$1.8261 billion."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior = 13.4%. PolicyEngine's direct model input gives -0.1966pp, rounded to a -0.2pp directional inside-view update; because the live 2027 economy run was unfinished, it is not treated as a completed 2027 estimate. No separate momentum or macro update is supported, so point = 13.4 - 0.2 = 13.2%. From fetched successive changes [-2.9, -4.5, 7.2, 1.3, -0.3], sample sigma = 4.5319pp. The nominal 80% half-width is 1.28*sigma = 1.28 × 4.5319 = 5.8008pp. Widen by 1.10 for the announced revised-methodology transition, the unfinished live 2027 PolicyEngine run, and the limitation of calibrating volatility from only five annual changes: 5.8008 × 1.10 = 6.3809pp. Thus 13.2 ± 6.3809 = [6.8191, 19.5809], published as [6.8, 19.6]. Four of the five observed annual moves—80%—fit within ±6.3809pp."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool result: PolicyEngine API policy 85587 sets gov.irs.credits.ctc.refundable.phase_in.threshold to 0 from 2026 onward, an economic approximation to statutory $1; baseline policy 2 is labeled Current law. The live 2027 economy request returned status=computing, so it supplies no finished 2027 estimate and increases uncertainty. The public 2026 model artifact (policyengine-us 1.764.6) reports child poverty 0.1701733 baseline versus 0.1682073 reform: change -0.001966, or -0.1966 percentage points; budgetary impact was -$1.8261 billion.","Mechanism and counter-consideration: the condition reaches very-low-earning families by starting the ACTC phase-in near the first dollar, but the unchanged 15% rate limits the mechanical gain to roughly $375 and nonfiling can prevent take-up. The modeled -0.2pp effect is therefore applied once, not double-counted with the 2021 expanded-CTC observation. Upside risk would land above the interval if the revised SPM methodology sharply raises measured child poverty while a recession substantially reduces low-income earnings. Downside risk would land below the interval if unexpectedly strong earnings combine with much broader refundable-credit legislation or unusually complete filing take-up."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["CY2027 Census child Supplemental Poverty Measure conditional forecast","Tool result: {\"schemaVersion\":\"thesis_model_candidate_v1\",\"model\":\"persistence\",\"point\":13.4,\"p10\":7.6,\"p50\":13.4,\"p90\":19.2,\"ci80\":[7.6,19.2],\"ci90\":[5.9,20.9],\"intervalMethod\":\"empirical successive-change normal approximation\",\"calibration_n\":5,\"trainCutoff\":\"2024\",\"walkForwardScore\":{\"metric\":\"MAE\",\"value\":3.24}}. Fetched-history changes were -2.9, -4.5, +7.2, +1.3, and -0.3 percentage points."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: spm-child-poverty-rate-cy2027-threshold-one-dollar\nrunLabel: Headline\nresolutionDate: 2028-12-31\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.spm-child-poverty-rate-cy2027-current-law.2026-08-06T00-36-05Z.2fab2a4c727323cc","runId":"run.spm-child-poverty-rate-cy2027-current-law.2026-08-06T00-36-05Z.2fab2a4c727323cc","predictionId":"spm-child-poverty-rate-cy2027-current-law","specId":"spec.spm-child-poverty-rate-cy2027-current-law","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the current official Table B-2 vintage is admissible because Census has not yet published any revised-methodology print or backcast. Across 2013-2024 the child SPM rate ranged from 5.2% to 18.1%; the latest six values were 12.6%, 9.7%, 5.2%, 12.4%, 13.7%, and 13.4%. Last-print persistence at 13.4% is the prior and beats the expanding-mean benchmark in walk-forward MAE, 1.97 versus 2.62 percentage points.","Prior/update/interval: persistence prior = 13.4% from the 2024 current-vintage official Table B-2 print; historical sample = 2013-2024 values 18.1, 17.1, 16.2, 15.2, 14.2, 13.7, 12.6, 9.7, 5.2, 12.4, 13.7, 13.4; adjustment components = 0.0 pp for the current-law threshold condition and 0.0 pp for unsupported momentum, so point = 13.4 + 0.0 + 0.0 = 13.4%. Successive changes are -1.0, -0.9, -1.0, -1.0, -0.5, -1.1, -2.9, -4.5, +7.2, +1.3, and -0.3 pp, giving sigma = 2.92 pp; 1.28*sigma = 3.74 pp. Widening by 1.36 for the multi-year horizon and announced methodology transition gives a 5.1 pp half-width, hence 13.4 ± 5.1 = [8.3, 18.5]%. This band would cover 11 of the 12 fetched annual levels."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Forecast for the CY2027 Census child Supplemental Poverty Measure rate under current law","Framing: resolve the first Census revised-methodology annual Table B-2 print for calendar year 2027, ALL RACES, Under 18 years, Below Poverty, Percent. This annual percentage is not seasonally adjusted. The registered 2028-12-31 date is a Thesis resolve-by bound, not a scheduled release date, and the announcement authenticates methodology identity only."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing: resolve the first Census revised-methodology annual Table B-2 print for calendar year 2027, ALL RACES, Under 18 years, Below Poverty, Percent. This annual percentage is not seasonally adjusted. The registered 2028-12-31 date is a Thesis resolve-by bound, not a scheduled release date, and the announcement authenticates methodology identity only.","Tool call: fetch_official_announcement({\"url\":\"https://www.census.gov/newsroom/press-releases/2026/statement-on-supplemental-poverty-measure.html\"})"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 10.2, distribution present, forecast step count 1.","evidence":["Tool result: Persistence candidate: point 13.4%, p10 8.3%, p50 13.4%, p90 18.5%, 80% interval [8.3%,18.5%], 90% interval [6.8%,20.0%], interval method successive-change Gaussian empirical-residual wrapper, calibration_n 11, train cutoff 2024, walk-forward MAE 1.97 pp. Expanding-mean benchmark walk-forward MAE was 2.62 pp, so persistence was stronger.","Level, momentum, one-off, and policy mechanism: the level is the latest 13.4% print; momentum is nearly flat from 13.7% in 2023 to 13.4% in 2024; the 2020-2022 transfer-policy cycle created exceptional moves and is retained in interval calibration; and the stated current-law condition leaves the $2,500 earned-income threshold unchanged, so the conditional policy update is 0.0 percentage points. No direct current signal supports moving materially from persistence. The Thesis specs citation was used only to verify target metadata and slug uniqueness, not as evidence for the forecast point or interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate/reference class: the current official Table B-2 vintage is admissible because Census has not yet published any revised-methodology print or backcast. Across 2013-2024 the child SPM rate ranged from 5.2% to 18.1%; the latest six values were 12.6%, 9.7%, 5.2%, 12.4%, 13.7%, and 13.4%. Last-print persistence at 13.4% is the prior and beats the expanding-mean benchmark in walk-forward MAE, 1.97 versus 2.62 percentage points.","Level, momentum, one-off, and policy mechanism: the level is the latest 13.4% print; momentum is nearly flat from 13.7% in 2023 to 13.4% in 2024; the 2020-2022 transfer-policy cycle created exceptional moves and is retained in interval calibration; and the stated current-law condition leaves the $2,500 earned-income threshold unchanged, so the conditional policy update is 0.0 percentage points. No direct current signal supports moving materially from persistence. The Thesis specs citation was used only to verify target metadata and slug uniqueness, not as evidence for the forecast point or interval."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool result: Official statutory text fetched: IRC §24(d)(1)(B)(i) uses an underlying earned-income amount of $3,000, while §24(h)(6) substitutes $2,500 for $3,000. The conditional therefore preserves the modeled current-law threshold at $2,500 and contributes a 0.0 percentage-point policy adjustment.","Counter-consideration: downside risk would land below the interval if Congress enacted a major refundable-credit expansion consistent with the condition but affecting another CTC parameter, or if labor-market strength and transfers reduced child poverty toward the 2021 trough. Upside risk would land above the interval if a recession sharply reduced family resources, benefits contracted materially, or the revised methodology raised measured child poverty by more than the historical calibration allows. Either tail could also arise from an unexpectedly large methodology discontinuity."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for the CY2027 Census child Supplemental Poverty Measure rate under current law","Tool result: Official statutory text fetched: IRC §24(d)(1)(B)(i) uses an underlying earned-income amount of $3,000, while §24(h)(6) substitutes $2,500 for $3,000. The conditional therefore preserves the modeled current-law threshold at $2,500 and contributes a 0.0 percentage-point policy adjustment."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: spm-child-poverty-rate-cy2027-current-law\nrunLabel: Headline\nresolutionDate: 2028-12-31\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.additional-child-tax-credit-total-claims-ty2027-threshold-one-dollar.2026-08-04T14-57-45Z.be85da61fc2dc683","runId":"run.additional-child-tax-credit-total-claims-ty2027-threshold-one-dollar.2026-08-04T14-57-45Z.be85da61fc2dc683","predictionId":"additional-child-tax-credit-total-claims-ty2027-threshold-one-dollar","specId":"spec.additional-child-tax-credit-total-claims-ty2027-threshold-one-dollar","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the four most recent available exact-series first prints are 19.119249, 37.771612, 18.076696, and 17.626084 million. Their mean is 23.148410 million, median 18.597972 million, range 17.626084–37.771612 million, and last-print persistence benchmark is 17.626084 million. The 2021 observation is a policy-regime precedent rather than a clean estimate of the $1-threshold effect.","Prior/update/interval: persistence prior = 17.626084 million using TY2020–TY2023 official first prints. The TY2021 excess over the mean of TY2020 and TY2022 is 37.771612 - (19.119249 + 18.076696)/2 = 19.173640 million. Because that precedent bundles other policy differences, apply a judgmental 50% shrinkage assumption rather than a fitted estimate: policy update = 0.50 × 19.173640 = 9.586820 million; momentum update = 0; one-off update = 0. Point = 17.626084 + 9.586820 = 27.212904, rounded to 27.2 million. For this annual flow series, the sample standard deviation of the four observed levels is sigma = 9.768837 million. The empirical-level interval method gives 80% half-width = 1.28*sigma = 12.504112 million, so implied bounds are 27.212904 ± 12.504112 = [14.708792, 39.717015], rounded to [14.7, 39.7]. This interval would contain all four fetched prints, including the high-policy-regime TY2021 observation."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 7 source-context item(s), activity log present.","evidence":["Tool call: Fetch and parse official IRS workbooks 20in33ar.xls and 21in33ar.xls through the registered irs-soi-pub1304 adapter.","Tool result: Official Table 3.3 whole-return counts fetched 2026-08-04: TY2020 = 19,119,249, transformed by 1e-6 to 19.119249 million (103,424-byte workbook), and TY2021 = 37,771,612, transformed by 1e-6 to 37.771612 million (113,664-byte workbook)."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing: the target is the first IRS SOI Publication 1304 Table 3.3 print for TY2027, all returns total, refundable child tax credit or additional child tax credit, number of returns. It is an annual, not-seasonally-adjusted flow count. The registered IRS-source window is 2029-01-01 through 2029-12-31 and fixes the by-date resolutionDate at 2029-12-31. The condition is evaluated on 2027-12-31; a failed condition leaves this arm unresolved.","Tool result: TY2024 returned no published workbook and therefore no value as of 2026-08-04: value = null and fetched bytes = 0. TY2023 remains the latest available official print."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 25, distribution present, forecast step count 1.","evidence":["Tool call: Generate a persistence candidate from the four live-parsed IRS observations, using empirical flow-level dispersion for intervals.","Tool result: Candidate persistence: point = 17.626084 million; p10 = 5.121972, p50 = 17.626084, p90 = 30.130196; 80% interval = [5.121972, 30.130196]; 90% interval = [1.556347, 33.695821]; interval_method = empirical-level-sigma normal wrapper; calibration_n = 4; train_cutoff = TY2023; walk_forward_MAE = 12.932630 million. The candidate is the unconditional benchmark but is overridden because the question conditions on a material statutory change."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: Candidate persistence: point = 17.626084 million; p10 = 5.121972, p50 = 17.626084, p90 = 30.130196; 80% interval = [5.121972, 30.130196]; 90% interval = [1.556347, 33.695821]; interval_method = empirical-level-sigma normal wrapper; calibration_n = 4; train_cutoff = TY2023; walk_forward_MAE = 12.932630 million. The candidate is the unconditional benchmark but is overridden because the question conditions on a material statutory change.","Prior/update/interval: persistence prior = 17.626084 million using TY2020–TY2023 official first prints. The TY2021 excess over the mean of TY2020 and TY2022 is 37.771612 - (19.119249 + 18.076696)/2 = 19.173640 million. Because that precedent bundles other policy differences, apply a judgmental 50% shrinkage assumption rather than a fitted estimate: policy update = 0.50 × 19.173640 = 9.586820 million; momentum update = 0; one-off update = 0. Point = 17.626084 + 9.586820 = 27.212904, rounded to 27.2 million. For this annual flow series, the sample standard deviation of the four observed levels is sigma = 9.768837 million. The empirical-level interval method gives 80% half-width = 1.28*sigma = 12.504112 million, so implied bounds are 27.212904 ± 12.504112 = [14.708792, 39.717015], rounded to [14.7, 39.7]. This interval would contain all four fetched prints, including the high-policy-regime TY2021 observation."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool result: Candidate persistence: point = 17.626084 million; p10 = 5.121972, p50 = 17.626084, p90 = 30.130196; 80% interval = [5.121972, 30.130196]; 90% interval = [1.556347, 33.695821]; interval_method = empirical-level-sigma normal wrapper; calibration_n = 4; train_cutoff = TY2023; walk_forward_MAE = 12.932630 million. The candidate is the unconditional benchmark but is overridden because the question conditions on a material statutory change.","Mechanism and counter-consideration: lowering the threshold makes low-earned-income returns eligible for some refundable credit, increasing claimant counts, but the amount and take-up depend on earnings, qualifying children, filing behavior, and other TY2027 credit parameters. Upside risk would land above the interval if near-universal filing and take-up among newly eligible families produces an expansion larger than the fetched TY2021 claimant-count precedent. Downside risk would land below the interval if the enacted provision is paired with restrictive eligibility rules or unusually weak filing take-up, leaving claims below 14.7 million."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["ACTC total claimant-return forecast for tax year 2027 under the registered $1-threshold condition","Tool call: Generate a persistence candidate from the four live-parsed IRS observations, using empirical flow-level dispersion for intervals."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: additional-child-tax-credit-total-claims-ty2027-threshold-one-dollar\nrunLabel: Headline\nresolutionDate: 2029-12-31\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.additional-child-tax-credit-total-claims-ty2027-current-law.2026-08-04T15-02-49Z.08d6ec65ebf2350c","runId":"run.additional-child-tax-credit-total-claims-ty2027-current-law.2026-08-04T15-02-49Z.08d6ec65ebf2350c","predictionId":"additional-child-tax-credit-total-claims-ty2027-current-law","specId":"spec.additional-child-tax-credit-total-claims-ty2027-current-law","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the four exact-series first prints for TY2020–TY2023 are 19.119249, 37.771612, 18.076696, and 17.626084 million; these match the registered adapter's verified anchors. Their mean = 23.148410 million, median = 18.597972 million, and range = 17.626084–37.771612 million. TY2021 is a conspicuous policy-regime outlier, but it remains in interval calibration rather than being discarded.","Benchmark and model candidates: latest first-print persistence forecasts 17.626084 million. The thesis_model_candidate_v1 persistence candidate has point/p50 = 17.626084, p10 = 5.121972, p90 = 30.130196, 80% interval = [5.121972, 30.130196], 90% interval = [1.556347, 33.695821], intervalMethod = fallback-prior empirical level dispersion, calibration_n = 4, train cutoff = TY2023, and walk-forward MAE = 12.932630 million across the three available transitions. More elaborate time-series fitting is rejected because four observations with a major TY2021 regime break do not support stable parameter estimation. Persistence is selected."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 7 source-context item(s), activity log present.","evidence":["Framing: this is the not-seasonally-adjusted number of claimant returns, not credit dollars or children. It resolves on the first TY2027 IRS SOI Publication 1304 Table 3.3 print. The ledger supplies only an expected 2029-01-01 through 2029-12-31 release window, not an exact IRS calendar day; the registered 2029-12-31 deadline is therefore preserved and this discrepancy is disclosed rather than silently converted into a claimed scheduled date.","Tool call: Parse official Publication 1304 Table 3.3 workbooks 20in33ar.xls and 21in33ar.xls with the registered irs.actc.total_claims adapter."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing: this is the not-seasonally-adjusted number of claimant returns, not credit dollars or children. It resolves on the first TY2027 IRS SOI Publication 1304 Table 3.3 print. The ledger supplies only an expected 2029-01-01 through 2029-12-31 release window, not an exact IRS calendar day; the registered 2029-12-31 deadline is therefore preserved and this discrepancy is disclosed rather than silently converted into a claimed scheduled date.","Tool result: Official first-print whole-return counts fetched and parsed this run: TY2020 = 19,119,249 (19.119249 million), retrieved 2026-08-04T14:59:09Z; TY2021 = 37,771,612 (37.771612 million), retrieved 2026-08-04T14:59:10Z."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 25.01, distribution present, forecast step count 1.","evidence":["Base rate/reference class: the four exact-series first prints for TY2020–TY2023 are 19.119249, 37.771612, 18.076696, and 17.626084 million; these match the registered adapter's verified anchors. Their mean = 23.148410 million, median = 18.597972 million, and range = 17.626084–37.771612 million. TY2021 is a conspicuous policy-regime outlier, but it remains in interval calibration rather than being discarded.","Benchmark and model candidates: latest first-print persistence forecasts 17.626084 million. The thesis_model_candidate_v1 persistence candidate has point/p50 = 17.626084, p10 = 5.121972, p90 = 30.130196, 80% interval = [5.121972, 30.130196], 90% interval = [1.556347, 33.695821], intervalMethod = fallback-prior empirical level dispersion, calibration_n = 4, train cutoff = TY2023, and walk-forward MAE = 12.932630 million across the three available transitions. More elaborate time-series fitting is rejected because four observations with a major TY2021 regime break do not support stable parameter estimation. Persistence is selected."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Benchmark and model candidates: latest first-print persistence forecasts 17.626084 million. The thesis_model_candidate_v1 persistence candidate has point/p50 = 17.626084, p10 = 5.121972, p90 = 30.130196, 80% interval = [5.121972, 30.130196], 90% interval = [1.556347, 33.695821], intervalMethod = fallback-prior empirical level dispersion, calibration_n = 4, train cutoff = TY2023, and walk-forward MAE = 12.932630 million across the three available transitions. More elaborate time-series fitting is rejected because four observations with a major TY2021 regime break do not support stable parameter estimation. Persistence is selected.","Prior/update/interval: prior = TY2023 persistence = 17.626084 million, using the four TY2020–TY2023 official first prints. Adjustment components = 0.000000 million for momentum, 0.000000 million for one-offs, and 0.000000 million for policy because the forecast is explicitly conditional on the registered current-law threshold remaining operative and no direct TY2027 filing signal was fetched. Prior weight = 100%; update weight = 0%. For this annual claimant-return flow series, realized level dispersion is sigma = sample_std(19.119249, 37.771612, 18.076696, 17.626084) = 9.768837 million. The 80% half-width is 1.28*sigma = 12.504112 million, so 17.626084 - 12.504112 = 5.121972 and 17.626084 + 12.504112 = 30.130196 million. The interval method is fallback-prior empirical level dispersion; all 4 of 4 historical prints fall within these same-width bounds around the persistence point."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: the four exact-series first prints for TY2020–TY2023 are 19.119249, 37.771612, 18.076696, and 17.626084 million; these match the registered adapter's verified anchors. Their mean = 23.148410 million, median = 18.597972 million, and range = 17.626084–37.771612 million. TY2021 is a conspicuous policy-regime outlier, but it remains in interval calibration rather than being discarded.","Inside-view restraint: the current-law condition identifies the arm but supplies no direct evidence that TY2027 claimant counts will differ from the latest exact-series print. The dramatic TY2021 value demonstrates policy sensitivity and justifies uncertainty, but using that temporary regime as a directional update under the stated current-law arm would double-count a mechanism not shown to persist."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["TY2027 current-law ACTC claimant-return forecast","Base rate/reference class: the four exact-series first prints for TY2020–TY2023 are 19.119249, 37.771612, 18.076696, and 17.626084 million; these match the registered adapter's verified anchors. Their mean = 23.148410 million, median = 18.597972 million, and range = 17.626084–37.771612 million. TY2021 is a conspicuous policy-regime outlier, but it remains in interval calibration rather than being discarded."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: additional-child-tax-credit-total-claims-ty2027-current-law\nrunLabel: Headline\nresolutionDate: 2029-12-31\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.jolts-hires-rate-july-2026.2026-07-31T18-11-41Z.e0758911bf796542","runId":"run.jolts-hires-rate-july-2026.2026-07-31T18-11-41Z.e0758911bf796542","predictionId":"jolts-hires-rate-july-2026","specId":"spec.jolts-hires-rate-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: since early 2024 the total nonfarm seasonally adjusted hires rate has mostly sat in a narrow 3.2 to 3.6 percent band, with July 2025 at 3.3 percent and the latest May 2026 print also 3.3 percent. That makes a persistence base rate around 3.3 percent the right starting point.","Prior/update/interval: persistence prior = latest May 2026 value of 3.3 percent, with a small level adjustment of 0.0 because BLS described hires as unchanged and recent churn indicators were stable; momentum adjustment = 0.0 because Apr-to-May was 0.0 and the recent 3-month average is about (3.5+3.3+3.3)/3 = 3.37, which rounds near 3.3; one-off/policy adjustment = 0.0 because there is no official-source evidence of a July hiring regime break. For the 2024-01 to 2026-05 fetched window, target-horizon two-month changes have sample sigma = 0.17 percentage point; 80 percent half-width = 1.28*sigma = 1.28*0.17 = 0.218 percentage point, rounded to the one-decimal target as about 0.2. Final implied bounds: 3.3 - 0.2 = 3.1 and 3.3 + 0.2 = 3.5."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this forecast is for the BLS JOLTS seasonally adjusted total nonfarm hires rate, series JTS000000000000000HIR, mirrored as ALFRED/FRED JTSHIR, for reference month July 2026. The release variant is seasonally adjusted, total nonfarm, rate, first print, in percent rounded to one decimal.","Tool call: Checked the BLS JOLTS release schedule page for the reference-month release date."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["US JOLTS total nonfarm hires rate, July 2026 first print","Framing and exact resolver: this forecast is for the BLS JOLTS seasonally adjusted total nonfarm hires rate, series JTS000000000000000HIR, mirrored as ALFRED/FRED JTSHIR, for reference month July 2026. The release variant is seasonally adjusted, total nonfarm, rate, first print, in percent rounded to one decimal."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.4, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = latest May 2026 value of 3.3 percent, with a small level adjustment of 0.0 because BLS described hires as unchanged and recent churn indicators were stable; momentum adjustment = 0.0 because Apr-to-May was 0.0 and the recent 3-month average is about (3.5+3.3+3.3)/3 = 3.37, which rounds near 3.3; one-off/policy adjustment = 0.0 because there is no official-source evidence of a July hiring regime break. For the 2024-01 to 2026-05 fetched window, target-horizon two-month changes have sample sigma = 0.17 percentage point; 80 percent half-width = 1.28*sigma = 1.28*0.17 = 0.218 percentage point, rounded to the one-decimal target as about 0.2. Final implied bounds: 3.3 - 0.2 = 3.1 and 3.3 + 0.2 = 3.5.","Counter-considerations: upside risk would come from summer leisure, retail, or government hiring rebounding enough to push the rounded first print to 3.6 or higher, which would land above the interval. Downside risk would come from a broad hiring freeze or sharp payroll slowdown pushing the first print to 3.0 or lower, which would land outside the interval below. The middle case is that low churn persists and July rounds to 3.3."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior = latest May 2026 value of 3.3 percent, with a small level adjustment of 0.0 because BLS described hires as unchanged and recent churn indicators were stable; momentum adjustment = 0.0 because Apr-to-May was 0.0 and the recent 3-month average is about (3.5+3.3+3.3)/3 = 3.37, which rounds near 3.3; one-off/policy adjustment = 0.0 because there is no official-source evidence of a July hiring regime break. For the 2024-01 to 2026-05 fetched window, target-horizon two-month changes have sample sigma = 0.17 percentage point; 80 percent half-width = 1.28*sigma = 1.28*0.17 = 0.218 percentage point, rounded to the one-decimal target as about 0.2. Final implied bounds: 3.3 - 0.2 = 3.1 and 3.3 + 0.2 = 3.5."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-considerations: upside risk would come from summer leisure, retail, or government hiring rebounding enough to push the rounded first print to 3.6 or higher, which would land above the interval. Downside risk would come from a broad hiring freeze or sharp payroll slowdown pushing the first print to 3.0 or lower, which would land outside the interval below. The middle case is that low churn persists and July rounds to 3.3."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Framing and exact resolver: this forecast is for the BLS JOLTS seasonally adjusted total nonfarm hires rate, series JTS000000000000000HIR, mirrored as ALFRED/FRED JTSHIR, for reference month July 2026. The release variant is seasonally adjusted, total nonfarm, rate, first print, in percent rounded to one decimal.","Reference class and base rate: since early 2024 the total nonfarm seasonally adjusted hires rate has mostly sat in a narrow 3.2 to 3.6 percent band, with July 2025 at 3.3 percent and the latest May 2026 print also 3.3 percent. That makes a persistence base rate around 3.3 percent the right starting point."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: jolts-hires-rate-july-2026\nrunLabel: Headline\nresolutionDate: 2026-09-01\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-eci-private-wages-salaries-q3-2026.2026-07-31T18-16-29Z.8bb338abd6b0f15b","runId":"run.us-eci-private-wages-salaries-q3-2026.2026-07-31T18-16-29Z.8bb338abd6b0f15b","predictionId":"us-eci-private-wages-salaries-q3-2026","specId":"spec.us-eci-private-wages-salaries-q3-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: the direct reference class is recent first-print seasonally adjusted BLS Table 2 quarter-over-quarter private wage ECI changes. The last 9 printed changes average about 0.82 percent, and the last 5 values are 1.0, 0.8, 0.7, 0.7, and 0.9, so the base rate is a persistent 0.8 percent rather than a sharp acceleration or collapse.","Prior/update/interval: persistence prior is the last-9-quarter BLS Table 2 private wage q/q sample: [0.8, 0.8, 0.9, 0.8, 1.0, 0.8, 0.7, 0.7, 0.9], mean = 7.4/9 = 0.82; sigma = 0.10 percentage points from those values; 1.28*sigma = 0.12 percentage points, so an 80% interval around 0.82 is about 0.70 to 0.94, widened trivially to 0.69 to 0.95 for first-print/index-rounding uncertainty. Adjustment components: +0.02 for Q2 momentum after the 0.9 print, -0.02 for payroll cooling and steady 3.5 percent AHE growth, net 0.00, leaving point = 0.82."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing and exact resolver: the target is the BLS Employment Cost Index Table 2 seasonally adjusted quarter-over-quarter percent growth for wages and salaries, Private industry workers, All workers, for the quarter ended September 2026. The ledger resolver is the ALFRED/FRED ECIWAG first-print index vintage, with BLS Table 2 as the underlying official release table.","Tool call: BLS Employment Cost Index release schedule lookup"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["US ECI private wages and salaries, 2026 Q3 first print","Framing and exact resolver: the target is the BLS Employment Cost Index Table 2 seasonally adjusted quarter-over-quarter percent growth for wages and salaries, Private industry workers, All workers, for the quarter ended September 2026. The ledger resolver is the ALFRED/FRED ECIWAG first-print index vintage, with BLS Table 2 as the underlying official release table."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.26, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is the last-9-quarter BLS Table 2 private wage q/q sample: [0.8, 0.8, 0.9, 0.8, 1.0, 0.8, 0.7, 0.7, 0.9], mean = 7.4/9 = 0.82; sigma = 0.10 percentage points from those values; 1.28*sigma = 0.12 percentage points, so an 80% interval around 0.82 is about 0.70 to 0.94, widened trivially to 0.69 to 0.95 for first-print/index-rounding uncertainty. Adjustment components: +0.02 for Q2 momentum after the 0.9 print, -0.02 for payroll cooling and steady 3.5 percent AHE growth, net 0.00, leaving point = 0.82.","Counter-considerations: upside risk is renewed wage pressure in health care, construction, or incentive-heavy occupations that would land above the interval near 1.0 percent or higher. Downside risk is broader labor-market weakening, retail and leisure pay softness, or lower bonuses pulling private wage growth toward 0.6 percent, which would land below the interval. An outside the interval result would likely require a visible shift in labor demand or compensation mix rather than ordinary quarter-to-quarter noise."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior is the last-9-quarter BLS Table 2 private wage q/q sample: [0.8, 0.8, 0.9, 0.8, 1.0, 0.8, 0.7, 0.7, 0.9], mean = 7.4/9 = 0.82; sigma = 0.10 percentage points from those values; 1.28*sigma = 0.12 percentage points, so an 80% interval around 0.82 is about 0.70 to 0.94, widened trivially to 0.69 to 0.95 for first-print/index-rounding uncertainty. Adjustment components: +0.02 for Q2 momentum after the 0.9 print, -0.02 for payroll cooling and steady 3.5 percent AHE growth, net 0.00, leaving point = 0.82.","Level, momentum, and mechanism: the ECIWAG index level rose from 177.498 to 179.010 in Q2, confirming wage growth remained firm. Momentum is still in the 0.7 to 0.9 band, while slower payroll growth and unemployment at 4.2 percent argue against a sustained jump above 1 percent."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence prior is the last-9-quarter BLS Table 2 private wage q/q sample: [0.8, 0.8, 0.9, 0.8, 1.0, 0.8, 0.7, 0.7, 0.9], mean = 7.4/9 = 0.82; sigma = 0.10 percentage points from those values; 1.28*sigma = 0.12 percentage points, so an 80% interval around 0.82 is about 0.70 to 0.94, widened trivially to 0.69 to 0.95 for first-print/index-rounding uncertainty. Adjustment components: +0.02 for Q2 momentum after the 0.9 print, -0.02 for payroll cooling and steady 3.5 percent AHE growth, net 0.00, leaving point = 0.82.","Counter-considerations: upside risk is renewed wage pressure in health care, construction, or incentive-heavy occupations that would land above the interval near 1.0 percent or higher. Downside risk is broader labor-market weakening, retail and leisure pay softness, or lower bonuses pulling private wage growth toward 0.6 percent, which would land below the interval. An outside the interval result would likely require a visible shift in labor demand or compensation mix rather than ordinary quarter-to-quarter noise."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: persistence prior is the last-9-quarter BLS Table 2 private wage q/q sample: [0.8, 0.8, 0.9, 0.8, 1.0, 0.8, 0.7, 0.7, 0.9], mean = 7.4/9 = 0.82; sigma = 0.10 percentage points from those values; 1.28*sigma = 0.12 percentage points, so an 80% interval around 0.82 is about 0.70 to 0.94, widened trivially to 0.69 to 0.95 for first-print/index-rounding uncertainty. Adjustment components: +0.02 for Q2 momentum after the 0.9 print, -0.02 for payroll cooling and steady 3.5 percent AHE growth, net 0.00, leaving point = 0.82.","Counter-considerations: upside risk is renewed wage pressure in health care, construction, or incentive-heavy occupations that would land above the interval near 1.0 percent or higher. Downside risk is broader labor-market weakening, retail and leisure pay softness, or lower bonuses pulling private wage growth toward 0.6 percent, which would land below the interval. An outside the interval result would likely require a visible shift in labor demand or compensation mix rather than ordinary quarter-to-quarter noise."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-eci-private-wages-salaries-q3-2026\nrunLabel: Headline\nresolutionDate: 2026-10-30\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-unit-labor-costs-q3-2026-prelim.2026-07-31T18-18-37Z.ce4c95589c9d089e","runId":"run.us-unit-labor-costs-q3-2026-prelim.2026-07-31T18-18-37Z.ce4c95589c9d089e","predictionId":"us-unit-labor-costs-q3-2026-prelim","specId":"spec.us-unit-labor-costs-q3-2026-prelim","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 8 historical point(s) and explicit outside-view language.","evidence":["Framing and exact resolver: this is the BLS Productivity and Costs nonfarm business sector unit labor costs series, quarterly percent change from the previous quarter at a seasonally adjusted annualized rate, first print for 2026 Q3. The release and all historical anchors below use the same preliminary-release variant rather than revised database values.","The base rate/reference class is the eight most recent available same-variant preliminary nonfarm business ULC prints: 0.9, 1.9, 3.0, 5.7, 1.6, -1.9, 2.8, and 2.3 percent. Their mean is 2.04 percent; persistence from 2026-Q1 is 2.3 percent, so both point to a low-to-mid 2 percent forecast before current-quarter specifics."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 10 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this is the BLS Productivity and Costs nonfarm business sector unit labor costs series, quarterly percent change from the previous quarter at a seasonally adjusted annualized rate, first print for 2026 Q3. The release and all historical anchors below use the same preliminary-release variant rather than revised database values.","Resolver alignment: the official statistical release is the BLS Productivity and Costs preliminary release, while the canonical ledger sourceBinding resolves through ALFRED/FRED series PRS85006112 with releasePolicy first_print. I keep the canonical slug and dataPointId and set the resolution URL to the ledger ALFRED series while naming the underlying BLS release in the rule."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this is the BLS Productivity and Costs nonfarm business sector unit labor costs series, quarterly percent change from the previous quarter at a seasonally adjusted annualized rate, first print for 2026 Q3. The release and all historical anchors below use the same preliminary-release variant rather than revised database values.","Resolver alignment: the official statistical release is the BLS Productivity and Costs preliminary release, while the canonical ledger sourceBinding resolves through ALFRED/FRED series PRS85006112 with releasePolicy first_print. I keep the canonical slug and dataPointId and set the resolution URL to the ledger ALFRED series while naming the underlying BLS release in the rule."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5.4, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = 2.3 from the latest same-variant 2026-Q1 preliminary print; historical sample = the eight preliminary prints from 2024-Q2 through 2026-Q1 with mean 2.04. Adjustment components: +0.2 for compensation growth staying positive, +0.1 for uncertainty before the not-yet-released Q2 productivity print, and -0.2 for the tendency of stronger productivity to offset hourly compensation in this series, giving point = 2.4. For a change/flow series, sigma is computed from the values themselves: sample standard deviation of [0.9, 1.9, 3.0, 5.7, 1.6, -1.9, 2.8, 2.3] gives sigma = 2.14. The 80 percent normal half-width is 1.28*sigma = 1.28*2.14 = 2.74, rounded to 2.7, so bounds are 2.4 - 2.7 = -0.3 and 2.4 + 2.7 = 5.1.","Eight same-variant first prints are a short but clean reference class; using a longer revised database history would mix vintages and understate the exact first-print target noise. The interval is therefore tied to preliminary-print dispersion, and revision-prone tails remain the main residual risk."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence prior = 2.3 from the latest same-variant 2026-Q1 preliminary print; historical sample = the eight preliminary prints from 2024-Q2 through 2026-Q1 with mean 2.04. Adjustment components: +0.2 for compensation growth staying positive, +0.1 for uncertainty before the not-yet-released Q2 productivity print, and -0.2 for the tendency of stronger productivity to offset hourly compensation in this series, giving point = 2.4. For a change/flow series, sigma is computed from the values themselves: sample standard deviation of [0.9, 1.9, 3.0, 5.7, 1.6, -1.9, 2.8, 2.3] gives sigma = 2.14. The 80 percent normal half-width is 1.28*sigma = 1.28*2.14 = 2.74, rounded to 2.7, so bounds are 2.4 - 2.7 = -0.3 and 2.4 + 2.7 = 5.1.","Eight same-variant first prints are a short but clean reference class; using a longer revised database history would mix vintages and understate the exact first-print target noise. The interval is therefore tied to preliminary-print dispersion, and revision-prone tails remain the main residual risk."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Resolver alignment: the official statistical release is the BLS Productivity and Costs preliminary release, while the canonical ledger sourceBinding resolves through ALFRED/FRED series PRS85006112 with releasePolicy first_print. I keep the canonical slug and dataPointId and set the resolution URL to the ledger ALFRED series while naming the underlying BLS release in the rule.","The base rate/reference class is the eight most recent available same-variant preliminary nonfarm business ULC prints: 0.9, 1.9, 3.0, 5.7, 1.6, -1.9, 2.8, and 2.3 percent. Their mean is 2.04 percent; persistence from 2026-Q1 is 2.3 percent, so both point to a low-to-mid 2 percent forecast before current-quarter specifics."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-unit-labor-costs-q3-2026-prelim\nrunLabel: Headline\nresolutionDate: 2026-11-05\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-housing-completions-july-2026.2026-07-31T14-52-42Z.004d8c0b56f796f6","runId":"run.us-housing-completions-july-2026.2026-07-31T14-52-42Z.004d8c0b56f796f6","predictionId":"us-housing-completions-july-2026","specId":"spec.us-housing-completions-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: for this same SAAR variant, the near-term reference class is month-to-month changes in recent total completions. A persistence base rate around the latest print, 1,392 thousand, is more informative than the 2025 July level because completions are volatile and the July first print is a one-month SAAR estimate.","Prior/update/interval: persistence prior is June 2026 total completions SAAR = 1,392. Historical sample is the official January-June 2026 Census Table 5a sequence 1,439, 1,324, 1,373, 1,454, 1,347, 1,392, giving successive changes -115, +49, +81, -107, +45; sample sigma = 94 thousand. Adjustment components: -20 thousand for weak 2026 year-to-date NSA completions versus 2025, +10 thousand for high single-family completions, +8 thousand for June starts rebound and still-large under-construction stock, net about -2 thousand from persistence. Point = 1,390. 80% half-width = 1.28*sigma = 1.28*94 = 120 thousand, so bounds are 1,390 - 120 = 1,270 and 1,390 + 120 = 1,510."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["US July 2026 housing completions SAAR first print","Framing and exact resolver: this forecasts Census/HUD New Residential Construction privately-owned housing completions, seasonally adjusted annual rate, total United States, July 2026, in thousands. The official release is Census/HUD; the registered resolution mirror is ALFRED/FRED sourceSeriesId COMPUTSA under first_print policy, so I keep the final rule tied to that first-vintage target."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["US July 2026 housing completions SAAR first print","Framing and exact resolver: this forecasts Census/HUD New Residential Construction privately-owned housing completions, seasonally adjusted annual rate, total United States, July 2026, in thousands. The official release is Census/HUD; the registered resolution mirror is ALFRED/FRED sourceSeriesId COMPUTSA under first_print policy, so I keep the final rule tied to that first-vintage target."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 240, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is June 2026 total completions SAAR = 1,392. Historical sample is the official January-June 2026 Census Table 5a sequence 1,439, 1,324, 1,373, 1,454, 1,347, 1,392, giving successive changes -115, +49, +81, -107, +45; sample sigma = 94 thousand. Adjustment components: -20 thousand for weak 2026 year-to-date NSA completions versus 2025, +10 thousand for high single-family completions, +8 thousand for June starts rebound and still-large under-construction stock, net about -2 thousand from persistence. Point = 1,390. 80% half-width = 1.28*sigma = 1.28*94 = 120 thousand, so bounds are 1,390 - 120 = 1,270 and 1,390 + 120 = 1,510.","Counter-considerations: upside risk would come from June's 1,427 thousand starts rebound pulling through quickly or multifamily completions normalizing upward, which would land above the interval if the first print exceeds 1,510 thousand. Downside risk is a renewed multifamily completion drop or seasonal adjustment reversal after June's single-family strength, which would land below the interval if the first print is under 1,270 thousand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Reference class and base rate: for this same SAAR variant, the near-term reference class is month-to-month changes in recent total completions. A persistence base rate around the latest print, 1,392 thousand, is more informative than the 2025 July level because completions are volatile and the July first print is a one-month SAAR estimate."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-considerations: upside risk would come from June's 1,427 thousand starts rebound pulling through quickly or multifamily completions normalizing upward, which would land above the interval if the first print exceeds 1,510 thousand. Downside risk is a renewed multifamily completion drop or seasonal adjustment reversal after June's single-family strength, which would land below the interval if the first print is under 1,270 thousand."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Framing and exact resolver: this forecasts Census/HUD New Residential Construction privately-owned housing completions, seasonally adjusted annual rate, total United States, July 2026, in thousands. The official release is Census/HUD; the registered resolution mirror is ALFRED/FRED sourceSeriesId COMPUTSA under first_print policy, so I keep the final rule tied to that first-vintage target.","Prior/update/interval: persistence prior is June 2026 total completions SAAR = 1,392. Historical sample is the official January-June 2026 Census Table 5a sequence 1,439, 1,324, 1,373, 1,454, 1,347, 1,392, giving successive changes -115, +49, +81, -107, +45; sample sigma = 94 thousand. Adjustment components: -20 thousand for weak 2026 year-to-date NSA completions versus 2025, +10 thousand for high single-family completions, +8 thousand for June starts rebound and still-large under-construction stock, net about -2 thousand from persistence. Point = 1,390. 80% half-width = 1.28*sigma = 1.28*94 = 120 thousand, so bounds are 1,390 - 120 = 1,270 and 1,390 + 120 = 1,510."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-housing-completions-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-18\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-export-prices-mom-july-2026.2026-07-31T14-55-19Z.d6f07baee344581b","runId":"run.us-export-prices-mom-july-2026.2026-07-31T14-55-19Z.d6f07baee344581b","predictionId":"us-export-prices-mom-july-2026","specId":"spec.us-export-prices-mom-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate / reference class: use the nonmissing BLS all-export monthly percent changes shown in the latest release table from June 2025 through June 2026, excluding missing lapse months: 0.5, 0.3, 0.1, 0.0, 0.6, 0.5, 1.9, 1.7, 3.5, 1.2, -0.6. The sample mean is 0.88 percent and the median is 0.5 percent.","Prior/update/interval: persistence prior is the recent reference-class median of +0.5 percent, with the mean +0.88 pulled down because the spring surge of +1.9, +1.7, +3.5, and +1.2 was followed by a June reversal of -0.6. I apply -0.2 percentage point for mean reversion after the spring spike and +0.1 percentage point for July energy/industrial-supplies upside, giving a point forecast of +0.4 percent. For the 80% interval, use the values themselves for this change series; from the 11 nonmissing BLS monthly changes, sigma = 1.14 percentage points, so 1.28*sigma = 1.46 percentage points. Rounding the half-width to 1.5 gives +0.4 +/- 1.5, or [-1.1, 1.9]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["Forecast for BLS all-commodities export prices, July 2026 first print","The resolver is the BLS not seasonally adjusted Export Price Index (End Use): All commodities, Table 2, first-print monthly percent change for July 2026. The BLS August 2026 release calendar lists U.S. Import and Export Price Indexes for July 2026 on August 18, 2026 at 08:30 Eastern, matching the ledger date."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast for BLS all-commodities export prices, July 2026 first print","The resolver is the BLS not seasonally adjusted Export Price Index (End Use): All commodities, Table 2, first-print monthly percent change for July 2026. The BLS August 2026 release calendar lists U.S. Import and Export Price Indexes for July 2026 on August 18, 2026 at 08:30 Eastern, matching the ledger date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is the recent reference-class median of +0.5 percent, with the mean +0.88 pulled down because the spring surge of +1.9, +1.7, +3.5, and +1.2 was followed by a June reversal of -0.6. I apply -0.2 percentage point for mean reversion after the spring spike and +0.1 percentage point for July energy/industrial-supplies upside, giving a point forecast of +0.4 percent. For the 80% interval, use the values themselves for this change series; from the 11 nonmissing BLS monthly changes, sigma = 1.14 percentage points, so 1.28*sigma = 1.46 percentage points. Rounding the half-width to 1.5 gives +0.4 +/- 1.5, or [-1.1, 1.9].","Upside risk: another July jump in petroleum, natural gas, metals, or industrial supplies would land above the interval if it pushed all-commodities exports above about +1.9 percent. Downside risk: a renewed reversal in nonagricultural industrial supplies or a broad commodity selloff would land below the interval if the first print were below -1.1 percent."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior is the recent reference-class median of +0.5 percent, with the mean +0.88 pulled down because the spring surge of +1.9, +1.7, +3.5, and +1.2 was followed by a June reversal of -0.6. I apply -0.2 percentage point for mean reversion after the spring spike and +0.1 percentage point for July energy/industrial-supplies upside, giving a point forecast of +0.4 percent. For the 80% interval, use the values themselves for this change series; from the 11 nonmissing BLS monthly changes, sigma = 1.14 percentage points, so 1.28*sigma = 1.46 percentage points. Rounding the half-width to 1.5 gives +0.4 +/- 1.5, or [-1.1, 1.9]."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Upside risk: another July jump in petroleum, natural gas, metals, or industrial supplies would land above the interval if it pushed all-commodities exports above about +1.9 percent. Downside risk: a renewed reversal in nonagricultural industrial supplies or a broad commodity selloff would land below the interval if the first print were below -1.1 percent."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for BLS all-commodities export prices, July 2026 first print","Prior/update/interval: persistence prior is the recent reference-class median of +0.5 percent, with the mean +0.88 pulled down because the spring surge of +1.9, +1.7, +3.5, and +1.2 was followed by a June reversal of -0.6. I apply -0.2 percentage point for mean reversion after the spring spike and +0.1 percentage point for July energy/industrial-supplies upside, giving a point forecast of +0.4 percent. For the 80% interval, use the values themselves for this change series; from the 11 nonmissing BLS monthly changes, sigma = 1.14 percentage points, so 1.28*sigma = 1.46 percentage points. Rounding the half-width to 1.5 gives +0.4 +/- 1.5, or [-1.1, 1.9]."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-export-prices-mom-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-18\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-durable-goods-orders-mom-july-2026.2026-07-31T15-03-02Z.9b3315a9db35e065","runId":"run.us-durable-goods-orders-mom-july-2026.2026-07-31T15-03-02Z.9b3315a9db35e065","predictionId":"us-durable-goods-orders-mom-july-2026","specId":"spec.us-durable-goods-orders-mom-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool call: Read the May 2026 historical Census advance release for the recent reference-class path and volatility.","Base rate / reference class: durable-goods headline MoM is a high-variance flow series because aircraft and defense orders can swing the aggregate. The recent official reference class is centered near zero: the Jun-25 through Jun-26 first-print-style values average about -0.17 percentage points, while the non-transport June reading at +0.6% and core capital-goods excluding aircraft at +0.9% argue against treating the May drop as persistent weakness."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this targets the seasonally adjusted Total Durable Goods New Orders month-over-month percent change, not the not-seasonally-adjusted level, not ex-transportation, and not the later full-report revision. Census M3 is the official origin source; ALFRED DGORDER is the stable mirror used by the ledger resolver for the first vintage.","Tool call: Checked the Census M3 release schedule for the July 2026 survey month."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this targets the seasonally adjusted Total Durable Goods New Orders month-over-month percent change, not the not-seasonally-adjusted level, not ex-transportation, and not the later full-report revision. Census M3 is the official origin source; ALFRED DGORDER is the stable mirror used by the ledger resolver for the first vintage.","Tool call: Checked the Census M3 release schedule for the July 2026 survey month."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 11.2, distribution present, forecast step count 1.","evidence":["Tool call: Read the June 2026 component detail in Census advance Table 1.","Prior/update/interval: persistence/reference-class prior is the recent headline mean, using official Jun-25 through Jun-26 monthly changes [-9.4, -2.8, 3.0, 0.6, -2.1, 5.4, -0.9, -0.4, -1.2, 1.3, 8.5, -4.5, 0.3], mean = -0.17. Updates: +0.3 pp for June headline stabilization, +0.2 pp for ex-transport/core-capital strength, and +0.1 pp for partial mean reversion after the May/April aircraft whipsaw, giving point = 0.4. For a change/flow target I size dispersion from the values themselves and prefer first-print-style values where available because the target itself is first print: sample sigma = 4.4 percentage points, so 1.28*sigma = 5.6; point 0.4 +/- 5.6 gives an 80% interval of -5.2 to 6.0."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate / reference class: durable-goods headline MoM is a high-variance flow series because aircraft and defense orders can swing the aggregate. The recent official reference class is centered near zero: the Jun-25 through Jun-26 first-print-style values average about -0.17 percentage points, while the non-transport June reading at +0.6% and core capital-goods excluding aircraft at +0.9% argue against treating the May drop as persistent weakness.","Prior/update/interval: persistence/reference-class prior is the recent headline mean, using official Jun-25 through Jun-26 monthly changes [-9.4, -2.8, 3.0, 0.6, -2.1, 5.4, -0.9, -0.4, -1.2, 1.3, 8.5, -4.5, 0.3], mean = -0.17. Updates: +0.3 pp for June headline stabilization, +0.2 pp for ex-transport/core-capital strength, and +0.1 pp for partial mean reversion after the May/April aircraft whipsaw, giving point = 0.4. For a change/flow target I size dispersion from the values themselves and prefer first-print-style values where available because the target itself is first print: sample sigma = 4.4 percentage points, so 1.28*sigma = 5.6; point 0.4 +/- 5.6 gives an 80% interval of -5.2 to 6.0."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-considerations: upside risk is a renewed aircraft or defense-order surge like April 2026, which would land above the interval if transportation orders jump sharply. Downside risk is another aircraft cancellation or broad transportation reversal like May 2026, which would land below the interval. Outside the interval would require a move larger than the recent non-aircraft trend can explain, so it would most likely be transportation/aircraft-specific rather than broad manufacturing momentum."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for July 2026 durable goods new orders MoM","Base rate / reference class: durable-goods headline MoM is a high-variance flow series because aircraft and defense orders can swing the aggregate. The recent official reference class is centered near zero: the Jun-25 through Jun-26 first-print-style values average about -0.17 percentage points, while the non-transport June reading at +0.6% and core capital-goods excluding aircraft at +0.9% argue against treating the May drop as persistent weakness."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-durable-goods-orders-mom-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-26\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-durable-goods-shipments-mom-july-2026.2026-07-31T15-07-02Z.e0acb33bdf3366cf","runId":"run.us-durable-goods-shipments-mom-july-2026.2026-07-31T15-07-02Z.e0acb33bdf3366cf","predictionId":"us-durable-goods-shipments-mom-july-2026","specId":"spec.us-durable-goods-shipments-mom-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: the closest base rate is monthly percent growth in the same SA durable-goods shipments series. The fetched numeric base-rate sample is short and recent, so I use it mainly for momentum and volatility rather than treating it as a full-cycle mean. That recent 2026 reference class is unusually firm: implied Feb-Jan +1.6%, Mar-Feb +0.8%, Apr-Mar +0.7%, then the Census advance table has May-Apr +1.1% and Jun-May +0.7%. I anchor below that near-term average because shipments are a level flow with mean reversion and because June new orders were only +0.3%.","Prior/update/interval: persistence prior starts from the recent same-series average, (1.6 + 0.8 + 0.7 + 1.1 + 0.7) / 5 = 1.0%, then I subtract 0.4 percentage point for mean reversion from an unusually strong first half of 2026, subtract 0.1 for June new-orders softness, and add 0.0 to 0.1 for still-firm core shipments, giving a rounded point of +0.4%. For dispersion, using fetched recent monthly percent changes [1.6, 0.8, 0.7, 1.1, 0.7], sigma = 0.36 percentage point, so 1.28*sigma = 0.46 percentage point. I widen to a 0.7 point half-width, about 1.5x the recent-sample half-width, because July first-print transportation and aircraft shipments can be lumpy and the five-month sample is quiet. Rounded 80% interval: 0.4 - 0.7 = -0.3 and 0.4 + 0.7 = 1.1."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this forecast is for Census M3 durable goods manufacturers' shipments, seasonally adjusted, total durable goods, first print for July 2026. The ledger resolver is AMDMVS through ALFRED/FRED; the underlying official publication is the Census Advance Report on Durable Goods Manufacturers' Shipments, Inventories, and Orders. I am keeping the ledger target unchanged even though Census is the official agency source and ALFRED is the resolver mirror.","Tool call: Checked Census M3 release schedule and 2026 economic-indicator calendar for the July 2026 advance report date."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this forecast is for Census M3 durable goods manufacturers' shipments, seasonally adjusted, total durable goods, first print for July 2026. The ledger resolver is AMDMVS through ALFRED/FRED; the underlying official publication is the Census Advance Report on Durable Goods Manufacturers' Shipments, Inventories, and Orders. I am keeping the ledger target unchanged even though Census is the official agency source and ALFRED is the resolver mirror.","Tool call: Checked Census M3 release schedule and 2026 economic-indicator calendar for the July 2026 advance report date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.4, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior starts from the recent same-series average, (1.6 + 0.8 + 0.7 + 1.1 + 0.7) / 5 = 1.0%, then I subtract 0.4 percentage point for mean reversion from an unusually strong first half of 2026, subtract 0.1 for June new-orders softness, and add 0.0 to 0.1 for still-firm core shipments, giving a rounded point of +0.4%. For dispersion, using fetched recent monthly percent changes [1.6, 0.8, 0.7, 1.1, 0.7], sigma = 0.36 percentage point, so 1.28*sigma = 0.46 percentage point. I widen to a 0.7 point half-width, about 1.5x the recent-sample half-width, because July first-print transportation and aircraft shipments can be lumpy and the five-month sample is quiet. Rounded 80% interval: 0.4 - 0.7 = -0.3 and 0.4 + 0.7 = 1.1.","Counter-considerations: upside risk is a July catch-up in transportation or aircraft shipments plus continued strong core capital-goods shipments, which would land above the interval if total shipments rose more than +1.1%. Downside risk is a vehicle/aircraft reversal or weaker tariff-related factory throughput, which would land below the interval if total shipments fell more than -0.3%. Outside the interval would most likely require a transportation-led swing rather than normal month-to-month drift in nontransport durable categories."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Reference class and base rate: the closest base rate is monthly percent growth in the same SA durable-goods shipments series. The fetched numeric base-rate sample is short and recent, so I use it mainly for momentum and volatility rather than treating it as a full-cycle mean. That recent 2026 reference class is unusually firm: implied Feb-Jan +1.6%, Mar-Feb +0.8%, Apr-Mar +0.7%, then the Census advance table has May-Apr +1.1% and Jun-May +0.7%. I anchor below that near-term average because shipments are a level flow with mean reversion and because June new orders were only +0.3%.","Prior/update/interval: persistence prior starts from the recent same-series average, (1.6 + 0.8 + 0.7 + 1.1 + 0.7) / 5 = 1.0%, then I subtract 0.4 percentage point for mean reversion from an unusually strong first half of 2026, subtract 0.1 for June new-orders softness, and add 0.0 to 0.1 for still-firm core shipments, giving a rounded point of +0.4%. For dispersion, using fetched recent monthly percent changes [1.6, 0.8, 0.7, 1.1, 0.7], sigma = 0.36 percentage point, so 1.28*sigma = 0.46 percentage point. I widen to a 0.7 point half-width, about 1.5x the recent-sample half-width, because July first-print transportation and aircraft shipments can be lumpy and the five-month sample is quiet. Rounded 80% interval: 0.4 - 0.7 = -0.3 and 0.4 + 0.7 = 1.1."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-considerations: upside risk is a July catch-up in transportation or aircraft shipments plus continued strong core capital-goods shipments, which would land above the interval if total shipments rose more than +1.1%. Downside risk is a vehicle/aircraft reversal or weaker tariff-related factory throughput, which would land below the interval if total shipments fell more than -0.3%. Outside the interval would most likely require a transportation-led swing rather than normal month-to-month drift in nontransport durable categories."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["July 2026 durable goods shipments MoM forecast","Framing and exact resolver: this forecast is for Census M3 durable goods manufacturers' shipments, seasonally adjusted, total durable goods, first print for July 2026. The ledger resolver is AMDMVS through ALFRED/FRED; the underlying official publication is the Census Advance Report on Durable Goods Manufacturers' Shipments, Inventories, and Orders. I am keeping the ledger target unchanged even though Census is the official agency source and ALFRED is the resolver mirror."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-durable-goods-shipments-mom-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-26\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-construction-spending-mom-july-2026.2026-07-31T15-09-31Z.98564745ecff0853","runId":"run.us-construction-spending-mom-july-2026.2026-07-31T15-09-31Z.98564745ecff0853","predictionId":"us-construction-spending-mom-july-2026","specId":"spec.us-construction-spending-mom-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: recent monthly percent changes in total construction spending are centered close to zero. The volatility sample uses current revised public MPCTXXXXS values available before the run, not ALFRED first-vintage values, because it is an uncertainty reference class rather than the resolution source. The 2024-08 through 2026-05 sequence was 0.2, -0.3, 0.0, -0.2, -0.7, -0.3, -0.2, -0.7, 0.1, -0.2, 0.5, 0.4, 0.4, -0.4, -0.1, 0.6, 1.8, -1.9, -0.8, 0.2, 0.4, 0.1, giving a near-zero mean around -0.05 percentage point.","Level, momentum, one-off, and policy-mechanism effects: the latest Census release shows nominal total spending barely positive, public construction positive, private residential positive, and private nonresidential soft. I do not see a clear one-off mechanism that should dominate the base rate by July; July is therefore anchored near flat rather than extrapolating the revised January drop or the December spike."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["July 2026 U.S. construction spending MoM first print","Framing and exact resolver: the target is the U.S. Census Bureau Value of Construction Put in Place Survey total construction series, seasonally adjusted annual rate, for July 2026. The canonical ledger binds resolution to ALFRED TTLCONS first_print even though Census is the official agency source; I use Census pages for schedule and release context, and keep the resolver tied to the registered ALFRED TTLCONS first-vintage rule."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["July 2026 U.S. construction spending MoM first print","Framing and exact resolver: the target is the U.S. Census Bureau Value of Construction Put in Place Survey total construction series, seasonally adjusted annual rate, for July 2026. The canonical ledger binds resolution to ALFRED TTLCONS first_print even though Census is the official agency source; I use Census pages for schedule and release context, and keep the resolver tied to the registered ALFRED TTLCONS first-vintage rule."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.8, distribution present, forecast step count 1.","evidence":["Reference class and base rate: recent monthly percent changes in total construction spending are centered close to zero. The volatility sample uses current revised public MPCTXXXXS values available before the run, not ALFRED first-vintage values, because it is an uncertainty reference class rather than the resolution source. The 2024-08 through 2026-05 sequence was 0.2, -0.3, 0.0, -0.2, -0.7, -0.3, -0.2, -0.7, 0.1, -0.2, 0.5, 0.4, 0.4, -0.4, -0.1, 0.6, 1.8, -1.9, -0.8, 0.2, 0.4, 0.1, giving a near-zero mean around -0.05 percentage point.","Prior/update/interval: persistence/base-rate prior is a rolling recent-history prior near 0.0 from the recent MPCTXXXXS reference class, with no separate AR or structural model. I apply a small positive update from May total spending at +0.1 percent, private residential +0.3 percent, and public construction +0.5 percent, offset by private nonresidential -0.3 percent. I set point = 0.1. For the 22 recent percent-change observations listed above, mean is about -0.05 and sample sigma = 0.69 percentage point; 1.28*sigma = 0.88 percentage point, so an 80% interval around 0.1 is roughly -0.8 to 1.0 after rounding."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Reference class and base rate: recent monthly percent changes in total construction spending are centered close to zero. The volatility sample uses current revised public MPCTXXXXS values available before the run, not ALFRED first-vintage values, because it is an uncertainty reference class rather than the resolution source. The 2024-08 through 2026-05 sequence was 0.2, -0.3, 0.0, -0.2, -0.7, -0.3, -0.2, -0.7, 0.1, -0.2, 0.5, 0.4, 0.4, -0.4, -0.1, 0.6, 1.8, -1.9, -0.8, 0.2, 0.4, 0.1, giving a near-zero mean around -0.05 percentage point.","Level, momentum, one-off, and policy-mechanism effects: the latest Census release shows nominal total spending barely positive, public construction positive, private residential positive, and private nonresidential soft. I do not see a clear one-off mechanism that should dominate the base rate by July; July is therefore anchored near flat rather than extrapolating the revised January drop or the December spike."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Reference class and base rate: recent monthly percent changes in total construction spending are centered close to zero. The volatility sample uses current revised public MPCTXXXXS values available before the run, not ALFRED first-vintage values, because it is an uncertainty reference class rather than the resolution source. The 2024-08 through 2026-05 sequence was 0.2, -0.3, 0.0, -0.2, -0.7, -0.3, -0.2, -0.7, 0.1, -0.2, 0.5, 0.4, 0.4, -0.4, -0.1, 0.6, 1.8, -1.9, -0.8, 0.2, 0.4, 0.1, giving a near-zero mean around -0.05 percentage point.","Prior/update/interval: persistence/base-rate prior is a rolling recent-history prior near 0.0 from the recent MPCTXXXXS reference class, with no separate AR or structural model. I apply a small positive update from May total spending at +0.1 percent, private residential +0.3 percent, and public construction +0.5 percent, offset by private nonresidential -0.3 percent. I set point = 0.1. For the 22 recent percent-change observations listed above, mean is about -0.05 and sample sigma = 0.69 percentage point; 1.28*sigma = 0.88 percentage point, so an 80% interval around 0.1 is roughly -0.8 to 1.0 after rounding."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Reference class and base rate: recent monthly percent changes in total construction spending are centered close to zero. The volatility sample uses current revised public MPCTXXXXS values available before the run, not ALFRED first-vintage values, because it is an uncertainty reference class rather than the resolution source. The 2024-08 through 2026-05 sequence was 0.2, -0.3, 0.0, -0.2, -0.7, -0.3, -0.2, -0.7, 0.1, -0.2, 0.5, 0.4, 0.4, -0.4, -0.1, 0.6, 1.8, -1.9, -0.8, 0.2, 0.4, 0.1, giving a near-zero mean around -0.05 percentage point.","Prior/update/interval: persistence/base-rate prior is a rolling recent-history prior near 0.0 from the recent MPCTXXXXS reference class, with no separate AR or structural model. I apply a small positive update from May total spending at +0.1 percent, private residential +0.3 percent, and public construction +0.5 percent, offset by private nonresidential -0.3 percent. I set point = 0.1. For the 22 recent percent-change observations listed above, mean is about -0.05 and sample sigma = 0.69 percentage point; 1.28*sigma = 0.88 percentage point, so an 80% interval around 0.1 is roughly -0.8 to 1.0 after rounding."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-construction-spending-mom-july-2026\nrunLabel: Headline\nresolutionDate: 2026-09-01\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-consumer-credit-annual-rate-july-2026.2026-07-31T15-11-54Z.3b23dcceddc75621","runId":"run.us-consumer-credit-annual-rate-july-2026.2026-07-31T15-11-54Z.3b23dcceddc75621","predictionId":"us-consumer-credit-annual-rate-july-2026","specId":"spec.us-consumer-credit-annual-rate-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["The base rate/reference class is the 2023-01 through 2026-05 monthly TOTALSLAR sample, which avoids the 2022 reopening-credit surge but keeps the current high-rate regime. Its mean is 2.29, close to the trailing 12-month mean of 2.36, so the outside-view anchor is near 2.3 percent.","Prior/update/interval: Persistence/reference class prior is 2023-01 through 2026-05 TOTALSLAR values: mean 2.29 and sigma = 2.03 from the values themselves; half-width = 1.28*sigma = 1.28*2.03 = 2.60. Update components: latest May value -0.04 pulls down, March-April strength and July same-month mean 3.44 pull up, and tight-credit conditions keep the point near the recent mean. Point = 2.40; 80% interval = 2.40 +/- 2.60 = [-0.20, 5.00]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["US G.19 total consumer credit annual-rate forecast","The target is the Federal Reserve G.19 Consumer Credit table, seasonally adjusted Total percent change at annual rate, series code TOTALSLAR, for July 2026 first print. The official Fed September 2026 calendar lists G.19 Consumer Credit on September 8 at 3:00 p.m., so resolutionDate is 2026-09-08; the resolved value is read from the ALFRED first vintage for TOTALSLAR."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the Federal Reserve G.19 Consumer Credit table, seasonally adjusted Total percent change at annual rate, series code TOTALSLAR, for July 2026 first print. The official Fed September 2026 calendar lists G.19 Consumer Credit on September 8 at 3:00 p.m., so resolutionDate is 2026-09-08; the resolved value is read from the ALFRED first vintage for TOTALSLAR.","Tool call: Federal Reserve current G.19 release and table check for latest same-variant data"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5.2, distribution present, forecast step count 1.","evidence":["Prior/update/interval: Persistence/reference class prior is 2023-01 through 2026-05 TOTALSLAR values: mean 2.29 and sigma = 2.03 from the values themselves; half-width = 1.28*sigma = 1.28*2.03 = 2.60. Update components: latest May value -0.04 pulls down, March-April strength and July same-month mean 3.44 pull up, and tight-credit conditions keep the point near the recent mean. Point = 2.40; 80% interval = 2.40 +/- 2.60 = [-0.20, 5.00].","Upside risk is a rebound in revolving balances after the May -4.71 revolving print plus resilient auto or student nonrevolving flows, which would land above the interval if total credit growth exceeds 5.0. Downside risk is another revolving contraction or weaker auto-credit origination, which would land outside the interval below -0.2."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Review disposition: accepted the resolver critique by aligning resolutionSourceUrl and the rule with the canonical ALFRED TOTALSLAR first-vintage binding while retaining the Fed G.19 calendar and release as the originating official source; rejected changing the point or interval because the base-rate and sigma calculation remain coherent."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The base rate/reference class is the 2023-01 through 2026-05 monthly TOTALSLAR sample, which avoids the 2022 reopening-credit surge but keeps the current high-rate regime. Its mean is 2.29, close to the trailing 12-month mean of 2.36, so the outside-view anchor is near 2.3 percent.","Upside risk is a rebound in revolving balances after the May -4.71 revolving print plus resilient auto or student nonrevolving flows, which would land above the interval if total credit growth exceeds 5.0. Downside risk is another revolving contraction or weaker auto-credit origination, which would land outside the interval below -0.2."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["US G.19 total consumer credit annual-rate forecast","Prior/update/interval: Persistence/reference class prior is 2023-01 through 2026-05 TOTALSLAR values: mean 2.29 and sigma = 2.03 from the values themselves; half-width = 1.28*sigma = 1.28*2.03 = 2.60. Update components: latest May value -0.04 pulls down, March-April strength and July same-month mean 3.44 pull up, and tight-credit conditions keep the point near the recent mean. Point = 2.40; 80% interval = 2.40 +/- 2.60 = [-0.20, 5.00]."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-consumer-credit-annual-rate-july-2026\nrunLabel: Headline\nresolutionDate: 2026-09-08\ntraceLineCount: 13\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-revolving-consumer-credit-annual-rate-july-2026.2026-07-31T15-14-57Z.11c40d4318fca54a","runId":"run.us-revolving-consumer-credit-annual-rate-july-2026.2026-07-31T15-14-57Z.11c40d4318fca54a","predictionId":"us-revolving-consumer-credit-annual-rate-july-2026","specId":"spec.us-revolving-consumer-credit-annual-rate-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate: the recent non-pandemic reference class, 2023-01 through 2026-05, has a mean near 5.02 percent, while the more current 2025 through May 2026 average is closer to 3.22 percent; I anchor between these, leaning toward the lower recent regime because 2025-2026 revolving growth has slowed from the 2022-2023 rebound.","Prior/update/interval: persistence/base prior is the 2023-01 to 2026-05 REVOLSLAR sample mean 5.02; current-regime pull from 2025-May 2026 average 3.22 and the latest -4.71 May print lowers the point by about 1.5 percentage points, while March 9.66 and April 10.36 keep it above zero, giving 3.5. For the 80% interval, using the sample standard deviation of the 41 fetched monthly annualized REVOLSLAR rates themselves gives sigma = 5.47; 1.28*sigma = 1.28*5.47 = 7.00, so 3.5 +/- 7.0 gives [-3.5, 10.5]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing: the target is the Federal Reserve G.19 seasonally adjusted annual-rate percent change for total revolving consumer credit, series REVOLSLAR, for July 2026. I use the same variant throughout: revolving credit, seasonally adjusted, percent change at annual rate, first print.","Tool result: The Federal Reserve September 2026 calendar lists G.19 Consumer Credit at 3:00 p.m. on release date 8 in September 2026, so the verified resolution date is 2026-09-08."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast for July 2026 REVOLSLAR first print","Framing: the target is the Federal Reserve G.19 seasonally adjusted annual-rate percent change for total revolving consumer credit, series REVOLSLAR, for July 2026. I use the same variant throughout: revolving credit, seasonally adjusted, percent change at annual rate, first print."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 14, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence/base prior is the 2023-01 to 2026-05 REVOLSLAR sample mean 5.02; current-regime pull from 2025-May 2026 average 3.22 and the latest -4.71 May print lowers the point by about 1.5 percentage points, while March 9.66 and April 10.36 keep it above zero, giving 3.5. For the 80% interval, using the sample standard deviation of the 41 fetched monthly annualized REVOLSLAR rates themselves gives sigma = 5.47; 1.28*sigma = 1.28*5.47 = 7.00, so 3.5 +/- 7.0 gives [-3.5, 10.5].","Counter-considerations: upside risk is a renewed summer borrowing surge like March-April 2026, which would land above the interval if July prints above 10.5 percent; downside risk is another broad paydown or credit-card charge-off tightening episode, which would land below the interval if July prints below -3.5 percent."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate: the recent non-pandemic reference class, 2023-01 through 2026-05, has a mean near 5.02 percent, while the more current 2025 through May 2026 average is closer to 3.22 percent; I anchor between these, leaning toward the lower recent regime because 2025-2026 revolving growth has slowed from the 2022-2023 rebound.","Mechanisms: level growth in revolving balances remains positive on average, but momentum is mixed after the sharp May contraction; high credit card APRs are a drag, and no official June or July G.19 print is available yet to confirm whether May was one-off paydown or a turn lower."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Mechanisms: level growth in revolving balances remains positive on average, but momentum is mixed after the sharp May contraction; high credit card APRs are a drag, and no official June or July G.19 print is available yet to confirm whether May was one-off paydown or a turn lower.","Counter-considerations: upside risk is a renewed summer borrowing surge like March-April 2026, which would land above the interval if July prints above 10.5 percent; downside risk is another broad paydown or credit-card charge-off tightening episode, which would land below the interval if July prints below -3.5 percent."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for July 2026 REVOLSLAR first print","Prior/update/interval: persistence/base prior is the 2023-01 to 2026-05 REVOLSLAR sample mean 5.02; current-regime pull from 2025-May 2026 average 3.22 and the latest -4.71 May print lowers the point by about 1.5 percentage points, while March 9.66 and April 10.36 keep it above zero, giving 3.5. For the 80% interval, using the sample standard deviation of the 41 fetched monthly annualized REVOLSLAR rates themselves gives sigma = 5.47; 1.28*sigma = 1.28*5.47 = 7.00, so 3.5 +/- 7.0 gives [-3.5, 10.5]."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-revolving-consumer-credit-annual-rate-july-2026\nrunLabel: Headline\nresolutionDate: 2026-09-08\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-nonrevolving-consumer-credit-annual-rate-july-2026.2026-07-31T15-16-50Z.f55bdb346672b8eb","runId":"run.us-nonrevolving-consumer-credit-annual-rate-july-2026.2026-07-31T15-16-50Z.f55bdb346672b8eb","predictionId":"us-nonrevolving-consumer-credit-annual-rate-july-2026","specId":"spec.us-nonrevolving-consumer-credit-annual-rate-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 7 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the near-term reference class is the five available 2026 monthly NONREVSLAR observations before the target window, 0.84, 1.94, 3.84, 2.93, and 1.61, with mean 2.23. The official table's annual context is also moderate: 2025 nonrevolving growth 1.8 and 2026 Q1 2.2.","Prior/update/interval: persistence prior is latest NONREVSLAR 1.61 and reference class is Jan-May 2026 values 0.84, 1.94, 3.84, 2.93, 1.61 with mean 2.23. Point estimate starts from a 75 percent reference-class / 25 percent latest blend: 0.75*2.23 + 0.25*1.61 = 2.08, then applies +0.2 for the 2025/Q1 baseline around 1.8-2.2, -0.1 for still-high loan rates, and -0.1 for the May downshift in flow, giving 2.08, rounded to 2.1. For this change-rate series I use the fetched annual-rate values themselves; five observations is a thin volatility sample, but it is the immediate pre-target regime. sigma = 1.17 from the sample standard deviation of 0.84, 1.94, 3.84, 2.93, 1.61; 1.28*sigma = 1.50, so the 80 percent interval is 2.1 +/- 1.5 = 0.6 to 3.6."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: the target is Federal Reserve G.19 Consumer Credit, table Consumer Credit Outstanding, seasonally adjusted, Nonrevolving percent change at annual rate for July 2026. The ledger binds source series NONREVSLAR and the ALFRED first-vintage mirror; the official economic release being mirrored is the Federal Reserve G.19 release.","Tool call: Federal Reserve September 2026 statistical release calendar lookup for G.19 Consumer Credit"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast for July 2026 NONREVSLAR first print","Framing and exact resolver: the target is Federal Reserve G.19 Consumer Credit, table Consumer Credit Outstanding, seasonally adjusted, Nonrevolving percent change at annual rate for July 2026. The ledger binds source series NONREVSLAR and the ALFRED first-vintage mirror; the official economic release being mirrored is the Federal Reserve G.19 release."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is latest NONREVSLAR 1.61 and reference class is Jan-May 2026 values 0.84, 1.94, 3.84, 2.93, 1.61 with mean 2.23. Point estimate starts from a 75 percent reference-class / 25 percent latest blend: 0.75*2.23 + 0.25*1.61 = 2.08, then applies +0.2 for the 2025/Q1 baseline around 1.8-2.2, -0.1 for still-high loan rates, and -0.1 for the May downshift in flow, giving 2.08, rounded to 2.1. For this change-rate series I use the fetched annual-rate values themselves; five observations is a thin volatility sample, but it is the immediate pre-target regime. sigma = 1.17 from the sample standard deviation of 0.84, 1.94, 3.84, 2.93, 1.61; 1.28*sigma = 1.50, so the 80 percent interval is 2.1 +/- 1.5 = 0.6 to 3.6.","Upside risk: a rebound in auto-loan origination, a larger student-loan/federal-government contribution, or revision-prone seasonal factors could put July growth above 3.6. Downside risk: weak vehicle credit, paydowns, or another negative finance-company/federal component could push the print below 0.6. A sharp credit contraction or one-off technical adjustment would land outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence prior is latest NONREVSLAR 1.61 and reference class is Jan-May 2026 values 0.84, 1.94, 3.84, 2.93, 1.61 with mean 2.23. Point estimate starts from a 75 percent reference-class / 25 percent latest blend: 0.75*2.23 + 0.25*1.61 = 2.08, then applies +0.2 for the 2025/Q1 baseline around 1.8-2.2, -0.1 for still-high loan rates, and -0.1 for the May downshift in flow, giving 2.08, rounded to 2.1. For this change-rate series I use the fetched annual-rate values themselves; five observations is a thin volatility sample, but it is the immediate pre-target regime. sigma = 1.17 from the sample standard deviation of 0.84, 1.94, 3.84, 2.93, 1.61; 1.28*sigma = 1.50, so the 80 percent interval is 2.1 +/- 1.5 = 0.6 to 3.6.","Upside risk: a rebound in auto-loan origination, a larger student-loan/federal-government contribution, or revision-prone seasonal factors could put July growth above 3.6. Downside risk: weak vehicle credit, paydowns, or another negative finance-company/federal component could push the print below 0.6. A sharp credit contraction or one-off technical adjustment would land outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for July 2026 NONREVSLAR first print","Prior/update/interval: persistence prior is latest NONREVSLAR 1.61 and reference class is Jan-May 2026 values 0.84, 1.94, 3.84, 2.93, 1.61 with mean 2.23. Point estimate starts from a 75 percent reference-class / 25 percent latest blend: 0.75*2.23 + 0.25*1.61 = 2.08, then applies +0.2 for the 2025/Q1 baseline around 1.8-2.2, -0.1 for still-high loan rates, and -0.1 for the May downshift in flow, giving 2.08, rounded to 2.1. For this change-rate series I use the fetched annual-rate values themselves; five observations is a thin volatility sample, but it is the immediate pre-target regime. sigma = 1.17 from the sample standard deviation of 0.84, 1.94, 3.84, 2.93, 1.61; 1.28*sigma = 1.50, so the 80 percent interval is 2.1 +/- 1.5 = 0.6 to 3.6."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-nonrevolving-consumer-credit-annual-rate-july-2026\nrunLabel: Headline\nresolutionDate: 2026-09-08\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-employment-cost-index-total-compensation-q2-2026.2026-07-27T18-05-01Z.0996958a3d2989b8","runId":"run.us-employment-cost-index-total-compensation-q2-2026.2026-07-27T18-05-01Z.0996958a3d2989b8","predictionId":"us-employment-cost-index-total-compensation-q2-2026","specId":"spec.us-employment-cost-index-total-compensation-q2-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the recent same-series BLS Table 1 reference class is the nine seasonally adjusted 3-month percent changes from Mar. 2024 through Mar. 2026: 1.0, 0.9, 0.8, 0.9, 0.8, 1.0, 0.8, 0.7, 0.9. Their mean is 0.87 and their median/latest are both close to 0.9, so persistence around 0.9 is the prior.","Prior/update/interval: persistence prior uses the exact BLS Table 1 private-industry total-compensation q/q values from Mar. 2024-Mar. 2026; historical sample mean = 0.87 and latest = 0.9. Adjustment components: level +0.00 because the latest 12-month private compensation pace is 3.4 percent, close to recent trend; momentum +0.03 because Q1 rebounded from 0.7 to 0.9; one-off -0.02 because Q1 benefits at 1.3 may partly mean-revert while wages were only 0.7; policy-mechanism +0.00 because no direct index-policy reset applies before the June quarter print. Point = 0.9. For the interval, because this is a percent-change series, compute dispersion from the rounded BLS percent-change values themselves: squared deviations around 0.8667 sum to 0.0800 over 9 observations, sample variance = 0.0800/(9-1) = 0.0100, sigma = 0.10. 80 percent half-width = 1.28*sigma = 0.128, so 0.9 +/- 0.128 gives 0.772 to 1.028, rounded to 0.77 to 1.03; this is model-scale support around a one-decimal official print."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["Forecast for BLS ECI private-industry total compensation, 2026-Q2 first print","Framing and exact resolver: this is the BLS Employment Cost Index Table 1 series for private industry workers, all workers, total compensation, seasonally adjusted 3-month percent change for the quarter ending June 2026. The ledger target binds resolution to the ALFRED/FRED ECICOM first-print mirror, while the agency source for the underlying print is BLS Table 1."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast for BLS ECI private-industry total compensation, 2026-Q2 first print","Framing and exact resolver: this is the BLS Employment Cost Index Table 1 series for private industry workers, all workers, total compensation, seasonally adjusted 3-month percent change for the quarter ending June 2026. The ledger target binds resolution to the ALFRED/FRED ECICOM first-print mirror, while the agency source for the underlying print is BLS Table 1."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.26, distribution present, forecast step count 1.","evidence":["Tool call: Fetched BLS current-release component detail for private industry compensation.","Prior/update/interval: persistence prior uses the exact BLS Table 1 private-industry total-compensation q/q values from Mar. 2024-Mar. 2026; historical sample mean = 0.87 and latest = 0.9. Adjustment components: level +0.00 because the latest 12-month private compensation pace is 3.4 percent, close to recent trend; momentum +0.03 because Q1 rebounded from 0.7 to 0.9; one-off -0.02 because Q1 benefits at 1.3 may partly mean-revert while wages were only 0.7; policy-mechanism +0.00 because no direct index-policy reset applies before the June quarter print. Point = 0.9. For the interval, because this is a percent-change series, compute dispersion from the rounded BLS percent-change values themselves: squared deviations around 0.8667 sum to 0.0800 over 9 observations, sample variance = 0.0800/(9-1) = 0.0100, sigma = 0.10. 80 percent half-width = 1.28*sigma = 0.128, so 0.9 +/- 0.128 gives 0.772 to 1.028, rounded to 0.77 to 1.03; this is model-scale support around a one-decimal official print."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior uses the exact BLS Table 1 private-industry total-compensation q/q values from Mar. 2024-Mar. 2026; historical sample mean = 0.87 and latest = 0.9. Adjustment components: level +0.00 because the latest 12-month private compensation pace is 3.4 percent, close to recent trend; momentum +0.03 because Q1 rebounded from 0.7 to 0.9; one-off -0.02 because Q1 benefits at 1.3 may partly mean-revert while wages were only 0.7; policy-mechanism +0.00 because no direct index-policy reset applies before the June quarter print. Point = 0.9. For the interval, because this is a percent-change series, compute dispersion from the rounded BLS percent-change values themselves: squared deviations around 0.8667 sum to 0.0800 over 9 observations, sample variance = 0.0800/(9-1) = 0.0100, sigma = 0.10. 80 percent half-width = 1.28*sigma = 0.128, so 0.9 +/- 0.128 gives 0.772 to 1.028, rounded to 0.77 to 1.03; this is model-scale support around a one-decimal official print."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-considerations: upside risk would be a broad private-benefits acceleration or another quarter like Q1 benefits that pushes the print above 1.03; downside risk would be wage cooling plus benefit mean reversion that pulls the print below 0.77; outside the interval would require a visible break from the very tight 0.7-1.0 recent same-series range."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for BLS ECI private-industry total compensation, 2026-Q2 first print","Prior/update/interval: persistence prior uses the exact BLS Table 1 private-industry total-compensation q/q values from Mar. 2024-Mar. 2026; historical sample mean = 0.87 and latest = 0.9. Adjustment components: level +0.00 because the latest 12-month private compensation pace is 3.4 percent, close to recent trend; momentum +0.03 because Q1 rebounded from 0.7 to 0.9; one-off -0.02 because Q1 benefits at 1.3 may partly mean-revert while wages were only 0.7; policy-mechanism +0.00 because no direct index-policy reset applies before the June quarter print. Point = 0.9. For the interval, because this is a percent-change series, compute dispersion from the rounded BLS percent-change values themselves: squared deviations around 0.8667 sum to 0.0800 over 9 observations, sample variance = 0.0800/(9-1) = 0.0100, sigma = 0.10. 80 percent half-width = 1.28*sigma = 0.128, so 0.9 +/- 0.128 gives 0.772 to 1.028, rounded to 0.77 to 1.03; this is model-scale support around a one-decimal official print."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-employment-cost-index-total-compensation-q2-2026\nrunLabel: Headline\nresolutionDate: 2026-07-31\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-eci-private-wages-salaries-q2-2026.2026-07-27T18-07-10Z.3bbbe95fe68dea0e","runId":"run.us-eci-private-wages-salaries-q2-2026.2026-07-27T18-07-10Z.3bbbe95fe68dea0e","predictionId":"us-eci-private-wages-salaries-q2-2026","specId":"spec.us-eci-private-wages-salaries-q2-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Reference class/base rate: for CIS2020000000000Q from 2014 Q1 through 2026 Q1, the mean is about 0.82 percent qoq, with a cooler recent run of 0.8, 1.0, 0.8, 0.7, 0.7 over the last five quarters. I anchor on that reference class but weight the latest two quarters because wage growth has decelerated from the 2021-2023 catch-up period.","Prior/update/interval: persistence prior is last two official prints, 0.7 and 0.7, blended with the 2014 Q1-2026 Q1 reference-class mean of 0.82 and the last-five-quarter mean of 0.80. Adjustment components: level/momentum +0.00 versus last-five mean, one-off reopening premium -0.05 versus 2021-2023, policy/labor-market stickiness +0.05 because wage contracts and low unemployment limit abrupt slowing, giving point 0.80. Interval method uses the values themselves for this qoq change series: n=49, sum=40.3, sumsq=39.9, sigma = sqrt((39.9 - 49*(40.3/49)^2)/48) = 0.375 percentage points; 1.28*sigma = 0.480, so an 80 percent band around 0.80 is about 0.32 to 1.28, rounded conservatively to 0.35 to 1.25."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Forecast for BLS private-industry wage ECI, Q2 2026 first print","The economic target is BLS Table 2, series CIS2020000000000Q: wages and salaries for all private industry workers, seasonally adjusted, 3-month percent change in current dollars. The ledger resolver is ALFRED/FRED ECIWAG under a first-print policy, so this forecast keeps the canonical catalog target while treating BLS Table 2 as the underlying official agency source mirrored by the ledger binding."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast for BLS private-industry wage ECI, Q2 2026 first print","The economic target is BLS Table 2, series CIS2020000000000Q: wages and salaries for all private industry workers, seasonally adjusted, 3-month percent change in current dollars. The ledger resolver is ALFRED/FRED ECIWAG under a first-print policy, so this forecast keeps the canonical catalog target while treating BLS Table 2 as the underlying official agency source mirrored by the ledger binding."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.9, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is last two official prints, 0.7 and 0.7, blended with the 2014 Q1-2026 Q1 reference-class mean of 0.82 and the last-five-quarter mean of 0.80. Adjustment components: level/momentum +0.00 versus last-five mean, one-off reopening premium -0.05 versus 2021-2023, policy/labor-market stickiness +0.05 because wage contracts and low unemployment limit abrupt slowing, giving point 0.80. Interval method uses the values themselves for this qoq change series: n=49, sum=40.3, sumsq=39.9, sigma = sqrt((39.9 - 49*(40.3/49)^2)/48) = 0.375 percentage points; 1.28*sigma = 0.480, so an 80 percent band around 0.80 is about 0.32 to 1.28, rounded conservatively to 0.35 to 1.25.","Upside risk: a renewed bonus-heavy quarter, health-care wage pressure, or broad labor-cost catch-up could print 1.3 percent or higher and would land above the interval. Downside risk: a faster private-sector labor-market cooling or weak incentive pay could print 0.3 percent or lower and would land below the interval. Outside the interval requires a move materially larger than recent 0.7-1.0 percent stability."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Reference class/base rate: for CIS2020000000000Q from 2014 Q1 through 2026 Q1, the mean is about 0.82 percent qoq, with a cooler recent run of 0.8, 1.0, 0.8, 0.7, 0.7 over the last five quarters. I anchor on that reference class but weight the latest two quarters because wage growth has decelerated from the 2021-2023 catch-up period.","Prior/update/interval: persistence prior is last two official prints, 0.7 and 0.7, blended with the 2014 Q1-2026 Q1 reference-class mean of 0.82 and the last-five-quarter mean of 0.80. Adjustment components: level/momentum +0.00 versus last-five mean, one-off reopening premium -0.05 versus 2021-2023, policy/labor-market stickiness +0.05 because wage contracts and low unemployment limit abrupt slowing, giving point 0.80. Interval method uses the values themselves for this qoq change series: n=49, sum=40.3, sumsq=39.9, sigma = sqrt((39.9 - 49*(40.3/49)^2)/48) = 0.375 percentage points; 1.28*sigma = 0.480, so an 80 percent band around 0.80 is about 0.32 to 1.28, rounded conservatively to 0.35 to 1.25."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Reference class/base rate: for CIS2020000000000Q from 2014 Q1 through 2026 Q1, the mean is about 0.82 percent qoq, with a cooler recent run of 0.8, 1.0, 0.8, 0.7, 0.7 over the last five quarters. I anchor on that reference class but weight the latest two quarters because wage growth has decelerated from the 2021-2023 catch-up period.","Upside risk: a renewed bonus-heavy quarter, health-care wage pressure, or broad labor-cost catch-up could print 1.3 percent or higher and would land above the interval. Downside risk: a faster private-sector labor-market cooling or weak incentive pay could print 0.3 percent or lower and would land below the interval. Outside the interval requires a move materially larger than recent 0.7-1.0 percent stability."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for BLS private-industry wage ECI, Q2 2026 first print","The economic target is BLS Table 2, series CIS2020000000000Q: wages and salaries for all private industry workers, seasonally adjusted, 3-month percent change in current dollars. The ledger resolver is ALFRED/FRED ECIWAG under a first-print policy, so this forecast keeps the canonical catalog target while treating BLS Table 2 as the underlying official agency source mirrored by the ledger binding."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-eci-private-wages-salaries-q2-2026\nrunLabel: Headline\nresolutionDate: 2026-07-31\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.u6-underemployment-rate-july-2026.2026-07-27T18-09-22Z.2ba7df3c50344c53","runId":"run.u6-underemployment-rate-july-2026.2026-07-27T18-09-22Z.2ba7df3c50344c53","predictionId":"u6-underemployment-rate-july-2026","specId":"spec.u6-underemployment-rate-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: for a monthly labor-underutilization rate already near 8 percent, the strongest reference class is persistence plus small one-month CPS sampling and composition movement. The 2026 official/mirror history gives recent one-month moves of -0.2, +0.1, +0.2, -0.1, and -0.2 percentage points from Jan through Jun, so unchanged or a one-tenth move is the modal case.","Prior/update/interval: persistence prior = June 2026 U-6 at 7.9 percent; historical sample = Jan-Jun 2026 seasonally adjusted U-6 values 8.1, 7.9, 8.0, 8.2, 8.1, 7.9, with successive changes -0.2, +0.1, +0.2, -0.1, -0.2. Sample sigma = 0.18 percentage point. 80% normal half-width is about 1.28*sigma = 1.28*0.18 = 0.23 percentage point. Adjustment components: level 0.00, recent downward momentum -0.05, mean-reversion from June drop +0.05, policy/mechanism one-off 0.00, leaving point 7.9. Implied continuous 80% bounds are 7.9 +/- 0.23 = 7.67 to 8.13, rounded to 7.7 to 8.1 for the printed one-decimal series. The narrow interval is intentional because it is based on recent realized monthly moves and the one-decimal first-print granularity."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["Forecast for BLS July 2026 U-6 first print","Framing and exact resolver: this targets the BLS CPS household-survey U-6 alternative labor underutilization rate, seasonally adjusted, Table A-15, source code LNS13327709 mirrored by FRED/ALFRED as U6RATE. The ledger mechanically resolves through the ALFRED U6RATE first-vintage binding, while BLS Table A-15 is the underlying official release."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast for BLS July 2026 U-6 first print","Framing and exact resolver: this targets the BLS CPS household-survey U-6 alternative labor underutilization rate, seasonally adjusted, Table A-15, source code LNS13327709 mirrored by FRED/ALFRED as U6RATE. The ledger mechanically resolves through the ALFRED U6RATE first-vintage binding, while BLS Table A-15 is the underlying official release."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.4, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = June 2026 U-6 at 7.9 percent; historical sample = Jan-Jun 2026 seasonally adjusted U-6 values 8.1, 7.9, 8.0, 8.2, 8.1, 7.9, with successive changes -0.2, +0.1, +0.2, -0.1, -0.2. Sample sigma = 0.18 percentage point. 80% normal half-width is about 1.28*sigma = 1.28*0.18 = 0.23 percentage point. Adjustment components: level 0.00, recent downward momentum -0.05, mean-reversion from June drop +0.05, policy/mechanism one-off 0.00, leaving point 7.9. Implied continuous 80% bounds are 7.9 +/- 0.23 = 7.67 to 8.13, rounded to 7.7 to 8.1 for the printed one-decimal series. The narrow interval is intentional because it is based on recent realized monthly moves and the one-decimal first-print granularity.","Counter-considerations: upside risk is a July jump in part-time-for-economic-reasons or marginal attachment that lifts U-6 to 8.2 or higher, which would land above the 80% interval. Downside risk is a broad household-survey improvement that pushes U-6 to 7.6 or lower, which would land below the interval. Outside the interval would most likely require a larger-than-recent move in the broader underemployment components rather than just a small U-3 change."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, and mechanism: the latest level is 7.9 percent, down from 8.2 in April and 8.1 in May, while June U-3 in the same Table A-15 was 4.2 after 4.3 in May. That argues against a sharp U-6 rise, but U-6 is broader than U-3 and can move with marginal attachment and part-time-for-economic-reasons even when unemployment is steady.","Prior/update/interval: persistence prior = June 2026 U-6 at 7.9 percent; historical sample = Jan-Jun 2026 seasonally adjusted U-6 values 8.1, 7.9, 8.0, 8.2, 8.1, 7.9, with successive changes -0.2, +0.1, +0.2, -0.1, -0.2. Sample sigma = 0.18 percentage point. 80% normal half-width is about 1.28*sigma = 1.28*0.18 = 0.23 percentage point. Adjustment components: level 0.00, recent downward momentum -0.05, mean-reversion from June drop +0.05, policy/mechanism one-off 0.00, leaving point 7.9. Implied continuous 80% bounds are 7.9 +/- 0.23 = 7.67 to 8.13, rounded to 7.7 to 8.1 for the printed one-decimal series. The narrow interval is intentional because it is based on recent realized monthly moves and the one-decimal first-print granularity."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, and mechanism: the latest level is 7.9 percent, down from 8.2 in April and 8.1 in May, while June U-3 in the same Table A-15 was 4.2 after 4.3 in May. That argues against a sharp U-6 rise, but U-6 is broader than U-3 and can move with marginal attachment and part-time-for-economic-reasons even when unemployment is steady.","Counter-considerations: upside risk is a July jump in part-time-for-economic-reasons or marginal attachment that lifts U-6 to 8.2 or higher, which would land above the 80% interval. Downside risk is a broad household-survey improvement that pushes U-6 to 7.6 or lower, which would land below the interval. Outside the interval would most likely require a larger-than-recent move in the broader underemployment components rather than just a small U-3 change."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for BLS July 2026 U-6 first print","Base rate/reference class: for a monthly labor-underutilization rate already near 8 percent, the strongest reference class is persistence plus small one-month CPS sampling and composition movement. The 2026 official/mirror history gives recent one-month moves of -0.2, +0.1, +0.2, -0.1, and -0.2 percentage points from Jan through Jun, so unchanged or a one-tenth move is the modal case."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: u6-underemployment-rate-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-07\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.u6-underemployment-rate-july-2026.2026-07-31T14-05-19Z.u6-underemployment-rate-july-2026-challenge-github-khs-2026-07-31t14-05-19z.3147750ffd8ef7a2","runId":"run.u6-underemployment-rate-july-2026.2026-07-31T14-05-19Z.u6-underemployment-rate-july-2026-challenge-github-khs-2026-07-31t14-05-19z.3147750ffd8ef7a2","predictionId":"u6-underemployment-rate-july-2026","specId":"spec.u6-underemployment-rate-july-2026","runLabel":"khs challenge submission","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.05,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 6 historical point(s) and explicit outside-view language.","evidence":["Base rate: 2026 U-6 SA is range-bound 7.9-8.2 (mean 8.03, sd of monthly change 0.18), June at 7.9. Random walk from June centers 7.9; mean reversion pulls up, but July survey-week initial claims (188k, w/e 7/18) and U-3 easing to 4.2 pull down. The two roughly offset. Disconfirming: two straight declines could mark a real downshift below the range, and July SA is noisy (auto retooling, teen employment). Verified against BLS LNS13327709 live."]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 0 typed tool call(s), 1 source-context item(s), activity log absent.","evidence":["Base rate: 2026 U-6 SA is range-bound 7.9-8.2 (mean 8.03, sd of monthly change 0.18), June at 7.9. Random walk from June centers 7.9; mean reversion pulls up, but July survey-week initial claims (188k, w/e 7/18) and U-3 easing to 4.2 pull down. The two roughly offset. Disconfirming: two straight declines could mark a real downshift below the range, and July SA is noisy (auto retooling, teen employment). Verified against BLS LNS13327709 live."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Published challenge submission"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.4, distribution present, forecast step count 1.","evidence":["Forecast: point 7.9, 80% interval [7.7, 8.1]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate: 2026 U-6 SA is range-bound 7.9-8.2 (mean 8.03, sd of monthly change 0.18), June at 7.9. Random walk from June centers 7.9; mean reversion pulls up, but July survey-week initial claims (188k, w/e 7/18) and U-3 easing to 4.2 pull down. The two roughly offset. Disconfirming: two straight declines could mark a real downshift below the range, and July SA is noisy (auto retooling, teen employment). Verified against BLS LNS13327709 live."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 7.9, 80% interval [7.7, 8.1]"]}],"flags":["no_typed_tool_call"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: u6-underemployment-rate-july-2026\nrunLabel: khs challenge submission\nresolutionDate: 2026-08-07\ntraceLineCount: 5\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: mechanism reasoning (2/4). Flags: no_typed_tool_call."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-cpi-primary-rent-mom-july-2026.2026-07-27T18-12-03Z.ec3983bd0245b4e6","runId":"run.us-cpi-primary-rent-mom-july-2026.2026-07-27T18-12-03Z.ec3983bd0245b4e6","predictionId":"us-cpi-primary-rent-mom-july-2026","specId":"spec.us-cpi-primary-rent-mom-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the 15 valid recent exact index-derived monthly changes average 0.2674 percent. The latest rounded BLS table and exact June calculation point lower than that base rate, while the April and May prints argue against assuming the series has fully reset to a very low monthly pace.","Prior/update/interval: persistence prior is the recent valid-change mean from CUSR0000SEHA, 0.2674 percent; no AR, ETS, or other formal time-series model was used because the public-history sample available here is short and the target is a one-step first-print index change. Adjustment components: -0.06 pp for June's low exact 0.1495 percent and rounded BLS 0.1 percent signal, +0.01 pp for sticky rent renewal inertia, and +0.00 pp for no identified July-specific policy break, giving 0.2674 - 0.06 + 0.01 = 0.2174, rounded to 0.22. Interval method uses the sample standard deviation of the 15 valid recent exact MoM values: sigma = 0.099 percentage point. The 80 percent normal half-width is roughly 1.28*sigma = 1.28*0.099 = 0.127 percentage point, so 0.22 +/- 0.13 gives 0.09 to 0.35 after rounding."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this targets the seasonally adjusted CPI-U rent of primary residence index for the U.S. city average, series CUSR0000SEHA, converted to month-over-month percent growth for July 2026 on the first official print. The variant is seasonally adjusted, U.S. city average, not regional, not unadjusted, and not owners' equivalent rent. The ledger resolver is the ALFRED/FRED first-vintage record for the BLS series, so ALFRED is used to recover the first-vintage index levels rather than as a subjective alternate source.","Tool call: Checked the BLS CPI release schedule for the July 2026 reference month."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this targets the seasonally adjusted CPI-U rent of primary residence index for the U.S. city average, series CUSR0000SEHA, converted to month-over-month percent growth for July 2026 on the first official print. The variant is seasonally adjusted, U.S. city average, not regional, not unadjusted, and not owners' equivalent rent. The ledger resolver is the ALFRED/FRED first-vintage record for the BLS series, so ALFRED is used to recover the first-vintage index levels rather than as a subjective alternate source.","Tool call: Checked the BLS CPI release schedule for the July 2026 reference month."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.26, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is the recent valid-change mean from CUSR0000SEHA, 0.2674 percent; no AR, ETS, or other formal time-series model was used because the public-history sample available here is short and the target is a one-step first-print index change. Adjustment components: -0.06 pp for June's low exact 0.1495 percent and rounded BLS 0.1 percent signal, +0.01 pp for sticky rent renewal inertia, and +0.00 pp for no identified July-specific policy break, giving 0.2674 - 0.06 + 0.01 = 0.2174, rounded to 0.22. Interval method uses the sample standard deviation of the 15 valid recent exact MoM values: sigma = 0.099 percentage point. The 80 percent normal half-width is roughly 1.28*sigma = 1.28*0.099 = 0.127 percentage point, so 0.22 +/- 0.13 gives 0.09 to 0.35 after rounding.","Counter-considerations: upside risk is a repeat of the April-May rebound in sampled rents or seasonal adjustment that would land above the interval, above 0.35 percent. Downside risk is another very soft rent sample or a correction in lagged market rents that would land below the interval, below 0.09 percent. Outside the interval would most likely reflect a data-processing or sampling surprise rather than a visible release-calendar issue."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior is the recent valid-change mean from CUSR0000SEHA, 0.2674 percent; no AR, ETS, or other formal time-series model was used because the public-history sample available here is short and the target is a one-step first-print index change. Adjustment components: -0.06 pp for June's low exact 0.1495 percent and rounded BLS 0.1 percent signal, +0.01 pp for sticky rent renewal inertia, and +0.00 pp for no identified July-specific policy break, giving 0.2674 - 0.06 + 0.01 = 0.2174, rounded to 0.22. Interval method uses the sample standard deviation of the 15 valid recent exact MoM values: sigma = 0.099 percentage point. The 80 percent normal half-width is roughly 1.28*sigma = 1.28*0.099 = 0.127 percentage point, so 0.22 +/- 0.13 gives 0.09 to 0.35 after rounding."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-considerations: upside risk is a repeat of the April-May rebound in sampled rents or seasonal adjustment that would land above the interval, above 0.35 percent. Downside risk is another very soft rent sample or a correction in lagged market rents that would land below the interval, below 0.09 percent. Outside the interval would most likely reflect a data-processing or sampling surprise rather than a visible release-calendar issue."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["US CPI primary rent MoM forecast for July 2026","Base rate/reference class: the 15 valid recent exact index-derived monthly changes average 0.2674 percent. The latest rounded BLS table and exact June calculation point lower than that base rate, while the April and May prints argue against assuming the series has fully reset to a very low monthly pace."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-cpi-primary-rent-mom-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-12\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-cpi-owners-equivalent-rent-mom-july-2026.2026-07-27T18-13-47Z.9d9a4b7dab257493","runId":"run.us-cpi-owners-equivalent-rent-mom-july-2026.2026-07-27T18-13-47Z.9d9a4b7dab257493","predictionId":"us-cpi-owners-equivalent-rent-mom-july-2026","specId":"spec.us-cpi-owners-equivalent-rent-mom-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: using the latest continuous official CUSR0000SEHC history visible before resolution from Dec 2025 through Jun 2026 as a close proxy for first-print-style recent behavior, the six observed 2026 monthly changes are 0.220%, 0.224%, 0.284%, 0.533%, 0.297%, and 0.240%, with a mean near 0.300%. The June rounded OER print of 0.2% and the softer shelter aggregate argue for a July point below that six-month mean but not a break from the positive OER trend.","Prior/update/interval: persistence prior is recent official CUSR0000SEHC MoM history, with the Jan-Jun 2026 reference class above. Adjustment components: start from the six-month mean 0.300%, subtract 0.04 pp for the latest June 0.240% value being below the mean, subtract 0.01 pp because June shelter was only 0.1%, and keep 0.00 pp for one-off energy/goods effects because they do not directly drive OER. Point = 0.300 - 0.040 - 0.010 = 0.250%. Interval method: realized sample dispersion of the six monthly OER values gives sigma = 0.118 percentage points; 1.28*sigma = 0.151 pp, so the 80% interval is about 0.250 +/- 0.151 = 0.099 to 0.401, rounded to 0.10 to 0.40."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing and exact resolver: the target is BLS CPI-U Owners' equivalent rent of residences in U.S. city average, seasonally adjusted, series CUSR0000SEHC. The forecast is the July 2026 first-print month-over-month percent change, computed from the first published July and June index levels; this uses the same seasonally adjusted variant for all anchors.","Resolver alignment: BLS is the originating official agency for the CPI-U series, while the canonical ledger target binds resolution to ALFRED/FRED first-vintage capture at alfred.stlouisfed.org for CUSR0000SEHC. The JSON resolver fields follow that ledger source binding and first_print policy."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: the target is BLS CPI-U Owners' equivalent rent of residences in U.S. city average, seasonally adjusted, series CUSR0000SEHC. The forecast is the July 2026 first-print month-over-month percent change, computed from the first published July and June index levels; this uses the same seasonally adjusted variant for all anchors.","Resolver alignment: BLS is the originating official agency for the CPI-U series, while the canonical ledger target binds resolution to ALFRED/FRED first-vintage capture at alfred.stlouisfed.org for CUSR0000SEHC. The JSON resolver fields follow that ledger source binding and first_print policy."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.3, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is recent official CUSR0000SEHC MoM history, with the Jan-Jun 2026 reference class above. Adjustment components: start from the six-month mean 0.300%, subtract 0.04 pp for the latest June 0.240% value being below the mean, subtract 0.01 pp because June shelter was only 0.1%, and keep 0.00 pp for one-off energy/goods effects because they do not directly drive OER. Point = 0.300 - 0.040 - 0.010 = 0.250%. Interval method: realized sample dispersion of the six monthly OER values gives sigma = 0.118 percentage points; 1.28*sigma = 0.151 pp, so the 80% interval is about 0.250 +/- 0.151 = 0.099 to 0.401, rounded to 0.10 to 0.40.","Counter-considerations: upside risk is a renewed catch-up in sampled rents after April's 0.533% jump, which would land above the interval if July OER prints above 0.40%. Downside risk is a broad shelter deceleration following June's 0.1% shelter increase, which would land below the interval if July OER is under 0.10%. Outside the interval would likely require either another April-like rotation shock or an abrupt near-zero rent-equivalence print."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior is recent official CUSR0000SEHC MoM history, with the Jan-Jun 2026 reference class above. Adjustment components: start from the six-month mean 0.300%, subtract 0.04 pp for the latest June 0.240% value being below the mean, subtract 0.01 pp because June shelter was only 0.1%, and keep 0.00 pp for one-off energy/goods effects because they do not directly drive OER. Point = 0.300 - 0.040 - 0.010 = 0.250%. Interval method: realized sample dispersion of the six monthly OER values gives sigma = 0.118 percentage points; 1.28*sigma = 0.151 pp, so the 80% interval is about 0.250 +/- 0.151 = 0.099 to 0.401, rounded to 0.10 to 0.40."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: using the latest continuous official CUSR0000SEHC history visible before resolution from Dec 2025 through Jun 2026 as a close proxy for first-print-style recent behavior, the six observed 2026 monthly changes are 0.220%, 0.224%, 0.284%, 0.533%, 0.297%, and 0.240%, with a mean near 0.300%. The June rounded OER print of 0.2% and the softer shelter aggregate argue for a July point below that six-month mean but not a break from the positive OER trend.","Counter-considerations: upside risk is a renewed catch-up in sampled rents after April's 0.533% jump, which would land above the interval if July OER prints above 0.40%. Downside risk is a broad shelter deceleration following June's 0.1% shelter increase, which would land below the interval if July OER is under 0.10%. Outside the interval would likely require either another April-like rotation shock or an abrupt near-zero rent-equivalence print."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for July 2026 CPI-U owners' equivalent rent MoM","Framing and exact resolver: the target is BLS CPI-U Owners' equivalent rent of residences in U.S. city average, seasonally adjusted, series CUSR0000SEHC. The forecast is the July 2026 first-print month-over-month percent change, computed from the first published July and June index levels; this uses the same seasonally adjusted variant for all anchors."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-cpi-owners-equivalent-rent-mom-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-12\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-cpi-services-less-energy-mom-july-2026.2026-07-27T18-16-11Z.8bcbaeeeebb0b383","runId":"run.us-cpi-services-less-energy-mom-july-2026.2026-07-27T18-16-11Z.8bcbaeeeebb0b383","predictionId":"us-cpi-services-less-energy-mom-july-2026","specId":"spec.us-cpi-services-less-energy-mom-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 7 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the recent same-series, same-seasonally-adjusted reference class clusters around 0.3 percent MoM. The rounded BLS Table A sequence since mid-2025 has a 0.29 percent mean across the 10 usable non-missing observations, while the first half of 2026 alone averages about 0.28 percent.","Prior/update/interval: persistence prior is the same-series recent BLS Table A base rate, sample Jul 2025, Aug 2025, Sep 2025, Dec 2025, Jan 2026, Feb 2026, Mar 2026, Apr 2026, May 2026, Jun 2026 = [0.4, 0.3, 0.2, 0.3, 0.4, 0.3, 0.2, 0.5, 0.3, 0.0]. Mean = 0.29; current-release adjustment is -0.04 for June cooling and shelter moderation plus +0.02 for likely partial reversal of one-off service drags, giving point = 0.27. Values are rounded Table A percent-growth observations, so sigma = 0.14 from the sample standard deviation; this may understate or distort first-print index-derived volatility. 1.28*sigma = 0.18, giving a symmetric 80% interval of 0.27 +/- 0.18 = [0.09, 0.45], with uncertainty from monthly noise and possible index-to-MoM resolver conversion."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 11 source-context item(s), activity log present.","evidence":["Forecast for July 2026 BLS CPI Services Less Energy MoM","Framing and exact resolver: the target is the BLS CPI-U Services Less Energy Services series, CUSR0000SASLE, U.S. city average, seasonally adjusted, for July 2026, first print. The registered ledger sourceBinding points to ALFRED/FRED CUSR0000SASLE index levels with only a multiply transform, which is inconsistent with the targetUnit percent_growth and MoM slug; I keep the ledger target and forecast the intended official first-print MoM percent change, using the ALFRED first-vintage index source if the resolver computes growth from first-published index values."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: the target is the BLS CPI-U Services Less Energy Services series, CUSR0000SASLE, U.S. city average, seasonally adjusted, for July 2026, first print. The registered ledger sourceBinding points to ALFRED/FRED CUSR0000SASLE index levels with only a multiply transform, which is inconsistent with the targetUnit percent_growth and MoM slug; I keep the ledger target and forecast the intended official first-print MoM percent change, using the ALFRED first-vintage index source if the resolver computes growth from first-published index values.","Tool call: Checked BLS CPI release schedule page for the July 2026 reference month."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.36, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is the same-series recent BLS Table A base rate, sample Jul 2025, Aug 2025, Sep 2025, Dec 2025, Jan 2026, Feb 2026, Mar 2026, Apr 2026, May 2026, Jun 2026 = [0.4, 0.3, 0.2, 0.3, 0.4, 0.3, 0.2, 0.5, 0.3, 0.0]. Mean = 0.29; current-release adjustment is -0.04 for June cooling and shelter moderation plus +0.02 for likely partial reversal of one-off service drags, giving point = 0.27. Values are rounded Table A percent-growth observations, so sigma = 0.14 from the sample standard deviation; this may understate or distort first-print index-derived volatility. 1.28*sigma = 0.18, giving a symmetric 80% interval of 0.27 +/- 0.18 = [0.09, 0.45], with uncertainty from monthly noise and possible index-to-MoM resolver conversion.","Counter-considerations: upside risk is a rebound in motor vehicle insurance, airfares, medical care, or shelter that would land above the interval if services less energy prints near 0.5 percent or higher. Downside risk is another broad services decline, especially communication, insurance, lodging, and medical care, which would land below the interval if the print is near 0.0 percent or negative. Outside the interval would most likely reflect a concentrated component shock rather than normal monthly noise."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Current-release adjustment: June's 0.0 percent print was pulled down by broad core weakness, including motor vehicle insurance at -2.0 percent and communication at -1.5 percent in the BLS June discussion, while shelter still rose 0.1 percent. I treat that as a downside signal but not a new zero-growth regime for services less energy.","Prior/update/interval: persistence prior is the same-series recent BLS Table A base rate, sample Jul 2025, Aug 2025, Sep 2025, Dec 2025, Jan 2026, Feb 2026, Mar 2026, Apr 2026, May 2026, Jun 2026 = [0.4, 0.3, 0.2, 0.3, 0.4, 0.3, 0.2, 0.5, 0.3, 0.0]. Mean = 0.29; current-release adjustment is -0.04 for June cooling and shelter moderation plus +0.02 for likely partial reversal of one-off service drags, giving point = 0.27. Values are rounded Table A percent-growth observations, so sigma = 0.14 from the sample standard deviation; this may understate or distort first-print index-derived volatility. 1.28*sigma = 0.18, giving a symmetric 80% interval of 0.27 +/- 0.18 = [0.09, 0.45], with uncertainty from monthly noise and possible index-to-MoM resolver conversion."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for July 2026 BLS CPI Services Less Energy MoM","Framing and exact resolver: the target is the BLS CPI-U Services Less Energy Services series, CUSR0000SASLE, U.S. city average, seasonally adjusted, for July 2026, first print. The registered ledger sourceBinding points to ALFRED/FRED CUSR0000SASLE index levels with only a multiply transform, which is inconsistent with the targetUnit percent_growth and MoM slug; I keep the ledger target and forecast the intended official first-print MoM percent change, using the ALFRED first-vintage index source if the resolver computes growth from first-published index values."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-cpi-services-less-energy-mom-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-12\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-cpi-services-less-rent-shelter-mom-july-2026.2026-07-27T18-18-38Z.e2a5eaba853d167c","runId":"run.us-cpi-services-less-rent-shelter-mom-july-2026.2026-07-27T18-18-38Z.e2a5eaba853d167c","predictionId":"us-cpi-services-less-rent-shelter-mom-july-2026","specId":"spec.us-cpi-services-less-rent-shelter-mom-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the recent adjacent-change reference class centers near 0.27 percent per month for services less rent of shelter. I use that as the persistence prior, then adjust slightly upward from June's -0.175 percent because the June release identified unusually weak categories such as motor vehicle insurance and communication, while keeping the adjustment small because broad core services momentum also cooled.","Prior/update/interval: persistence prior is the mean of the 10 fetched adjacent MoM changes from Jul. 2025-Sep. 2025 and Dec. 2025-Jun. 2026, about 0.268 percent; adjustment components are +0.07 for partial rebound from June one-off drags and -0.05 for soft June core-services breadth, giving 0.268 + 0.07 - 0.05 = 0.288, rounded to a 0.29 point forecast. Interval method uses the short 10-observation realized dispersion sample of those MoM percent changes: sigma = 0.188 percentage points, so the 80 percent half-width is about 1.28*sigma = 1.28*0.188 = 0.241 percentage points; 0.29 +/- 0.24 gives 0.05 to 0.53."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: the target is the July 2026 first-print month-over-month percent growth for BLS CPI-U Services Less Rent of Shelter, U.S. city average, seasonally adjusted, series CUSR0000SASL2RS. The ledger sourceBinding points to ALFRED series CUSR0000SASL2RS and targetUnit percent_growth; I keep the ledger target and compute MoM percent growth from the first-print CUSR0000SASL2RS seasonally adjusted index values.","Tool call: BLS CPI release schedule for 2026, Consumer Price Index release dates"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["US CPI-U Services Less Rent of Shelter MoM, July 2026 first print","Framing and exact resolver: the target is the July 2026 first-print month-over-month percent growth for BLS CPI-U Services Less Rent of Shelter, U.S. city average, seasonally adjusted, series CUSR0000SASL2RS. The ledger sourceBinding points to ALFRED series CUSR0000SASL2RS and targetUnit percent_growth; I keep the ledger target and compute MoM percent growth from the first-print CUSR0000SASL2RS seasonally adjusted index values."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.48, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is the mean of the 10 fetched adjacent MoM changes from Jul. 2025-Sep. 2025 and Dec. 2025-Jun. 2026, about 0.268 percent; adjustment components are +0.07 for partial rebound from June one-off drags and -0.05 for soft June core-services breadth, giving 0.268 + 0.07 - 0.05 = 0.288, rounded to a 0.29 point forecast. Interval method uses the short 10-observation realized dispersion sample of those MoM percent changes: sigma = 0.188 percentage points, so the 80 percent half-width is about 1.28*sigma = 1.28*0.188 = 0.241 percentage points; 0.29 +/- 0.24 gives 0.05 to 0.53.","Counter-considerations: upside risk is a sharp rebound in motor vehicle insurance, airline fares, or energy services that would land above the interval; downside risk is continued declines in communication, insurance, medical care services, or transportation services that would keep July near zero or outside the interval below 0.05 percent."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: Computed adjacent MoM changes include Jul. 2025 0.347 percent, Aug. 2025 0.190 percent, Sep. 2025 0.191 percent, Dec. 2025 0.231 percent, Jan. 2026 0.348 percent, Feb. 2026 0.282 percent, Mar. 2026 0.334 percent, Apr. 2026 0.385 percent, May 2026 0.548 percent, and Jun. 2026 -0.175 percent; the gap around Oct. 2025 was excluded because the fetched table showed a missing Oct. 2025 value.","Base rate/reference class: the recent adjacent-change reference class centers near 0.27 percent per month for services less rent of shelter. I use that as the persistence prior, then adjust slightly upward from June's -0.175 percent because the June release identified unusually weak categories such as motor vehicle insurance and communication, while keeping the adjustment small because broad core services momentum also cooled."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-considerations: upside risk is a sharp rebound in motor vehicle insurance, airline fares, or energy services that would land above the interval; downside risk is continued declines in communication, insurance, medical care services, or transportation services that would keep July near zero or outside the interval below 0.05 percent.","Review disposition: accepted the resolver critique by aligning resolutionSourceUrl with the canonical ALFRED ledger URL and making the MoM transformation from first-print CUSR0000SASL2RS index values explicit; accepted the optional ALFRED source-context and short-sample uncertainty clarification."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Framing and exact resolver: the target is the July 2026 first-print month-over-month percent growth for BLS CPI-U Services Less Rent of Shelter, U.S. city average, seasonally adjusted, series CUSR0000SASL2RS. The ledger sourceBinding points to ALFRED series CUSR0000SASL2RS and targetUnit percent_growth; I keep the ledger target and compute MoM percent growth from the first-print CUSR0000SASL2RS seasonally adjusted index values.","Prior/update/interval: persistence prior is the mean of the 10 fetched adjacent MoM changes from Jul. 2025-Sep. 2025 and Dec. 2025-Jun. 2026, about 0.268 percent; adjustment components are +0.07 for partial rebound from June one-off drags and -0.05 for soft June core-services breadth, giving 0.268 + 0.07 - 0.05 = 0.288, rounded to a 0.29 point forecast. Interval method uses the short 10-observation realized dispersion sample of those MoM percent changes: sigma = 0.188 percentage points, so the 80 percent half-width is about 1.28*sigma = 1.28*0.188 = 0.241 percentage points; 0.29 +/- 0.24 gives 0.05 to 0.53."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-cpi-services-less-rent-shelter-mom-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-12\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-manufacturing-production-mom-july-2026.2026-07-27T18-20-57Z.3b8a78a9799967fd","runId":"run.us-manufacturing-production-mom-july-2026.2026-07-27T18-20-57Z.3b8a78a9799967fd","predictionId":"us-manufacturing-production-mom-july-2026","specId":"spec.us-manufacturing-production-mom-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Reference class/base rate: using the same seasonally adjusted Manufacturing (NAICS) monthly-rate variant, the last six official monthly prints average 0.283 percent. I discount that upward mean because the latest month was flat, durable manufacturing was negative, and the Q2 strength appears front-loaded rather than accelerating into June.","Prior/update/interval: persistence prior is recent Fed G.17 Manufacturing (NAICS) m/m prints from Jan-Jun 2026 [0.1, 0.7, 0.1, 0.7, 0.1, 0.0], with base rate mean 0.283; updates are -0.10 for June flatness, -0.05 for durable weakness, and -0.03 for front-loaded Q2, giving about 0.10 after rounding. For the 80% interval, I use the fetched same-year realized dispersion because the draft evidence set only fetched these exact same-variant monthly changes; sample dispersion of those monthly percent changes is sigma = 0.33, so half-width = 1.28*sigma = 1.28*0.33 = 0.42; point 0.10 minus/plus 0.42 gives [-0.32, 0.52]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing and exact resolver: the target is the Federal Reserve G.17 Manufacturing (NAICS) industrial production monthly percent change, seasonally adjusted, for July 2026. The ledger resolver is ALFRED/FRED IPMAN first-vintage CSV; FRED/ALFRED is therefore used as the bound resolution mirror, while the Federal Reserve G.17 Table 1 Manufacturing (NAICS) monthly percent-change row identifies the official agency variant.","Reference class/base rate: using the same seasonally adjusted Manufacturing (NAICS) monthly-rate variant, the last six official monthly prints average 0.283 percent. I discount that upward mean because the latest month was flat, durable manufacturing was negative, and the Q2 strength appears front-loaded rather than accelerating into June."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["US Manufacturing Production July 2026 First Print","Framing and exact resolver: the target is the Federal Reserve G.17 Manufacturing (NAICS) industrial production monthly percent change, seasonally adjusted, for July 2026. The ledger resolver is ALFRED/FRED IPMAN first-vintage CSV; FRED/ALFRED is therefore used as the bound resolution mirror, while the Federal Reserve G.17 Table 1 Manufacturing (NAICS) monthly percent-change row identifies the official agency variant."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.84, distribution present, forecast step count 1.","evidence":["Tool call: Federal Reserve G.17 current release industry-detail lookup","Prior/update/interval: persistence prior is recent Fed G.17 Manufacturing (NAICS) m/m prints from Jan-Jun 2026 [0.1, 0.7, 0.1, 0.7, 0.1, 0.0], with base rate mean 0.283; updates are -0.10 for June flatness, -0.05 for durable weakness, and -0.03 for front-loaded Q2, giving about 0.10 after rounding. For the 80% interval, I use the fetched same-year realized dispersion because the draft evidence set only fetched these exact same-variant monthly changes; sample dispersion of those monthly percent changes is sigma = 0.33, so half-width = 1.28*sigma = 1.28*0.33 = 0.42; point 0.10 minus/plus 0.42 gives [-0.32, 0.52]."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Reference class/base rate: using the same seasonally adjusted Manufacturing (NAICS) monthly-rate variant, the last six official monthly prints average 0.283 percent. I discount that upward mean because the latest month was flat, durable manufacturing was negative, and the Q2 strength appears front-loaded rather than accelerating into June.","Prior/update/interval: persistence prior is recent Fed G.17 Manufacturing (NAICS) m/m prints from Jan-Jun 2026 [0.1, 0.7, 0.1, 0.7, 0.1, 0.0], with base rate mean 0.283; updates are -0.10 for June flatness, -0.05 for durable weakness, and -0.03 for front-loaded Q2, giving about 0.10 after rounding. For the 80% interval, I use the fetched same-year realized dispersion because the draft evidence set only fetched these exact same-variant monthly changes; sample dispersion of those monthly percent changes is sigma = 0.33, so half-width = 1.28*sigma = 1.28*0.33 = 0.42; point 0.10 minus/plus 0.42 gives [-0.32, 0.52]."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-considerations: upside risk is a July rebound in motor vehicles, high-tech equipment, or petroleum-related manufacturing that would land above the interval; downside risk is a broad durable-goods pullback, auto shutdowns, or machinery/electrical-equipment weakness that would land below the interval; outside the interval would require a monthly move larger than roughly 0.5 percent or below roughly -0.3 percent on the first print."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: persistence prior is recent Fed G.17 Manufacturing (NAICS) m/m prints from Jan-Jun 2026 [0.1, 0.7, 0.1, 0.7, 0.1, 0.0], with base rate mean 0.283; updates are -0.10 for June flatness, -0.05 for durable weakness, and -0.03 for front-loaded Q2, giving about 0.10 after rounding. For the 80% interval, I use the fetched same-year realized dispersion because the draft evidence set only fetched these exact same-variant monthly changes; sample dispersion of those monthly percent changes is sigma = 0.33, so half-width = 1.28*sigma = 1.28*0.33 = 0.42; point 0.10 minus/plus 0.42 gives [-0.32, 0.52].","Counter-considerations: upside risk is a July rebound in motor vehicles, high-tech equipment, or petroleum-related manufacturing that would land above the interval; downside risk is a broad durable-goods pullback, auto shutdowns, or machinery/electrical-equipment weakness that would land below the interval; outside the interval would require a monthly move larger than roughly 0.5 percent or below roughly -0.3 percent on the first print."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-manufacturing-production-mom-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-18\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-manufacturing-capacity-utilization-july-2026.2026-07-27T18-22-55Z.49634c721e70d42e","runId":"run.us-manufacturing-capacity-utilization-july-2026.2026-07-27T18-22-55Z.49634c721e70d42e","predictionId":"us-manufacturing-capacity-utilization-july-2026","specId":"spec.us-manufacturing-capacity-utilization-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: for a one-month-ahead level forecast on this utilization rate, persistence from the latest exact MCUMFN value is the main prior because monthly movements in utilization are small relative to the level. The last three rounded official NAICS readings all sit at 75.6, while the exact latest is 75.5559.","Prior/update/interval: persistence prior = Jun exact 75.5559. Historical sample = short-run realized monthly-change proxy using rounded official Jan-Jun NAICS values plus exact current-vintage FRED/ALFRED Feb-Jun detail: Jan-Feb about +0.50, Feb-Mar +0.0187, Mar-Apr +0.4918, Apr-May +0.0120, May-Jun -0.0620. Adjustment components: level persistence +0.00, momentum +0.02 for Q2 firmness but flat June output, capacity-growth drag approximately -0.01, net about +0.04 before rounding, giving point 75.6. Dispersion: sigma = 0.28 percentage point from those recent successive changes; 1.28*sigma = 0.36, so an 80% interval around 75.6 is about 75.24 to 75.96, rounded to 75.25 to 75.95. This is a fragile short-window sigma, but it is appropriate here as a near-term first-print proxy because the resolver is one month ahead and the last three official rounded readings were stable at 75.6."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Target is Federal Reserve G.17 Capacity Utilization: Manufacturing (NAICS), series MCUMFN, seasonally adjusted percent of capacity. I use the same NAICS variant for anchors and interval work; broader manufacturing and SIC rows are not the resolver. The Federal Reserve table is the official human-facing release, while the machine-resolution path is the ledger ALFRED MCUMFN first-print vintage.","Tool call: Checked the public FRED/ALFRED mirror for exact MCUMFN observations sourced to the Federal Reserve G.17 release."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["US manufacturing NAICS capacity utilization, July 2026 first print","Target is Federal Reserve G.17 Capacity Utilization: Manufacturing (NAICS), series MCUMFN, seasonally adjusted percent of capacity. I use the same NAICS variant for anchors and interval work; broader manufacturing and SIC rows are not the resolver. The Federal Reserve table is the official human-facing release, while the machine-resolution path is the ledger ALFRED MCUMFN first-print vintage."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.7, distribution present, forecast step count 1.","evidence":["Target is Federal Reserve G.17 Capacity Utilization: Manufacturing (NAICS), series MCUMFN, seasonally adjusted percent of capacity. I use the same NAICS variant for anchors and interval work; broader manufacturing and SIC rows are not the resolver. The Federal Reserve table is the official human-facing release, while the machine-resolution path is the ledger ALFRED MCUMFN first-print vintage.","Prior/update/interval: persistence prior = Jun exact 75.5559. Historical sample = short-run realized monthly-change proxy using rounded official Jan-Jun NAICS values plus exact current-vintage FRED/ALFRED Feb-Jun detail: Jan-Feb about +0.50, Feb-Mar +0.0187, Mar-Apr +0.4918, Apr-May +0.0120, May-Jun -0.0620. Adjustment components: level persistence +0.00, momentum +0.02 for Q2 firmness but flat June output, capacity-growth drag approximately -0.01, net about +0.04 before rounding, giving point 75.6. Dispersion: sigma = 0.28 percentage point from those recent successive changes; 1.28*sigma = 0.36, so an 80% interval around 75.6 is about 75.24 to 75.96, rounded to 75.25 to 75.95. This is a fragile short-window sigma, but it is appropriate here as a near-term first-print proxy because the resolver is one month ahead and the last three official rounded readings were stable at 75.6."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate/reference class: for a one-month-ahead level forecast on this utilization rate, persistence from the latest exact MCUMFN value is the main prior because monthly movements in utilization are small relative to the level. The last three rounded official NAICS readings all sit at 75.6, while the exact latest is 75.5559.","Prior/update/interval: persistence prior = Jun exact 75.5559. Historical sample = short-run realized monthly-change proxy using rounded official Jan-Jun NAICS values plus exact current-vintage FRED/ALFRED Feb-Jun detail: Jan-Feb about +0.50, Feb-Mar +0.0187, Mar-Apr +0.4918, Apr-May +0.0120, May-Jun -0.0620. Adjustment components: level persistence +0.00, momentum +0.02 for Q2 firmness but flat June output, capacity-growth drag approximately -0.01, net about +0.04 before rounding, giving point 75.6. Dispersion: sigma = 0.28 percentage point from those recent successive changes; 1.28*sigma = 0.36, so an 80% interval around 75.6 is about 75.24 to 75.96, rounded to 75.25 to 75.95. This is a fragile short-window sigma, but it is appropriate here as a near-term first-print proxy because the resolver is one month ahead and the last three official rounded readings were stable at 75.6."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence prior = Jun exact 75.5559. Historical sample = short-run realized monthly-change proxy using rounded official Jan-Jun NAICS values plus exact current-vintage FRED/ALFRED Feb-Jun detail: Jan-Feb about +0.50, Feb-Mar +0.0187, Mar-Apr +0.4918, Apr-May +0.0120, May-Jun -0.0620. Adjustment components: level persistence +0.00, momentum +0.02 for Q2 firmness but flat June output, capacity-growth drag approximately -0.01, net about +0.04 before rounding, giving point 75.6. Dispersion: sigma = 0.28 percentage point from those recent successive changes; 1.28*sigma = 0.36, so an 80% interval around 75.6 is about 75.24 to 75.96, rounded to 75.25 to 75.95. This is a fragile short-window sigma, but it is appropriate here as a near-term first-print proxy because the resolver is one month ahead and the last three official rounded readings were stable at 75.6.","Counter-considerations: upside risk is a July rebound in manufacturing output, especially motor vehicles or high-tech industries, which would land above the interval if utilization prints above 75.95. Downside risk is a broad production pullback or downward first-print capacity-utilization surprise, which would land below the interval if MCUMFN prints below 75.25. Outside the interval would require roughly a 0.4 percentage point or larger move from June, larger than the recent flat May-June pattern."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Target is Federal Reserve G.17 Capacity Utilization: Manufacturing (NAICS), series MCUMFN, seasonally adjusted percent of capacity. I use the same NAICS variant for anchors and interval work; broader manufacturing and SIC rows are not the resolver. The Federal Reserve table is the official human-facing release, while the machine-resolution path is the ledger ALFRED MCUMFN first-print vintage.","Tool result: The public MCUMFN mirror shows Jun 2026 75.5559, May 2026 75.6179, Apr 2026 75.6059, Mar 2026 75.1141, and Feb 2026 75.0954, updated July 17, 2026; these are current public vintage observations used as forecasting evidence, not the future July first-print outcome."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-manufacturing-capacity-utilization-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-18\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-building-permits-july-2026.2026-07-27T18-25-15Z.817b1d5cc1dd21bd","runId":"run.us-building-permits-july-2026.2026-07-27T18-25-15Z.817b1d5cc1dd21bd","predictionId":"us-building-permits-july-2026","specId":"spec.us-building-permits-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: Checked prior Census New Residential Construction releases and archived/search-indexed release text for the recent first-print reference class.","Base rate/reference class: for this monthly level series, the starting base rate is a random-walk/persistence prior from the latest same-variant first print, 1367 thousand, cross-checked against the recent four-month first-print average of (1372 + 1442 + 1413 + 1367) / 4 = 1398.5 thousand. The recent range is narrow by housing-cycle standards but month-to-month multifamily swings make the next print noisy."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 7 source-context item(s), activity log present.","evidence":["Framing and exact resolver: the target is total privately owned housing units authorized by building permits, seasonally adjusted annual rate, measured in thousands, for July 2026. Census release pages are evidence sources for the agency print, while ALFRED PERMIT first vintage remains the binding ledger resolver; I am using the total SAAR variant throughout rather than single-family, multifamily-only, revised permits, or not-seasonally-adjusted permits.","Tool call: Checked Census Building Permits Survey and Economic Indicators release calendars for New Residential Construction July 2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["US July 2026 Building Permits First Print","Framing and exact resolver: the target is total privately owned housing units authorized by building permits, seasonally adjusted annual rate, measured in thousands, for July 2026. Census release pages are evidence sources for the agency print, while ALFRED PERMIT first vintage remains the binding ledger resolver; I am using the total SAAR variant throughout rather than single-family, multifamily-only, revised permits, or not-seasonally-adjusted permits."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 160, distribution present, forecast step count 1.","evidence":["Prior/update/interval: random-walk/persistence prior = 1367 from June 2026 first print; historical sample = first-print total SAAR permits for March-June 2026 of 1372, 1442, 1413, 1367; adjustment components = +8 thousand partial mean reversion toward the 1398.5 four-month average, -5 thousand for elevated mortgage/Treasury rates, +5 thousand because June starts strength and multifamily volatility argue against extrapolating the full June drop; final point = 1367 + 8 = 1375. Successive changes are +70, -29, -46; sample standard deviation of these changes gives sigma = 62.6 thousand, and 1.28*sigma = 80.2 thousand, so the rounded 80 percent interval is 1375 +/- 80 = [1295, 1455].","Upside risk: a rebound in multifamily applications similar to April's jump, easing local bottlenecks, or builders pulling permits before financing costs rise further would land above the interval. Downside risk: another leg up in mortgage rates, weak single-family demand, or a large reversal in five-plus-unit permits would land below the interval. Outside the interval would require roughly an 80 thousand move from the 1375 center, which is larger than two of the last three monthly changes but still plausible in this series."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Checked public rate context from Freddie Mac PMMS and Federal Reserve H.15 because permits are interest-rate sensitive.","Prior/update/interval: random-walk/persistence prior = 1367 from June 2026 first print; historical sample = first-print total SAAR permits for March-June 2026 of 1372, 1442, 1413, 1367; adjustment components = +8 thousand partial mean reversion toward the 1398.5 four-month average, -5 thousand for elevated mortgage/Treasury rates, +5 thousand because June starts strength and multifamily volatility argue against extrapolating the full June drop; final point = 1367 + 8 = 1375. Successive changes are +70, -29, -46; sample standard deviation of these changes gives sigma = 62.6 thousand, and 1.28*sigma = 80.2 thousand, so the rounded 80 percent interval is 1375 +/- 80 = [1295, 1455]."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: for this monthly level series, the starting base rate is a random-walk/persistence prior from the latest same-variant first print, 1367 thousand, cross-checked against the recent four-month first-print average of (1372 + 1442 + 1413 + 1367) / 4 = 1398.5 thousand. The recent range is narrow by housing-cycle standards but month-to-month multifamily swings make the next print noisy.","Upside risk: a rebound in multifamily applications similar to April's jump, easing local bottlenecks, or builders pulling permits before financing costs rise further would land above the interval. Downside risk: another leg up in mortgage rates, weak single-family demand, or a large reversal in five-plus-unit permits would land below the interval. Outside the interval would require roughly an 80 thousand move from the 1375 center, which is larger than two of the last three monthly changes but still plausible in this series."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: random-walk/persistence prior = 1367 from June 2026 first print; historical sample = first-print total SAAR permits for March-June 2026 of 1372, 1442, 1413, 1367; adjustment components = +8 thousand partial mean reversion toward the 1398.5 four-month average, -5 thousand for elevated mortgage/Treasury rates, +5 thousand because June starts strength and multifamily volatility argue against extrapolating the full June drop; final point = 1367 + 8 = 1375. Successive changes are +70, -29, -46; sample standard deviation of these changes gives sigma = 62.6 thousand, and 1.28*sigma = 80.2 thousand, so the rounded 80 percent interval is 1375 +/- 80 = [1295, 1455].","Upside risk: a rebound in multifamily applications similar to April's jump, easing local bottlenecks, or builders pulling permits before financing costs rise further would land above the interval. Downside risk: another leg up in mortgage rates, weak single-family demand, or a large reversal in five-plus-unit permits would land below the interval. Outside the interval would require roughly an 80 thousand move from the 1375 center, which is larger than two of the last three monthly changes but still plausible in this series."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-building-permits-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-18\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-durable-goods-orders-mom-june-2026.2026-07-26T00-59-31Z.20228e44c26b3bf7","runId":"run.us-durable-goods-orders-mom-june-2026.2026-07-26T00-59-31Z.20228e44c26b3bf7","predictionId":"us-durable-goods-orders-mom-june-2026","specId":"spec.us-durable-goods-orders-mom-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate / reference class: using the recent DGORDER monthly percent changes from January 2024 through May 2026 gives a volatile 29-observation reference class with mean about +0.47 percentage point and sigma about 5.15 percentage points. The series is dominated by aircraft and other transportation swings, so the May transportation drop and June aircraft order rebound matter more than a smooth manufacturing trend.","Prior/update/interval: persistence prior is the 2024-01 to 2026-05 DGORDER MoM base rate mean of +0.47 pp. I add +1.3 pp for transport/aircraft rebound after May's -14.0 percent transportation drop and June Boeing order strength, +0.4 pp for ISM new orders at 56.0, subtract 0.2 pp for flat Fed manufacturing output, and subtract 0.2 pp for softer exports/prices drag, giving +1.8 percent. Interval method uses realized dispersion of DGORDER MoM values themselves: sigma = 5.15, so 80 percent half-width is roughly 1.28*sigma = 1.28*5.15 = 6.59 pp; +1.8 +/- 6.6 gives [-4.8, 8.4] after rounding."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 8 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this targets the Census M3 Advance Report headline series for manufacturers' new orders for durable goods, seasonally adjusted, FRED/ALFRED series code DGORDER. The ledger source binding points to ALFRED DGORDER as the resolution mirror, while the underlying statistical release is the Census M3 Advance Report; I am forecasting the first-print month-over-month percent growth for June 2026, not the later full M3 revision.","Tool call: Checked Census M3 release schedule and Census economic indicators calendar for the June 2026 advance durable goods release date."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["US durable goods orders MoM, June 2026 first print","Framing and exact resolver: this targets the Census M3 Advance Report headline series for manufacturers' new orders for durable goods, seasonally adjusted, FRED/ALFRED series code DGORDER. The ledger source binding points to ALFRED DGORDER as the resolution mirror, while the underlying statistical release is the Census M3 Advance Report; I am forecasting the first-print month-over-month percent growth for June 2026, not the later full M3 revision."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 13.2, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is the 2024-01 to 2026-05 DGORDER MoM base rate mean of +0.47 pp. I add +1.3 pp for transport/aircraft rebound after May's -14.0 percent transportation drop and June Boeing order strength, +0.4 pp for ISM new orders at 56.0, subtract 0.2 pp for flat Fed manufacturing output, and subtract 0.2 pp for softer exports/prices drag, giving +1.8 percent. Interval method uses realized dispersion of DGORDER MoM values themselves: sigma = 5.15, so 80 percent half-width is roughly 1.28*sigma = 1.28*5.15 = 6.59 pp; +1.8 +/- 6.6 gives [-4.8, 8.4] after rounding.","Counter-considerations: upside risk is a much larger-than-assumed aircraft booking print or defense capital-goods jump, which would land above the interval if total orders rise more than about 8.4 percent. Downside risk is that June aircraft orders do not translate into Census M3 timing, or nontransport durable categories reverse despite ISM breadth, which would land below the interval if total orders fall more than about 4.8 percent."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-considerations: upside risk is a much larger-than-assumed aircraft booking print or defense capital-goods jump, which would land above the interval if total orders rise more than about 8.4 percent. Downside risk is that June aircraft orders do not translate into Census M3 timing, or nontransport durable categories reverse despite ISM breadth, which would land below the interval if total orders fall more than about 4.8 percent."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Framing and exact resolver: this targets the Census M3 Advance Report headline series for manufacturers' new orders for durable goods, seasonally adjusted, FRED/ALFRED series code DGORDER. The ledger source binding points to ALFRED DGORDER as the resolution mirror, while the underlying statistical release is the Census M3 Advance Report; I am forecasting the first-print month-over-month percent growth for June 2026, not the later full M3 revision.","Tool call: Read the current Census M3 advance durable goods release for the latest first-print reference point."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-durable-goods-orders-mom-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-27\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-durable-goods-shipments-mom-june-2026.2026-07-26T01-03-07Z.e398d59e5b0e31a9","runId":"run.us-durable-goods-shipments-mom-june-2026.2026-07-26T01-03-07Z.e398d59e5b0e31a9","predictionId":"us-durable-goods-shipments-mom-june-2026","specId":"spec.us-durable-goods-shipments-mom-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the 2024-02 through 2026-05 AMDMVS month-over-month changes have a mean of 0.455 percentage points, while the latest four reported changes were all positive at 1.563, 0.793, 0.684, and 1.004 percent, so the base rate is modest positive growth with unusually firm recent momentum.","Prior/update/interval: simple mean-plus-momentum prior is the 2024-02 to 2026-05 AMDMVS m/m reference class. Historical sample = 28 monthly percent changes computed from fetched AMDMVS levels; mean = 0.455. Adjustment components: +0.20 for broad early-2026 positive momentum, -0.05 for mean reversion after four consecutive gains, giving point = 0.60. Interval method uses realized dispersion of the m/m percent changes: sum of squares = 16.9229, sigma = sqrt((16.9229 - 28*0.4550^2)/27) = 0.642 percentage points, so 1.28*sigma = 0.822; point 0.60 +/- 0.82 gives [-0.22, 1.42]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: the target is Census M3 durable-goods shipments, seasonally adjusted AMDMVS, June 2026 first print. The Census release schedule verifies the June 2026 Advance Report date as 2026-07-27, with the Full Report on 2026-08-04; I use the advance first print only.","Tool call: Opened Census M3 release schedule for June 2026 advance and full report dates."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: the target is Census M3 durable-goods shipments, seasonally adjusted AMDMVS, June 2026 first print. The Census release schedule verifies the June 2026 Advance Report date as 2026-07-27, with the Full Report on 2026-08-04; I use the advance first print only.","Tool call: Opened Census M3 release schedule for June 2026 advance and full report dates."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.64, distribution present, forecast step count 1.","evidence":["Prior/update/interval: simple mean-plus-momentum prior is the 2024-02 to 2026-05 AMDMVS m/m reference class. Historical sample = 28 monthly percent changes computed from fetched AMDMVS levels; mean = 0.455. Adjustment components: +0.20 for broad early-2026 positive momentum, -0.05 for mean reversion after four consecutive gains, giving point = 0.60. Interval method uses realized dispersion of the m/m percent changes: sum of squares = 16.9229, sigma = sqrt((16.9229 - 28*0.4550^2)/27) = 0.642 percentage points, so 1.28*sigma = 0.822; point 0.60 +/- 0.82 gives [-0.22, 1.42].","Counter-consideration: upside risk is a stronger transportation-equipment or machinery shipment month that would land above the interval, especially if June catches delayed May shipments. Downside risk is a pullback after the strong January-May level rise or a volatile transportation drop; a broad reversal below about -0.22 percent would land outside the interval on the low side."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate/reference class: the 2024-02 through 2026-05 AMDMVS month-over-month changes have a mean of 0.455 percentage points, while the latest four reported changes were all positive at 1.563, 0.793, 0.684, and 1.004 percent, so the base rate is modest positive growth with unusually firm recent momentum.","Prior/update/interval: simple mean-plus-momentum prior is the 2024-02 to 2026-05 AMDMVS m/m reference class. Historical sample = 28 monthly percent changes computed from fetched AMDMVS levels; mean = 0.455. Adjustment components: +0.20 for broad early-2026 positive momentum, -0.05 for mean reversion after four consecutive gains, giving point = 0.60. Interval method uses realized dispersion of the m/m percent changes: sum of squares = 16.9229, sigma = sqrt((16.9229 - 28*0.4550^2)/27) = 0.642 percentage points, so 1.28*sigma = 0.822; point 0.60 +/- 0.82 gives [-0.22, 1.42]."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-consideration: upside risk is a stronger transportation-equipment or machinery shipment month that would land above the interval, especially if June catches delayed May shipments. Downside risk is a pullback after the strong January-May level rise or a volatile transportation drop; a broad reversal below about -0.22 percent would land outside the interval on the low side."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for June 2026 Durable Goods Shipments MoM","Base rate/reference class: the 2024-02 through 2026-05 AMDMVS month-over-month changes have a mean of 0.455 percentage points, while the latest four reported changes were all positive at 1.563, 0.793, 0.684, and 1.004 percent, so the base rate is modest positive growth with unusually firm recent momentum."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-durable-goods-shipments-mom-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-27\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-construction-spending-mom-june-2026.2026-07-26T01-09-32Z.03694e1ddb9162ca","runId":"run.us-construction-spending-mom-june-2026.2026-07-26T01-09-32Z.03694e1ddb9162ca","predictionId":"us-construction-spending-mom-june-2026","specId":"spec.us-construction-spending-mom-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Reference class/base rate: using recent TTLCONS level-implied total construction spending MoM changes, Feb through May 2026 were -0.271, +0.444, +0.348, and +0.143 percent, averaging about +0.166 percent. The base rate is therefore mildly positive, but May's first-print headline was only +0.1 percent and year-to-date spending was reported 2.7 percent below the same 2025 period.","Prior/update/interval: persistence prior is the recent Census/TTLCONS revised MoM history for Feb-May 2026, values -0.271, 0.444, 0.348, 0.143 percent. Adjustment components: -0.08 pp for falling June permits and still-soft private/residential conditions, +0.04 pp for the June starts/completions rebound, and -0.08 pp for slowing May total momentum versus the +0.166 base rate, giving a point near +0.05 percent. Interval method: sample dispersion of those four MoM values gives sigma = 0.317 percentage points; 1.28*sigma = 0.406 pp, so an 80 percent interval around 0.05 is about -0.36 to +0.46 percent after rounding. The four-month sample makes this band approximate, but it is anchored to realized recent monthly dispersion rather than a round hedge."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Forecast for June 2026 total construction spending MoM","Framing and exact resolver: this is the Census Value of Construction Put in Place total construction series, seasonally adjusted annual rate, first print for June 2026. The ledger binds dataPointId census.construction_spending.total_mom.2026_06.first_print and TTLCONS; the economic target is the headline percent change from revised May to June in the first Census release, while the mechanical ledger binding uses the ALFRED TTLCONS vintage mirror for reproducible first-print resolution."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this is the Census Value of Construction Put in Place total construction series, seasonally adjusted annual rate, first print for June 2026. The ledger binds dataPointId census.construction_spending.total_mom.2026_06.first_print and TTLCONS; the economic target is the headline percent change from revised May to June in the first Census release, while the mechanical ledger binding uses the ALFRED TTLCONS vintage mirror for reproducible first-print resolution.","Tool call: Checked Census Construction Spending release schedule for the June 2026 reporting period."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.82, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is the recent Census/TTLCONS revised MoM history for Feb-May 2026, values -0.271, 0.444, 0.348, 0.143 percent. Adjustment components: -0.08 pp for falling June permits and still-soft private/residential conditions, +0.04 pp for the June starts/completions rebound, and -0.08 pp for slowing May total momentum versus the +0.166 base rate, giving a point near +0.05 percent. Interval method: sample dispersion of those four MoM values gives sigma = 0.317 percentage points; 1.28*sigma = 0.406 pp, so an 80 percent interval around 0.05 is about -0.36 to +0.46 percent after rounding. The four-month sample makes this band approximate, but it is anchored to realized recent monthly dispersion rather than a round hedge.","The variant is total construction spending, seasonally adjusted annual rate, not unadjusted monthly dollars and not a private-only, residential-only, or FRED-transformed growth variant. Public construction is a meaningful upside risk because May public spending was +0.5 percent MoM, while downside risk comes from private nonresidential weakness and permits down 3.0 percent in June. A public-construction surge plus resilient private work large enough to push total spending more than about 0.46 percent MoM would land above the interval; a private residential or nonresidential pullback large enough to push total spending below about -0.36 percent MoM would land below the interval, outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior is the recent Census/TTLCONS revised MoM history for Feb-May 2026, values -0.271, 0.444, 0.348, 0.143 percent. Adjustment components: -0.08 pp for falling June permits and still-soft private/residential conditions, +0.04 pp for the June starts/completions rebound, and -0.08 pp for slowing May total momentum versus the +0.166 base rate, giving a point near +0.05 percent. Interval method: sample dispersion of those four MoM values gives sigma = 0.317 percentage points; 1.28*sigma = 0.406 pp, so an 80 percent interval around 0.05 is about -0.36 to +0.46 percent after rounding. The four-month sample makes this band approximate, but it is anchored to realized recent monthly dispersion rather than a round hedge.","The variant is total construction spending, seasonally adjusted annual rate, not unadjusted monthly dollars and not a private-only, residential-only, or FRED-transformed growth variant. Public construction is a meaningful upside risk because May public spending was +0.5 percent MoM, while downside risk comes from private nonresidential weakness and permits down 3.0 percent in June. A public-construction surge plus resilient private work large enough to push total spending more than about 0.46 percent MoM would land above the interval; a private residential or nonresidential pullback large enough to push total spending below about -0.36 percent MoM would land below the interval, outside the interval."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Reference class/base rate: using recent TTLCONS level-implied total construction spending MoM changes, Feb through May 2026 were -0.271, +0.444, +0.348, and +0.143 percent, averaging about +0.166 percent. The base rate is therefore mildly positive, but May's first-print headline was only +0.1 percent and year-to-date spending was reported 2.7 percent below the same 2025 period.","Prior/update/interval: persistence prior is the recent Census/TTLCONS revised MoM history for Feb-May 2026, values -0.271, 0.444, 0.348, 0.143 percent. Adjustment components: -0.08 pp for falling June permits and still-soft private/residential conditions, +0.04 pp for the June starts/completions rebound, and -0.08 pp for slowing May total momentum versus the +0.166 base rate, giving a point near +0.05 percent. Interval method: sample dispersion of those four MoM values gives sigma = 0.317 percentage points; 1.28*sigma = 0.406 pp, so an 80 percent interval around 0.05 is about -0.36 to +0.46 percent after rounding. The four-month sample makes this band approximate, but it is anchored to realized recent monthly dispersion rather than a round hedge."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for June 2026 total construction spending MoM","Framing and exact resolver: this is the Census Value of Construction Put in Place total construction series, seasonally adjusted annual rate, first print for June 2026. The ledger binds dataPointId census.construction_spending.total_mom.2026_06.first_print and TTLCONS; the economic target is the headline percent change from revised May to June in the first Census release, while the mechanical ledger binding uses the ALFRED TTLCONS vintage mirror for reproducible first-print resolution."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-construction-spending-mom-june-2026\nrunLabel: Headline\nresolutionDate: 2026-08-03\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.jolts-hires-rate-june-2026.2026-07-26T01-11-27Z.392d9883e1d08cb2","runId":"run.jolts-hires-rate-june-2026.2026-07-26T01-11-27Z.392d9883e1d08cb2","predictionId":"jolts-hires-rate-june-2026","specId":"spec.jolts-hires-rate-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: over the BLS Jun 2024-May 2026 recent expansion/cooling sample, the rate mostly sits from 3.2 to 3.4 percent, with only Feb 2026 at 3.1 and Mar 2026 at 3.5 breaking that tight range. That makes persistence around 3.3 the outside-view prior.","Prior/update/interval: persistence prior model uses latest official May 2026 value 3.30 percent; historical sample is the 23 successive monthly changes from the BLS Jun 2024-May 2026 hires-rate series. Level effect 0.00 because May and Apr are both 3.3; momentum effect 0.00 after the Feb-Mar-Apr-May swings net back to 3.3; one-off/policy-mechanism effect 0.00 because this is a labor-turnover rate with no release-specific policy reset. Successive-change sum of squares is 0.41, sample sigma = sqrt(0.41/22) = 0.14 percentage point, so 80 percent half-width is about 1.28*sigma = 1.28*0.14 = 0.18. Final bounds are 3.30 - 0.18 = 3.12 and 3.30 + 0.18 = 3.48."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Forecast for June 2026 BLS JOLTS hires rate","Framing: this is the BLS JOLTS Total nonfarm hires rate, seasonally adjusted, for June 2026, first print, tied to ledger source series JTSHIR. The ledger binding names the JOLTS news release table and the ALFRED/FRED first-print adapter; the BLS support table inspected for the current release is Table 2, while the registered resolver text says Table 1. I keep the forecast tied to the canonical JTSHIR first-print target and use BLS table evidence only as support."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing: this is the BLS JOLTS Total nonfarm hires rate, seasonally adjusted, for June 2026, first print, tied to ledger source series JTSHIR. The ledger binding names the JOLTS news release table and the ALFRED/FRED first-print adapter; the BLS support table inspected for the current release is Table 2, while the registered resolver text says Table 1. I keep the forecast tied to the canonical JTSHIR first-print target and use BLS table evidence only as support.","Tool call: Checked the BLS JOLTS release schedule for the June 2026 reference month."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.36, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior model uses latest official May 2026 value 3.30 percent; historical sample is the 23 successive monthly changes from the BLS Jun 2024-May 2026 hires-rate series. Level effect 0.00 because May and Apr are both 3.3; momentum effect 0.00 after the Feb-Mar-Apr-May swings net back to 3.3; one-off/policy-mechanism effect 0.00 because this is a labor-turnover rate with no release-specific policy reset. Successive-change sum of squares is 0.41, sample sigma = sqrt(0.41/22) = 0.14 percentage point, so 80 percent half-width is about 1.28*sigma = 1.28*0.14 = 0.18. Final bounds are 3.30 - 0.18 = 3.12 and 3.30 + 0.18 = 3.48.","Counter-consideration: upside risk is a rebound in gross hiring similar to Mar 2026 that would land above the interval at about 3.5 percent or higher; downside risk is a broad hiring freeze like Feb 2026 that would land below the interval near 3.1 percent or lower. The outside the interval cases are plausible but need a much sharper monthly move than the May/April stability implies."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior model uses latest official May 2026 value 3.30 percent; historical sample is the 23 successive monthly changes from the BLS Jun 2024-May 2026 hires-rate series. Level effect 0.00 because May and Apr are both 3.3; momentum effect 0.00 after the Feb-Mar-Apr-May swings net back to 3.3; one-off/policy-mechanism effect 0.00 because this is a labor-turnover rate with no release-specific policy reset. Successive-change sum of squares is 0.41, sample sigma = sqrt(0.41/22) = 0.14 percentage point, so 80 percent half-width is about 1.28*sigma = 1.28*0.14 = 0.18. Final bounds are 3.30 - 0.18 = 3.12 and 3.30 + 0.18 = 3.48."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-consideration: upside risk is a rebound in gross hiring similar to Mar 2026 that would land above the interval at about 3.5 percent or higher; downside risk is a broad hiring freeze like Feb 2026 that would land below the interval near 3.1 percent or lower. The outside the interval cases are plausible but need a much sharper monthly move than the May/April stability implies."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for June 2026 BLS JOLTS hires rate","Framing: this is the BLS JOLTS Total nonfarm hires rate, seasonally adjusted, for June 2026, first print, tied to ledger source series JTSHIR. The ledger binding names the JOLTS news release table and the ALFRED/FRED first-print adapter; the BLS support table inspected for the current release is Table 2, while the registered resolver text says Table 1. I keep the forecast tied to the canonical JTSHIR first-print target and use BLS table evidence only as support."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: jolts-hires-rate-june-2026\nrunLabel: Headline\nresolutionDate: 2026-08-04\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.jolts-hires-rate-june-2026.2026-07-31T14-00-26Z.jolts-hires-rate-june-2026-challenge-github-pavelmakarchuk-2026-07-31t14-00-26z.fda2c307a15c1d96","runId":"run.jolts-hires-rate-june-2026.2026-07-31T14-00-26Z.jolts-hires-rate-june-2026-challenge-github-pavelmakarchuk-2026-07-31t14-00-26z.fda2c307a15c1d96","predictionId":"jolts-hires-rate-june-2026","specId":"spec.jolts-hires-rate-june-2026","runLabel":"PavelMakarchuk challenge submission","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.95,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 6 historical point(s) and explicit outside-view language.","evidence":["Base rate: May 2026 print 3.3 (JTSHIR); 24m MoM-change stdev ~0.135pp, 20/24 changes within +/-0.1pp. June payrolls +57k with weak leisure/hospitality hiring tilts risk slightly down; claims calm near 215k. First-print resolution: ALFRED vintages show +/-0.1pp first-print revisions (Apr 2026 printed 3.2, revised 3.3), so interval widened ~0.05pp beyond the pure MoM base rate."]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 0 typed tool call(s), 1 source-context item(s), activity log absent.","evidence":["Base rate: May 2026 print 3.3 (JTSHIR); 24m MoM-change stdev ~0.135pp, 20/24 changes within +/-0.1pp. June payrolls +57k with weak leisure/hospitality hiring tilts risk slightly down; claims calm near 215k. First-print resolution: ALFRED vintages show +/-0.1pp first-print revisions (Apr 2026 printed 3.2, revised 3.3), so interval widened ~0.05pp beyond the pure MoM base rate."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Published challenge submission","Base rate: May 2026 print 3.3 (JTSHIR); 24m MoM-change stdev ~0.135pp, 20/24 changes within +/-0.1pp. June payrolls +57k with weak leisure/hospitality hiring tilts risk slightly down; claims calm near 215k. First-print resolution: ALFRED vintages show +/-0.1pp first-print revisions (Apr 2026 printed 3.2, revised 3.3), so interval widened ~0.05pp beyond the pure MoM base rate."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.35, distribution present, forecast step count 1.","evidence":["Base rate: May 2026 print 3.3 (JTSHIR); 24m MoM-change stdev ~0.135pp, 20/24 changes within +/-0.1pp. June payrolls +57k with weak leisure/hospitality hiring tilts risk slightly down; claims calm near 215k. First-print resolution: ALFRED vintages show +/-0.1pp first-print revisions (Apr 2026 printed 3.2, revised 3.3), so interval widened ~0.05pp beyond the pure MoM base rate.","Forecast: point 3.3, 80% interval [3.1, 3.45]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Base rate: May 2026 print 3.3 (JTSHIR); 24m MoM-change stdev ~0.135pp, 20/24 changes within +/-0.1pp. June payrolls +57k with weak leisure/hospitality hiring tilts risk slightly down; claims calm near 215k. First-print resolution: ALFRED vintages show +/-0.1pp first-print revisions (Apr 2026 printed 3.2, revised 3.3), so interval widened ~0.05pp beyond the pure MoM base rate."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Base rate: May 2026 print 3.3 (JTSHIR); 24m MoM-change stdev ~0.135pp, 20/24 changes within +/-0.1pp. June payrolls +57k with weak leisure/hospitality hiring tilts risk slightly down; claims calm near 215k. First-print resolution: ALFRED vintages show +/-0.1pp first-print revisions (Apr 2026 printed 3.2, revised 3.3), so interval widened ~0.05pp beyond the pure MoM base rate.","Forecast: point 3.3, 80% interval [3.1, 3.45]"]}],"flags":["weak_counterarguments","no_typed_tool_call"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: jolts-hires-rate-june-2026\nrunLabel: PavelMakarchuk challenge submission\nresolutionDate: 2026-08-04\ntraceLineCount: 5\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments, no_typed_tool_call."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-unit-labor-costs-q2-2026-prelim.2026-07-26T01-13-52Z.e13e253874187b37","runId":"run.us-unit-labor-costs-q2-2026-prelim.2026-07-26T01-13-52Z.e13e253874187b37","predictionId":"us-unit-labor-costs-q2-2026-prelim","specId":"spec.us-unit-labor-costs-q2-2026-prelim","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: using the same BLS nonfarm business unit-labor-costs variant, recent revised values from 2021 Q3 through 2026 Q1 average about 2.9 percent annualized, while the last four preliminary first prints before this target average about 1.2 percent but with a shutdown/benchmark-distorted negative Q3 2025. I weight the broader base rate more than the short preliminary sequence because this series is mechanically noisy and revised.","Prior/update/interval: persistence/base-rate prior is 2.9 from the 2021 Q3-2026 Q1 BLS revised-vintage reference class; no separate AR or time-series model was used beyond this persistence/base-rate anchor. Update components: Q1 revised ULC of 1.8 pulls slightly down, June payroll-hours softness with aggregate weekly hours 116.6 in April, 116.7 in May, and 116.8 in June supports positive productivity but not a boom, and 3.5 percent year-over-year hourly earnings plus recent compensation volatility keep compensation growth near 3.5-4.0. Net update leaves point near 3.0. Interval method uses realized dispersion of same-series quarterly annualized revised-vintage values [8.0, 3.5, 7.2, 3.5, 7.0, -1.7, 2.2, 2.4, 1.2, 1.2, 5.5, 1.1, 1.1, 2.9, 7.3, -2.9, 1.0, 2.1, 1.8]; sample sigma = 3.0, so 80 percent half-width is about 1.28*sigma = 1.28*3.0 = 3.8. Point 3.0 minus/plus 3.8 gives -0.8 to 6.8."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 10 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this is BLS nonfarm business sector unit labor costs, seasonally adjusted percent change from previous quarter at an annual rate, first print for 2026 Q2. The official underlying publication is BLS Productivity and Costs, while the canonical ledger binding resolves through the ALFRED/FRED first-print mirror for PRS85006112.","Tool call: BLS Productivity and Costs release schedule lookup"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this is BLS nonfarm business sector unit labor costs, seasonally adjusted percent change from previous quarter at an annual rate, first print for 2026 Q2. The official underlying publication is BLS Productivity and Costs, while the canonical ledger binding resolves through the ALFRED/FRED first-print mirror for PRS85006112.","Tool call: BLS Productivity and Costs release schedule lookup"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 7.6, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence/base-rate prior is 2.9 from the 2021 Q3-2026 Q1 BLS revised-vintage reference class; no separate AR or time-series model was used beyond this persistence/base-rate anchor. Update components: Q1 revised ULC of 1.8 pulls slightly down, June payroll-hours softness with aggregate weekly hours 116.6 in April, 116.7 in May, and 116.8 in June supports positive productivity but not a boom, and 3.5 percent year-over-year hourly earnings plus recent compensation volatility keep compensation growth near 3.5-4.0. Net update leaves point near 3.0. Interval method uses realized dispersion of same-series quarterly annualized revised-vintage values [8.0, 3.5, 7.2, 3.5, 7.0, -1.7, 2.2, 2.4, 1.2, 1.2, 5.5, 1.1, 1.1, 2.9, 7.3, -2.9, 1.0, 2.1, 1.8]; sample sigma = 3.0, so 80 percent half-width is about 1.28*sigma = 1.28*3.0 = 3.8. Point 3.0 minus/plus 3.8 gives -0.8 to 6.8.","Counter-considerations: upside risk is a compensation-per-hour jump with only modest output growth, which would land above the interval if preliminary hourly compensation prints near 8 percent and productivity is flat or negative. Downside risk is a strong Q2 output/productivity first print combined with subdued compensation, which would land below the interval if productivity exceeds compensation by more than about 1 percentage point annualized."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Reference class and base rate: using the same BLS nonfarm business unit-labor-costs variant, recent revised values from 2021 Q3 through 2026 Q1 average about 2.9 percent annualized, while the last four preliminary first prints before this target average about 1.2 percent but with a shutdown/benchmark-distorted negative Q3 2025. I weight the broader base rate more than the short preliminary sequence because this series is mechanically noisy and revised."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Reference class and base rate: using the same BLS nonfarm business unit-labor-costs variant, recent revised values from 2021 Q3 through 2026 Q1 average about 2.9 percent annualized, while the last four preliminary first prints before this target average about 1.2 percent but with a shutdown/benchmark-distorted negative Q3 2025. I weight the broader base rate more than the short preliminary sequence because this series is mechanically noisy and revised.","Prior/update/interval: persistence/base-rate prior is 2.9 from the 2021 Q3-2026 Q1 BLS revised-vintage reference class; no separate AR or time-series model was used beyond this persistence/base-rate anchor. Update components: Q1 revised ULC of 1.8 pulls slightly down, June payroll-hours softness with aggregate weekly hours 116.6 in April, 116.7 in May, and 116.8 in June supports positive productivity but not a boom, and 3.5 percent year-over-year hourly earnings plus recent compensation volatility keep compensation growth near 3.5-4.0. Net update leaves point near 3.0. Interval method uses realized dispersion of same-series quarterly annualized revised-vintage values [8.0, 3.5, 7.2, 3.5, 7.0, -1.7, 2.2, 2.4, 1.2, 1.2, 5.5, 1.1, 1.1, 2.9, 7.3, -2.9, 1.0, 2.1, 1.8]; sample sigma = 3.0, so 80 percent half-width is about 1.28*sigma = 1.28*3.0 = 3.8. Point 3.0 minus/plus 3.8 gives -0.8 to 6.8."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Variant control: all anchors above are nonfarm business sector, seasonally adjusted, percent change from previous quarter at an annual rate. I do not mix in manufacturing, year-over-year, index-level, or final-vintage-only variants for the point forecast.","Prior/update/interval: persistence/base-rate prior is 2.9 from the 2021 Q3-2026 Q1 BLS revised-vintage reference class; no separate AR or time-series model was used beyond this persistence/base-rate anchor. Update components: Q1 revised ULC of 1.8 pulls slightly down, June payroll-hours softness with aggregate weekly hours 116.6 in April, 116.7 in May, and 116.8 in June supports positive productivity but not a boom, and 3.5 percent year-over-year hourly earnings plus recent compensation volatility keep compensation growth near 3.5-4.0. Net update leaves point near 3.0. Interval method uses realized dispersion of same-series quarterly annualized revised-vintage values [8.0, 3.5, 7.2, 3.5, 7.0, -1.7, 2.2, 2.4, 1.2, 1.2, 5.5, 1.1, 1.1, 2.9, 7.3, -2.9, 1.0, 2.1, 1.8]; sample sigma = 3.0, so 80 percent half-width is about 1.28*sigma = 1.28*3.0 = 3.8. Point 3.0 minus/plus 3.8 gives -0.8 to 6.8."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-unit-labor-costs-q2-2026-prelim\nrunLabel: Headline\nresolutionDate: 2026-08-06\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-consumer-credit-annual-rate-june-2026.2026-07-26T01-16-00Z.99a3c924202a99c7","runId":"run.us-consumer-credit-annual-rate-june-2026.2026-07-26T01-16-00Z.99a3c924202a99c7","predictionId":"us-consumer-credit-annual-rate-june-2026","specId":"spec.us-consumer-credit-annual-rate-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: for the same TOTALSLAR variant, the 2024-01 through 2026-05 fetched values average about 2.14 percent annualized. The most recent five values average about 2.59, but May's -0.04 was a sharp reversal after March-April strength, so I use a base rate near 2.1 and only a small rebound adjustment.","Prior/update/interval: persistence/base-rate prior = 2.14 from the 29 monthly TOTALSLAR observations from 2024-01 through 2026-05; this simple recent-history time-series model is used without a richer structural model because the evidence set is recent monthly annualized first-print history. Adjustment components are +0.2 for rebound from May's revolving-credit drag, -0.1 for still-tight consumer-credit conditions, and roughly 0.0 for nonrevolving steadiness, giving point 2.2. Interval method uses realized dispersion of those same annualized change-rate values: sigma = 1.71; 1.28*sigma = 2.19, rounded and modestly widened to a 2.4-point half-width because the May-to-June first print can swing with revolving credit, implying about -0.2 to 4.6."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 8 source-context item(s), activity log present.","evidence":["US G.19 total consumer credit annual-rate forecast for June 2026","Framing and exact resolver: this targets TOTALSLAR, the Federal Reserve G.19 total consumer credit percent change at annual rate, seasonally adjusted, for June 2026. The first official print is the value to resolve; later revisions are excluded. The ledger sourceBinding uses the ALFRED/FRED TOTALSLAR first-vintage mirror for mechanical resolution, while the substantive agency release is Federal Reserve G.19 Consumer Credit."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this targets TOTALSLAR, the Federal Reserve G.19 total consumer credit percent change at annual rate, seasonally adjusted, for June 2026. The first official print is the value to resolve; later revisions are excluded. The ledger sourceBinding uses the ALFRED/FRED TOTALSLAR first-vintage mirror for mechanical resolution, while the substantive agency release is Federal Reserve G.19 Consumer Credit.","Tool call: Federal Reserve statistical release calendar lookup for August 2026 G.19 Consumer Credit"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.8, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence/base-rate prior = 2.14 from the 29 monthly TOTALSLAR observations from 2024-01 through 2026-05; this simple recent-history time-series model is used without a richer structural model because the evidence set is recent monthly annualized first-print history. Adjustment components are +0.2 for rebound from May's revolving-credit drag, -0.1 for still-tight consumer-credit conditions, and roughly 0.0 for nonrevolving steadiness, giving point 2.2. Interval method uses realized dispersion of those same annualized change-rate values: sigma = 1.71; 1.28*sigma = 2.19, rounded and modestly widened to a 2.4-point half-width because the May-to-June first print can swing with revolving credit, implying about -0.2 to 4.6.","Upside risk: a rebound in revolving balances after May's -4.71 revolving annual rate plus steady nonrevolving growth would land above the interval if total credit re-accelerates past about 4.6 percent annualized. Downside risk: another revolving contraction or auto/student nonrevolving weakness would land below the interval if the total annual rate is more negative than about -0.2. An outside the interval outcome is plausible mainly through unusually large revolving-card paydown or unusually strong June borrowing."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence/base-rate prior = 2.14 from the 29 monthly TOTALSLAR observations from 2024-01 through 2026-05; this simple recent-history time-series model is used without a richer structural model because the evidence set is recent monthly annualized first-print history. Adjustment components are +0.2 for rebound from May's revolving-credit drag, -0.1 for still-tight consumer-credit conditions, and roughly 0.0 for nonrevolving steadiness, giving point 2.2. Interval method uses realized dispersion of those same annualized change-rate values: sigma = 1.71; 1.28*sigma = 2.19, rounded and modestly widened to a 2.4-point half-width because the May-to-June first print can swing with revolving credit, implying about -0.2 to 4.6."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Reference class and base rate: for the same TOTALSLAR variant, the 2024-01 through 2026-05 fetched values average about 2.14 percent annualized. The most recent five values average about 2.59, but May's -0.04 was a sharp reversal after March-April strength, so I use a base rate near 2.1 and only a small rebound adjustment.","Upside risk: a rebound in revolving balances after May's -4.71 revolving annual rate plus steady nonrevolving growth would land above the interval if total credit re-accelerates past about 4.6 percent annualized. Downside risk: another revolving contraction or auto/student nonrevolving weakness would land below the interval if the total annual rate is more negative than about -0.2. An outside the interval outcome is plausible mainly through unusually large revolving-card paydown or unusually strong June borrowing."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["US G.19 total consumer credit annual-rate forecast for June 2026","Prior/update/interval: persistence/base-rate prior = 2.14 from the 29 monthly TOTALSLAR observations from 2024-01 through 2026-05; this simple recent-history time-series model is used without a richer structural model because the evidence set is recent monthly annualized first-print history. Adjustment components are +0.2 for rebound from May's revolving-credit drag, -0.1 for still-tight consumer-credit conditions, and roughly 0.0 for nonrevolving steadiness, giving point 2.2. Interval method uses realized dispersion of those same annualized change-rate values: sigma = 1.71; 1.28*sigma = 2.19, rounded and modestly widened to a 2.4-point half-width because the May-to-June first print can swing with revolving credit, implying about -0.2 to 4.6."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-consumer-credit-annual-rate-june-2026\nrunLabel: Headline\nresolutionDate: 2026-08-07\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-revolving-consumer-credit-annual-rate-june-2026.2026-07-26T01-17-58Z.c48df79bf1507377","runId":"run.us-revolving-consumer-credit-annual-rate-june-2026.2026-07-26T01-17-58Z.c48df79bf1507377","predictionId":"us-revolving-consumer-credit-annual-rate-june-2026","specId":"spec.us-revolving-consumer-credit-annual-rate-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate / reference class: I use the 2024-Jan through 2026-May REVOLSLAR sample as a current-rate-regime reference class rather than a longer pre-2024 sample. Monthly REVOLSLAR values are centered around low single-digit growth but have sharp reversals; the sample mean is about 3.96, while the latest five months average 3.60, so a point forecast near 3.8 keeps the base rate while not chasing May's -4.71 print.","Prior/update/interval: persistence/base-rate prior is the 2024-Jan through 2026-May REVOLSLAR sample, n = 29, mean = 3.96; current-release adjustment is -0.2 for May weakness after Mar 9.66 and Apr 10.36 strength, plus about 0.0 for policy/rate mechanism because credit-card rates remain high but stable. For this change-rate series I size uncertainty from the sample standard deviation of the annual-rate monthly values themselves, not forecast-error volatility: sigma = 4.96, so the 80% half-width is 1.28*sigma = 1.28*4.96 = 6.35. Point = 3.8; interval = 3.8 +/- 6.35 = [-2.55, 10.15], rounded to [-2.6, 10.2]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["US revolving consumer credit annual-rate forecast for June 2026","Framing and exact resolver: the target is Federal Reserve G.19 Consumer Credit, series REVOLSLAR, the seasonally adjusted annual-rate percent change of total revolving consumer credit for June 2026, first print. All anchors use the same seasonally adjusted annual-rate percent-change variant; the canonical ledger binds resolution to the ALFRED/FRED first-vintage REVOLSLAR feed while the underlying statistical release is Federal Reserve G.19."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: the target is Federal Reserve G.19 Consumer Credit, series REVOLSLAR, the seasonally adjusted annual-rate percent change of total revolving consumer credit for June 2026, first print. All anchors use the same seasonally adjusted annual-rate percent-change variant; the canonical ledger binds resolution to the ALFRED/FRED first-vintage REVOLSLAR feed while the underlying statistical release is Federal Reserve G.19.","Tool call: Checked the Federal Reserve August 2026 statistical release calendar for G.19 Consumer Credit."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 12.8, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence/base-rate prior is the 2024-Jan through 2026-May REVOLSLAR sample, n = 29, mean = 3.96; current-release adjustment is -0.2 for May weakness after Mar 9.66 and Apr 10.36 strength, plus about 0.0 for policy/rate mechanism because credit-card rates remain high but stable. For this change-rate series I size uncertainty from the sample standard deviation of the annual-rate monthly values themselves, not forecast-error volatility: sigma = 4.96, so the 80% half-width is 1.28*sigma = 1.28*4.96 = 6.35. Point = 3.8; interval = 3.8 +/- 6.35 = [-2.55, 10.15], rounded to [-2.6, 10.2].","Counter-considerations: upside risk is another rebound like March-April if card balances recover after May's paydown, which would land above the interval if annualized revolving growth exceeds 10.2. Downside risk is a second consecutive contraction from deleveraging or tighter card credit, which would land below the interval if growth is below -2.6. Outside the interval would require a monthly swing larger than typical current-regime dispersion, not just normal noise."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence/base-rate prior is the 2024-Jan through 2026-May REVOLSLAR sample, n = 29, mean = 3.96; current-release adjustment is -0.2 for May weakness after Mar 9.66 and Apr 10.36 strength, plus about 0.0 for policy/rate mechanism because credit-card rates remain high but stable. For this change-rate series I size uncertainty from the sample standard deviation of the annual-rate monthly values themselves, not forecast-error volatility: sigma = 4.96, so the 80% half-width is 1.28*sigma = 1.28*4.96 = 6.35. Point = 3.8; interval = 3.8 +/- 6.35 = [-2.55, 10.15], rounded to [-2.6, 10.2]."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate / reference class: I use the 2024-Jan through 2026-May REVOLSLAR sample as a current-rate-regime reference class rather than a longer pre-2024 sample. Monthly REVOLSLAR values are centered around low single-digit growth but have sharp reversals; the sample mean is about 3.96, while the latest five months average 3.60, so a point forecast near 3.8 keeps the base rate while not chasing May's -4.71 print.","Prior/update/interval: persistence/base-rate prior is the 2024-Jan through 2026-May REVOLSLAR sample, n = 29, mean = 3.96; current-release adjustment is -0.2 for May weakness after Mar 9.66 and Apr 10.36 strength, plus about 0.0 for policy/rate mechanism because credit-card rates remain high but stable. For this change-rate series I size uncertainty from the sample standard deviation of the annual-rate monthly values themselves, not forecast-error volatility: sigma = 4.96, so the 80% half-width is 1.28*sigma = 1.28*4.96 = 6.35. Point = 3.8; interval = 3.8 +/- 6.35 = [-2.55, 10.15], rounded to [-2.6, 10.2]."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["US revolving consumer credit annual-rate forecast for June 2026","Base rate / reference class: I use the 2024-Jan through 2026-May REVOLSLAR sample as a current-rate-regime reference class rather than a longer pre-2024 sample. Monthly REVOLSLAR values are centered around low single-digit growth but have sharp reversals; the sample mean is about 3.96, while the latest five months average 3.60, so a point forecast near 3.8 keeps the base rate while not chasing May's -4.71 print."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-revolving-consumer-credit-annual-rate-june-2026\nrunLabel: Headline\nresolutionDate: 2026-08-07\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-nonrevolving-consumer-credit-annual-rate-june-2026.2026-07-26T01-19-52Z.4ac5655ddaeb8ae8","runId":"run.us-nonrevolving-consumer-credit-annual-rate-june-2026.2026-07-26T01-19-52Z.4ac5655ddaeb8ae8","predictionId":"us-nonrevolving-consumer-credit-annual-rate-june-2026","specId":"spec.us-nonrevolving-consumer-credit-annual-rate-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate / reference class: the recent 2026 monthly values themselves are 0.84, 1.94, 3.84, 2.93, and 1.61, with mean (0.84+1.94+3.84+2.93+1.61)/5 = 2.23 percent annualized. The 2025 annual nonrevolving rate in the official release is a weak context anchor at 1.8 percent, so the outside-view anchor is roughly 2 percent rather than the higher March-April pace.","Prior/update/interval: model prior is simple recent-mean persistence using the Jan-May 2026 NONREVSLAR mean of 2.23; a formal AR model was ruled out for this fast run because only the fetched same-vintage recent observations were used. Adjust down 0.25 for May's slowdown from Apr 2.93 to May 1.61 and down 0.10 for still-tight auto and personal-loan credit conditions, giving a 1.9 point estimate after rounding. Interval method uses the fetched 2026 monthly values themselves because this target is already a change-rate series: sample sigma = 1.17 percentage points, so 1.28*sigma = 1.50; because five observations are a thin volatility sample for a noisy annualized monthly series, widen the half-width to 2.2, which is 1.47x the mechanical half-width, giving 1.9 - 2.2 = -0.3 and 1.9 + 2.2 = 4.1."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Forecast for June 2026 US nonrevolving consumer credit annual rate","Target is the Federal Reserve G.19 seasonally adjusted nonrevolving consumer credit percent change at annual rate, series NONREVSLAR, for June 2026 first print. The catalog slug, unit, dataPointId, and 2026-08-07 resolution date match the ledger contract; the resolver URL is the ledger-bound ALFRED original-vintage series, while the economic release is the Federal Reserve G.19 table."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Target is the Federal Reserve G.19 seasonally adjusted nonrevolving consumer credit percent change at annual rate, series NONREVSLAR, for June 2026 first print. The catalog slug, unit, dataPointId, and 2026-08-07 resolution date match the ledger contract; the resolver URL is the ledger-bound ALFRED original-vintage series, while the economic release is the Federal Reserve G.19 table.","Tool call: Opened Federal Reserve August 2026 statistical release calendar for G.19 Consumer Credit."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.4, distribution present, forecast step count 1.","evidence":["Prior/update/interval: model prior is simple recent-mean persistence using the Jan-May 2026 NONREVSLAR mean of 2.23; a formal AR model was ruled out for this fast run because only the fetched same-vintage recent observations were used. Adjust down 0.25 for May's slowdown from Apr 2.93 to May 1.61 and down 0.10 for still-tight auto and personal-loan credit conditions, giving a 1.9 point estimate after rounding. Interval method uses the fetched 2026 monthly values themselves because this target is already a change-rate series: sample sigma = 1.17 percentage points, so 1.28*sigma = 1.50; because five observations are a thin volatility sample for a noisy annualized monthly series, widen the half-width to 2.2, which is 1.47x the mechanical half-width, giving 1.9 - 2.2 = -0.3 and 1.9 + 2.2 = 4.1.","Counter-considerations: upside risk would come from a rebound in auto-loan originations or federal/student-loan components strong enough to put June above 4.1 percent annualized. Downside risk would be a paydown-heavy or weak auto-credit month that lands below -0.3 percent. A technical break or unusually large holder reclassification would be outside the interval mechanism, though the G.19 percent-change method is designed to exclude breaks."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: model prior is simple recent-mean persistence using the Jan-May 2026 NONREVSLAR mean of 2.23; a formal AR model was ruled out for this fast run because only the fetched same-vintage recent observations were used. Adjust down 0.25 for May's slowdown from Apr 2.93 to May 1.61 and down 0.10 for still-tight auto and personal-loan credit conditions, giving a 1.9 point estimate after rounding. Interval method uses the fetched 2026 monthly values themselves because this target is already a change-rate series: sample sigma = 1.17 percentage points, so 1.28*sigma = 1.50; because five observations are a thin volatility sample for a noisy annualized monthly series, widen the half-width to 2.2, which is 1.47x the mechanical half-width, giving 1.9 - 2.2 = -0.3 and 1.9 + 2.2 = 4.1."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-considerations: upside risk would come from a rebound in auto-loan originations or federal/student-loan components strong enough to put June above 4.1 percent annualized. Downside risk would be a paydown-heavy or weak auto-credit month that lands below -0.3 percent. A technical break or unusually large holder reclassification would be outside the interval mechanism, though the G.19 percent-change method is designed to exclude breaks."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for June 2026 US nonrevolving consumer credit annual rate","Target is the Federal Reserve G.19 seasonally adjusted nonrevolving consumer credit percent change at annual rate, series NONREVSLAR, for June 2026 first print. The catalog slug, unit, dataPointId, and 2026-08-07 resolution date match the ledger contract; the resolver URL is the ledger-bound ALFRED original-vintage series, while the economic release is the Federal Reserve G.19 table."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-nonrevolving-consumer-credit-annual-rate-june-2026\nrunLabel: Headline\nresolutionDate: 2026-08-07\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-cpi-shelter-mom-july-2026.2026-07-26T01-24-03Z.668b8cc60b675eee","runId":"run.us-cpi-shelter-mom-july-2026.2026-07-26T01-24-03Z.668b8cc60b675eee","predictionId":"us-cpi-shelter-mom-july-2026","specId":"spec.us-cpi-shelter-mom-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 7 historical point(s) and explicit outside-view language.","evidence":["Reference class/base rate: the recent same-variant BLS shelter MoM reference class is the seven printed monthly changes from Dec 2025 through Jun 2026. Its mean is 0.30 percent, but the last print was 0.1 and the exact CUSR0000SAH1 index calculation gives Jun about 0.118 and May about 0.318, so the short-term trend is below the mean.","Prior/update/interval: persistence/reference-class prior is the Dec 2025-Jun 2026 BLS shelter MoM mean of 0.30 percent; no richer time-series model is used because this one-month target is better served by transparent persistence plus component judgment. Updates are -0.08 for June's soft exact 0.118 reading and lower rent/OER momentum, +0.03 for partial lodging-drag reversal, and -0.01 for core services softness, giving 0.30 - 0.08 + 0.03 - 0.01 = 0.24. Interval method uses realized dispersion of the seven BLS printed shelter MoM values themselves, a small but same-variant sample: sigma = 0.163; 1.28*sigma = 0.209, so the 80 percent interval is 0.24 +/- 0.21 = [0.03, 0.45] after rounding."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this targets the first-print July 2026 seasonally adjusted CPI-U shelter index for U.S. city average, series CUSR0000SAH1. The ledger uses ALFRED/FRED as the canonical first-print binding for the registered target, while the underlying official economic release is BLS; FRED/ALFRED is used as the history and first-print mirror.","Tool call: Checked the BLS CPI release schedule for the July 2026 CPI reference month."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this targets the first-print July 2026 seasonally adjusted CPI-U shelter index for U.S. city average, series CUSR0000SAH1. The ledger uses ALFRED/FRED as the canonical first-print binding for the registered target, while the underlying official economic release is BLS; FRED/ALFRED is used as the history and first-print mirror.","Tool call: Checked the BLS CPI release schedule for the July 2026 CPI reference month."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.42, distribution present, forecast step count 1.","evidence":["Tool call: Fetched BLS CPI Table 1 component details for shelter, rent, and owners' equivalent rent.","Prior/update/interval: persistence/reference-class prior is the Dec 2025-Jun 2026 BLS shelter MoM mean of 0.30 percent; no richer time-series model is used because this one-month target is better served by transparent persistence plus component judgment. Updates are -0.08 for June's soft exact 0.118 reading and lower rent/OER momentum, +0.03 for partial lodging-drag reversal, and -0.01 for core services softness, giving 0.30 - 0.08 + 0.03 - 0.01 = 0.24. Interval method uses realized dispersion of the seven BLS printed shelter MoM values themselves, a small but same-variant sample: sigma = 0.163; 1.28*sigma = 0.209, so the 80 percent interval is 0.24 +/- 0.21 = [0.03, 0.45] after rounding."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and mechanism effects: shelter still has positive rent and OER mechanics, with June rent at 0.1 and OER at 0.2, but the aggregate was pulled down by lodging away from home falling 2.3 percent in June. I treat that lodging move as a partial one-off drag, while keeping some disinflationary momentum from the softer rent/OER prints.","Prior/update/interval: persistence/reference-class prior is the Dec 2025-Jun 2026 BLS shelter MoM mean of 0.30 percent; no richer time-series model is used because this one-month target is better served by transparent persistence plus component judgment. Updates are -0.08 for June's soft exact 0.118 reading and lower rent/OER momentum, +0.03 for partial lodging-drag reversal, and -0.01 for core services softness, giving 0.30 - 0.08 + 0.03 - 0.01 = 0.24. Interval method uses realized dispersion of the seven BLS printed shelter MoM values themselves, a small but same-variant sample: sigma = 0.163; 1.28*sigma = 0.209, so the 80 percent interval is 0.24 +/- 0.21 = [0.03, 0.45] after rounding."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Reference class/base rate: the recent same-variant BLS shelter MoM reference class is the seven printed monthly changes from Dec 2025 through Jun 2026. Its mean is 0.30 percent, but the last print was 0.1 and the exact CUSR0000SAH1 index calculation gives Jun about 0.118 and May about 0.318, so the short-term trend is below the mean.","Level, momentum, one-off, and mechanism effects: shelter still has positive rent and OER mechanics, with June rent at 0.1 and OER at 0.2, but the aggregate was pulled down by lodging away from home falling 2.3 percent in June. I treat that lodging move as a partial one-off drag, while keeping some disinflationary momentum from the softer rent/OER prints."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["US CPI-U shelter month-over-month forecast for July 2026","Prior/update/interval: persistence/reference-class prior is the Dec 2025-Jun 2026 BLS shelter MoM mean of 0.30 percent; no richer time-series model is used because this one-month target is better served by transparent persistence plus component judgment. Updates are -0.08 for June's soft exact 0.118 reading and lower rent/OER momentum, +0.03 for partial lodging-drag reversal, and -0.01 for core services softness, giving 0.30 - 0.08 + 0.03 - 0.01 = 0.24. Interval method uses realized dispersion of the seven BLS printed shelter MoM values themselves, a small but same-variant sample: sigma = 0.163; 1.28*sigma = 0.209, so the 80 percent interval is 0.24 +/- 0.21 = [0.03, 0.45] after rounding."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-cpi-shelter-mom-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-12\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bls-ppi-final-demand-monthly-change-july-2026.2026-07-25T23-36-46Z.2b46e0d64c47658f","runId":"run.bls-ppi-final-demand-monthly-change-july-2026.2026-07-25T23-36-46Z.2b46e0d64c47658f","predictionId":"bls-ppi-final-demand-monthly-change-july-2026","specId":"spec.bls-ppi-final-demand-monthly-change-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 7 historical point(s) and explicit outside-view language.","evidence":["Reference class/base rate: using the same BLS final-demand SA monthly percent-change series from June 2025 through June 2026 gives values 0.2, 0.8, -0.2, 0.6, 0.1, 0.4, 0.4, 0.6, 0.5, 0.8, 1.1, 0.6, -0.3, a base rate mean of about 0.43 percentage point per month. The recent reference class is hot but very energy-sensitive.","Prior/update/interval: persistence/reference-class prior is the Jun. 2025-Jun. 2026 BLS Table A history with mean 0.43; no separate AR or other time-series forecasting model was used beyond this 13-month persistence/reference-class prior. Adjustment components: -0.15 for June's large energy drop not fully reversing because partial July gasoline is below the June monthly average despite a late-month rise, +0.05 for still-positive services and core final-demand pressure, and +0.02 for high 5.5 percent 12-month headline PPI momentum, giving 0.43 - 0.15 + 0.05 + 0.02 = 0.35. EIA retail gasoline is a directional energy proxy, not the PPI energy component itself. For the 80% interval, the sample standard deviation of the 13 monthly changes is sigma = 0.40 percentage point, so half-width is roughly 1.28*sigma = 1.28*0.40 = 0.51; 0.35 +/- 0.51 gives -0.16 to 0.86."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this forecast targets the BLS Producer Price Index for final demand, seasonally adjusted, one-month percent change for July 2026, group code FD item code 4. The variant is the headline final-demand SA monthly percent change in Table 1, first print only, not the unadjusted 12-month change and not later revised data.","Tool call: Checked the BLS Producer Price Index release schedule for the July 2026 reference month."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this forecast targets the BLS Producer Price Index for final demand, seasonally adjusted, one-month percent change for July 2026, group code FD item code 4. The variant is the headline final-demand SA monthly percent change in Table 1, first print only, not the unadjusted 12-month change and not later revised data.","Tool call: Checked the BLS Producer Price Index release schedule for the July 2026 reference month."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.02, distribution present, forecast step count 1.","evidence":["Tool call: Fetched BLS Table 1 component details for the latest release to separate energy, goods, and services mechanisms.","Prior/update/interval: persistence/reference-class prior is the Jun. 2025-Jun. 2026 BLS Table A history with mean 0.43; no separate AR or other time-series forecasting model was used beyond this 13-month persistence/reference-class prior. Adjustment components: -0.15 for June's large energy drop not fully reversing because partial July gasoline is below the June monthly average despite a late-month rise, +0.05 for still-positive services and core final-demand pressure, and +0.02 for high 5.5 percent 12-month headline PPI momentum, giving 0.43 - 0.15 + 0.05 + 0.02 = 0.35. EIA retail gasoline is a directional energy proxy, not the PPI energy component itself. For the 80% interval, the sample standard deviation of the 13 monthly changes is sigma = 0.40 percentage point, so half-width is roughly 1.28*sigma = 1.28*0.40 = 0.51; 0.35 +/- 0.51 gives -0.16 to 0.86."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence/reference-class prior is the Jun. 2025-Jun. 2026 BLS Table A history with mean 0.43; no separate AR or other time-series forecasting model was used beyond this 13-month persistence/reference-class prior. Adjustment components: -0.15 for June's large energy drop not fully reversing because partial July gasoline is below the June monthly average despite a late-month rise, +0.05 for still-positive services and core final-demand pressure, and +0.02 for high 5.5 percent 12-month headline PPI momentum, giving 0.43 - 0.15 + 0.05 + 0.02 = 0.35. EIA retail gasoline is a directional energy proxy, not the PPI energy component itself. For the 80% interval, the sample standard deviation of the 13 monthly changes is sigma = 0.40 percentage point, so half-width is roughly 1.28*sigma = 1.28*0.40 = 0.51; 0.35 +/- 0.51 gives -0.16 to 0.86.","Counter-considerations: upside risk is a larger July pass-through from renewed gasoline, diesel, crude, trade-margin, or tariff-related cost pressure, which would land above the interval if headline final-demand energy and services both spike. Downside risk is a second month of falling fuels or a reversal in trade margins, which would land below the interval if final-demand goods repeat a June-like decline. An outside the interval outcome would likely require another energy shock or a broad services-margin reversal rather than ordinary monthly noise."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Reference class/base rate: using the same BLS final-demand SA monthly percent-change series from June 2025 through June 2026 gives values 0.2, 0.8, -0.2, 0.6, 0.1, 0.4, 0.4, 0.6, 0.5, 0.8, 1.1, 0.6, -0.3, a base rate mean of about 0.43 percentage point per month. The recent reference class is hot but very energy-sensitive.","Counter-considerations: upside risk is a larger July pass-through from renewed gasoline, diesel, crude, trade-margin, or tariff-related cost pressure, which would land above the interval if headline final-demand energy and services both spike. Downside risk is a second month of falling fuels or a reversal in trade margins, which would land below the interval if final-demand goods repeat a June-like decline. An outside the interval outcome would likely require another energy shock or a broad services-margin reversal rather than ordinary monthly noise."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Framing and exact resolver: this forecast targets the BLS Producer Price Index for final demand, seasonally adjusted, one-month percent change for July 2026, group code FD item code 4. The variant is the headline final-demand SA monthly percent change in Table 1, first print only, not the unadjusted 12-month change and not later revised data.","Reference class/base rate: using the same BLS final-demand SA monthly percent-change series from June 2025 through June 2026 gives values 0.2, 0.8, -0.2, 0.6, 0.1, 0.4, 0.4, 0.6, 0.5, 0.8, 1.1, 0.6, -0.3, a base rate mean of about 0.43 percentage point per month. The recent reference class is hot but very energy-sensitive."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bls-ppi-final-demand-monthly-change-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-13\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-cpi-annual-rate-july-2026.2026-07-25T23-35-04Z.93fc82c70a9670a2","runId":"run.canada-cpi-annual-rate-july-2026.2026-07-25T23-35-04Z.93fc82c70a9670a2","predictionId":"canada-cpi-annual-rate-july-2026","specId":"spec.canada-cpi-annual-rate-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.51,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base rate / reference class: the latest 12-month rates from July 2025 through June 2026 were 1.7, 1.9, 2.4, 2.2, 2.2, 2.4, 2.3, 1.8, 2.4, 2.8, 3.2, and 2.8 percent. A one-month persistence prior starts at 2.8 percent, while the Bank of Canada Q3 projection pulls the quarter-average reference point down toward 2.5 percent.","July index translation: keeping the June 2026 index unchanged at 169.0 against the July 2025 base of 164.9 would imply 100*(169.0/164.9-1)=2.5%. A moderate July NSA increase to about 169.4 implies 100*(169.4/164.9-1)=2.7%, so the point forecast is 2.7%."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["Resolver framing: this is the Statistics Canada all-items CPI for Canada, not seasonally adjusted, Table 18-10-0004-01, vector v41690973. I am forecasting the first official July 2026 print, converted to the year-over-year percent change and rounded to one decimal, with resolution through the canonical StatCan WDS endpoint for the vector and table context as support.","Counter-consideration: upside risk is a renewed gasoline or travel-services jump that pushes July CPI above about 170.2, which would land above the interval; downside risk is another gasoline decline or broad goods softness that leaves July CPI near 168.5, which would land outside the interval below 2.2%."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Resolver framing: this is the Statistics Canada all-items CPI for Canada, not seasonally adjusted, Table 18-10-0004-01, vector v41690973. I am forecasting the first official July 2026 print, converted to the year-over-year percent change and rounded to one decimal, with resolution through the canonical StatCan WDS endpoint for the vector and table context as support.","Tool call: Opened Statistics Canada CPI portal and June 2026 Daily release to verify release timing and current headline CPI context."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior model = latest year-over-year rate of 2.8%; historical sample = July 2025-June 2026 12-month rates listed above; adjustment components = -0.2 percentage point for Bank of Canada Q3 easing signal and ex-gasoline 2.2% anchor, +0.1 percentage point for partial gasoline/travel volatility after June's 0.4% monthly CPI drop; point = 2.7%. Successive changes in the July 2025-June 2026 year-over-year rates have sigma = 0.37 percentage point, so the 80% half-width is roughly 1.28*sigma = 1.28*0.37 = 0.47 percentage point. Rounded one-decimal interval: 2.7 +/- 0.47 gives 2.2% to 3.2%.","Counter-consideration: upside risk is a renewed gasoline or travel-services jump that pushes July CPI above about 170.2, which would land above the interval; downside risk is another gasoline decline or broad goods softness that leaves July CPI near 168.5, which would land outside the interval below 2.2%."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-consideration: upside risk is a renewed gasoline or travel-services jump that pushes July CPI above about 170.2, which would land above the interval; downside risk is another gasoline decline or broad goods softness that leaves July CPI near 168.5, which would land outside the interval below 2.2%."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Canada July 2026 CPI annual-rate forecast","Resolver framing: this is the Statistics Canada all-items CPI for Canada, not seasonally adjusted, Table 18-10-0004-01, vector v41690973. I am forecasting the first official July 2026 print, converted to the year-over-year percent change and rounded to one decimal, with resolution through the canonical StatCan WDS endpoint for the vector and table context as support."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-cpi-annual-rate-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-17\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.abs-labour-employment-change-australia-july-2026.2026-07-25T23-38-24Z.5d8aee31f5561cce","runId":"run.abs-labour-employment-change-australia-july-2026.2026-07-25T23-38-24Z.5d8aee31f5561cce","predictionId":"abs-labour-employment-change-australia-july-2026","specId":"spec.abs-labour-employment-change-australia-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Reference class/base rate: I used the last 24 official seasonally adjusted monthly employment changes from Jul-2024 through Jun-2026 as the base rate, because the target is a monthly change/flow series and the ABS itself cautions that short-term changes are volatile. That sample has a mean of 20.9 thousand and contains large positive and negative prints, including -74.8 thousand in Feb-2025, 104.0 thousand in Apr-2025, -38.6 thousand in Apr-2026, 44.0 thousand in May-2026, and 76.3 thousand in Jun-2026.","Prior/update/interval: persistence prior is the last-24-month official SA employment-change reference class mean of 20.9 thousand; historical sample is Jul-2024 through Jun-2026 values from ABS employed-person levels; adjustment components are +8 thousand for still-positive trend employment growth near 32.3 thousand in Jun-2026, -7 thousand for likely payback after the June waiting-to-start-job and rotation/sample effects, and +2 thousand for firm participation/labour-demand context, giving point 20.9+8-7+2 = 23.9, rounded to 24.0 thousand. Interval method uses the values themselves for this change/flow series: sigma = 39.7 thousand over the last 24 changes, so 1.28*sigma = 50.8 thousand; centered on 24.0 gives -26.8 to 74.8, rounded to an 80 percent interval of -27.0 to 75.0 thousand."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this is the ABS Labour Force, Australia first print for July 2026, seasonally adjusted employed people, Australia, month-over-month change in thousands. The ledger source series is LF/M3.3.1599.20.AUS.M, so anchors and the final resolver all use the same seasonally adjusted employed-persons variant rather than trend, original, hours, unemployment, or participation series.","Tool result: Fetched official schedule: Labour Force, Australia July 2026 release date is 20/08/2026; April 2026 was 21/05/2026, May 2026 was 25/06/2026, June 2026 was 23/07/2026, and August 2026 is scheduled for 24/09/2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Australia July 2026 employment change first-print forecast","Framing and exact resolver: this is the ABS Labour Force, Australia first print for July 2026, seasonally adjusted employed people, Australia, month-over-month change in thousands. The ledger source series is LF/M3.3.1599.20.AUS.M, so anchors and the final resolver all use the same seasonally adjusted employed-persons variant rather than trend, original, hours, unemployment, or participation series."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 102, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is the last-24-month official SA employment-change reference class mean of 20.9 thousand; historical sample is Jul-2024 through Jun-2026 values from ABS employed-person levels; adjustment components are +8 thousand for still-positive trend employment growth near 32.3 thousand in Jun-2026, -7 thousand for likely payback after the June waiting-to-start-job and rotation/sample effects, and +2 thousand for firm participation/labour-demand context, giving point 20.9+8-7+2 = 23.9, rounded to 24.0 thousand. Interval method uses the values themselves for this change/flow series: sigma = 39.7 thousand over the last 24 changes, so 1.28*sigma = 50.8 thousand; centered on 24.0 gives -26.8 to 74.8, rounded to an 80 percent interval of -27.0 to 75.0 thousand.","Counter-considerations: upside risk is that elevated participation and the June waiting-to-start-job comment were not just timing noise, in which case another broad hiring month would land above the interval. Downside risk is that the June surge borrowed from July or that survey-transition volatility reverses sharply, which would land below the interval. A material outside the interval print would most likely require either another rotation/sample shock or a sudden labour-demand break not visible in the June official data."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Reference class/base rate: I used the last 24 official seasonally adjusted monthly employment changes from Jul-2024 through Jun-2026 as the base rate, because the target is a monthly change/flow series and the ABS itself cautions that short-term changes are volatile. That sample has a mean of 20.9 thousand and contains large positive and negative prints, including -74.8 thousand in Feb-2025, 104.0 thousand in Apr-2025, -38.6 thousand in Apr-2026, 44.0 thousand in May-2026, and 76.3 thousand in Jun-2026."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-considerations: upside risk is that elevated participation and the June waiting-to-start-job comment were not just timing noise, in which case another broad hiring month would land above the interval. Downside risk is that the June surge borrowed from July or that survey-transition volatility reverses sharply, which would land below the interval. A material outside the interval print would most likely require either another rotation/sample shock or a sudden labour-demand break not visible in the June official data."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Australia July 2026 employment change first-print forecast","Tool result: Fetched current context: unemployment rate was 4.4 percent in June 2026, participation rate rose 0.3 percentage points to 67.0 percent, monthly hours worked rose 5 million or 0.2 percent, full-time employment rose 29.3 thousand, and part-time employment rose 47.0 thousand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: abs-labour-employment-change-australia-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-20\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.initial-claims-week-2026-08-01.2026-07-25T15-52-00Z.1eca59d5f71e84a6","runId":"run.initial-claims-week-2026-08-01.2026-07-25T15-52-00Z.1eca59d5f71e84a6","predictionId":"initial-claims-week-2026-08-01","specId":"spec.initial-claims-week-2026-08-01","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate / reference class: recent DOL first-print SA initial claims from April 4 through July 18 were 219, 207, 214, 189, 200, 211, 209, 215, 225, 229, 226, 215, 215, 215, 208, and 187 thousand. The base rate is a low-200s claims environment: the mean of that sample is 211.5 thousand, while the latest DOL four-week average is 207.5 thousand.","Prior/update/interval: persistence prior = 207.5 thousand from the latest DOL four-week average; historical sample = 16 recent DOL first-print SA initial-claims values from April 4 to July 18, 2026; adjustment components = -3.0 thousand for two-week downward momentum from July first prints, +1.5 thousand for reversion after the unusually low 187k July 18 print, and 0.0 thousand for policy mechanism, giving point = 207.5 - 3.0 + 1.5 = 206.0 thousand. Interval method uses recent level dispersion of the flow values themselves rather than a backtested out-of-sample forecast-error estimate: sample sigma = 11.8 thousand, so 1.28*sigma = 15.1 thousand; I widen to 17.0 thousand for two-week-ahead release and low seasonal factor noise, giving 206 - 17 = 189 and 206 + 17 = 223 thousand."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this targets DOL series ICSA, the advance seasonally adjusted initial claims count, for the week ending Saturday, August 1, 2026. The DOL release schedule says the UI Weekly Claims News Release is published weekly on Thursday at 8:30 a.m. EST and lists only one 2026 non-Thursday exception, November 25; the FRED release calendar also lists the UI Weekly Claims Report on Thursday, August 6, 2026. I use DOL as the final resolver; ALFRED/FRED is only the ledger's archived first-vintage retrieval mechanism and a history/schedule mirror.","Tool call: Inspect DOL OUI claims archive and latest-release schedule page for the official release rule and latest official SA claims numbers."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this targets DOL series ICSA, the advance seasonally adjusted initial claims count, for the week ending Saturday, August 1, 2026. The DOL release schedule says the UI Weekly Claims News Release is published weekly on Thursday at 8:30 a.m. EST and lists only one 2026 non-Thursday exception, November 25; the FRED release calendar also lists the UI Weekly Claims Report on Thursday, August 6, 2026. I use DOL as the final resolver; ALFRED/FRED is only the ledger's archived first-vintage retrieval mechanism and a history/schedule mirror.","Tool call: Inspect DOL OUI claims archive and latest-release schedule page for the official release rule and latest official SA claims numbers."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 34, distribution present, forecast step count 1.","evidence":["Tool call: Inspect published current seasonal-factor table for the target week and adjacent weeks to assess seasonal-adjustment risk, not as a resolver.","Level, momentum, one-off, and mechanism: the level anchor is the 207.5k four-week average, momentum is mildly down because the latest 187k print was a 22k drop, the one-off risk is that New York and school/auto-seasonal timing made the July 18 print unusually low, and the policy mechanism is neutral because weekly UI filings do not mechanically jump from a scheduled policy change in this target window."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and mechanism: the level anchor is the 207.5k four-week average, momentum is mildly down because the latest 187k print was a 22k drop, the one-off risk is that New York and school/auto-seasonal timing made the July 18 print unusually low, and the policy mechanism is neutral because weekly UI filings do not mechanically jump from a scheduled policy change in this target window.","Prior/update/interval: persistence prior = 207.5 thousand from the latest DOL four-week average; historical sample = 16 recent DOL first-print SA initial-claims values from April 4 to July 18, 2026; adjustment components = -3.0 thousand for two-week downward momentum from July first prints, +1.5 thousand for reversion after the unusually low 187k July 18 print, and 0.0 thousand for policy mechanism, giving point = 207.5 - 3.0 + 1.5 = 206.0 thousand. Interval method uses recent level dispersion of the flow values themselves rather than a backtested out-of-sample forecast-error estimate: sample sigma = 11.8 thousand, so 1.28*sigma = 15.1 thousand; I widen to 17.0 thousand for two-week-ahead release and low seasonal factor noise, giving 206 - 17 = 189 and 206 + 17 = 223 thousand."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool call: Inspect published current seasonal-factor table for the target week and adjacent weeks to assess seasonal-adjustment risk, not as a resolver.","Level, momentum, one-off, and mechanism: the level anchor is the 207.5k four-week average, momentum is mildly down because the latest 187k print was a 22k drop, the one-off risk is that New York and school/auto-seasonal timing made the July 18 print unusually low, and the policy mechanism is neutral because weekly UI filings do not mechanically jump from a scheduled policy change in this target window."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["US DOL initial claims forecast for week ending 2026-08-01","Prior/update/interval: persistence prior = 207.5 thousand from the latest DOL four-week average; historical sample = 16 recent DOL first-print SA initial-claims values from April 4 to July 18, 2026; adjustment components = -3.0 thousand for two-week downward momentum from July first prints, +1.5 thousand for reversion after the unusually low 187k July 18 print, and 0.0 thousand for policy mechanism, giving point = 207.5 - 3.0 + 1.5 = 206.0 thousand. Interval method uses recent level dispersion of the flow values themselves rather than a backtested out-of-sample forecast-error estimate: sample sigma = 11.8 thousand, so 1.28*sigma = 15.1 thousand; I widen to 17.0 thousand for two-week-ahead release and low seasonal factor noise, giving 206 - 17 = 189 and 206 + 17 = 223 thousand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: initial-claims-week-2026-08-01\nrunLabel: Headline\nresolutionDate: 2026-08-06\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.continued-claims-week-2026-08-01.2026-07-25T15-54-22Z.d024023ec25b93d8","runId":"run.continued-claims-week-2026-08-01.2026-07-25T15-54-22Z.d024023ec25b93d8","predictionId":"continued-claims-week-2026-08-01","specId":"spec.continued-claims-week-2026-08-01","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool result: The table shows Insured Unemployment (SA) of 1,796,000 for July 11, 1,798,000 for July 4, 1,821,000 for June 27, and a prior-year comparable value of 1,941,000.","Base rate/reference class: the outside-view prior is persistence of the latest official SA insured-unemployment level, with uncertainty calibrated to 2026 weekly changes in the same DOL SA continued-claims series rather than to initial claims or unadjusted state totals."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Ledger resolver note: the official statistical source is DOL ETA, but the canonical ledger sourceBinding for resolution is the ALFRED CCSA advance-vintage CSV at alfred.stlouisfed.org with a 1e-06 transform to millions. I keep the forecast tied to that ledger target and use DOL only to verify the first-print release date and source series substance.","Tool result: The official schedule says the UI Weekly Claims News Release is published each week on Thursday at 8:30 AM EST, with the listed 2026 non-Thursday exception being Wednesday, November 25, 2026 at 8:30 AM EST; August 13, 2026 is the Thursday release covering the August 1 insured-unemployment week and falls inside the ledger expected window of August 11 through August 15, 2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this targets the DOL ETA Unemployment Insurance Weekly Claims first print for seasonally adjusted insured unemployment, also called continued claims, for the week ending August 1, 2026. The DOL release table labels this variant as Insured Unemployment (SA), so all anchors below use that same seasonally adjusted variant.","Ledger resolver note: the official statistical source is DOL ETA, but the canonical ledger sourceBinding for resolution is the ALFRED CCSA advance-vintage CSV at alfred.stlouisfed.org with a 1e-06 transform to millions. I keep the forecast tied to that ledger target and use DOL only to verify the first-print release date and source series substance."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.1, distribution present, forecast step count 1.","evidence":["Base rate/reference class: the outside-view prior is persistence of the latest official SA insured-unemployment level, with uncertainty calibrated to 2026 weekly changes in the same DOL SA continued-claims series rather than to initial claims or unadjusted state totals.","Prior/update/interval: persistence prior = 1.796 million from the latest DOL first print; historical sample = 27 successive weekly SA insured-unemployment changes in 2026 from January 3 through July 11, giving sigma = 0.023 million. Update components: level is 0.009 million below the latest four-week average of 1.805 million, two-week momentum is -0.025 million from June 27 to July 11, and the July 18 initial-claims fall to 187,000 versus 209,000 in the same July 23 DOL release points to lower near-term inflows; combined adjustment = -0.016 million, so point = 1.796 - 0.016 = 1.780 million. One-week 80% half-width = 1.28*sigma = 1.28*0.023 = 0.029 million; because the target is three weekly steps after the latest continued-claims observation, scale by sqrt(3), giving half-width = 0.051 million and bounds 1.729 to 1.831 million."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior = 1.796 million from the latest DOL first print; historical sample = 27 successive weekly SA insured-unemployment changes in 2026 from January 3 through July 11, giving sigma = 0.023 million. Update components: level is 0.009 million below the latest four-week average of 1.805 million, two-week momentum is -0.025 million from June 27 to July 11, and the July 18 initial-claims fall to 187,000 versus 209,000 in the same July 23 DOL release points to lower near-term inflows; combined adjustment = -0.016 million, so point = 1.796 - 0.016 = 1.780 million. One-week 80% half-width = 1.28*sigma = 1.28*0.023 = 0.029 million; because the target is three weekly steps after the latest continued-claims observation, scale by sqrt(3), giving half-width = 0.051 million and bounds 1.729 to 1.831 million."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Ledger resolver note: the official statistical source is DOL ETA, but the canonical ledger sourceBinding for resolution is the ALFRED CCSA advance-vintage CSV at alfred.stlouisfed.org with a 1e-06 transform to millions. I keep the forecast tied to that ledger target and use DOL only to verify the first-print release date and source series substance.","Base rate/reference class: the outside-view prior is persistence of the latest official SA insured-unemployment level, with uncertainty calibrated to 2026 weekly changes in the same DOL SA continued-claims series rather than to initial claims or unadjusted state totals."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for DOL seasonally adjusted continued claims, week ending August 1, 2026","Ledger resolver note: the official statistical source is DOL ETA, but the canonical ledger sourceBinding for resolution is the ALFRED CCSA advance-vintage CSV at alfred.stlouisfed.org with a 1e-06 transform to millions. I keep the forecast tied to that ledger target and use DOL only to verify the first-print release date and source series substance."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: continued-claims-week-2026-08-01\nrunLabel: Headline\nresolutionDate: 2026-08-13\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.fed-g17-industrial-production-total-index-mom-july-2026.2026-07-25T16-00-25Z.37a0a339eb411557","runId":"run.fed-g17-industrial-production-total-index-mom-july-2026.2026-07-25T16-00-25Z.37a0a339eb411557","predictionId":"fed-g17-industrial-production-total-index-mom-july-2026","specId":"spec.fed-g17-industrial-production-total-index-mom-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["The base rate / reference class anchor is official G.17 monthly Total IP percent changes from 2023 through June 2026, with the latest persistence anchor at 0.1 percent because both May and June 2026 printed 0.1 percent. Across that 42-month sample the mean is about 0.07 percent, so I start from a near-flat monthly prior before applying current-release adjustments.","Tool call: Read Federal Reserve G.17 Table 11 for the historical reference class and index levels."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["The target is the Federal Reserve G.17 Total IP monthly percent change, seasonally adjusted, for July 2026 on the first official print. The same seasonally adjusted Total IP variant is used for the anchors and interval; the ledger sourceBinding names INDPRO, while the forecasted value is the G.17 monthly percent-change print derived from that total index target.","The base rate / reference class anchor is official G.17 monthly Total IP percent changes from 2023 through June 2026, with the latest persistence anchor at 0.1 percent because both May and June 2026 printed 0.1 percent. Across that 42-month sample the mean is about 0.07 percent, so I start from a near-flat monthly prior before applying current-release adjustments."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the Federal Reserve G.17 Total IP monthly percent change, seasonally adjusted, for July 2026 on the first official print. The same seasonally adjusted Total IP variant is used for the anchors and interval; the ledger sourceBinding names INDPRO, while the forecasted value is the G.17 monthly percent-change print derived from that total index target.","The base rate / reference class anchor is official G.17 monthly Total IP percent changes from 2023 through June 2026, with the latest persistence anchor at 0.1 percent because both May and June 2026 printed 0.1 percent. Across that 42-month sample the mean is about 0.07 percent, so I start from a near-flat monthly prior before applying current-release adjustments."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.4, distribution present, forecast step count 1.","evidence":["The target is the Federal Reserve G.17 Total IP monthly percent change, seasonally adjusted, for July 2026 on the first official print. The same seasonally adjusted Total IP variant is used for the anchors and interval; the ledger sourceBinding names INDPRO, while the forecasted value is the G.17 monthly percent-change print derived from that total index target.","Prior/update/interval: persistence prior is 0.1 percent from the latest June and May prints, with a 2023-Jun 2026 official Table 11 reference-class base rate near 0.07 percent; adjustment components are +0.05 for Q2 annualized strength, -0.05 for flat June manufacturing and below-average utilization, and 0.00 for unknown July weather/energy noise, leaving a 0.10 point. For the interval, use the 42 monthly change values from 2023-Jun 2026, including the 2023-2024 Table 11 monthly changes plus the enumerated 2025-Jan 2026 values; sigma = 0.55 percentage point from those fetched values, so 1.28*sigma = 0.70 percentage point. Point 0.10 minus/plus 0.70 gives -0.60 to 0.80."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The base rate / reference class anchor is official G.17 monthly Total IP percent changes from 2023 through June 2026, with the latest persistence anchor at 0.1 percent because both May and June 2026 printed 0.1 percent. Across that 42-month sample the mean is about 0.07 percent, so I start from a near-flat monthly prior before applying current-release adjustments."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Upside risk is a hot-weather utilities jump plus another mining gain or auto rebound, which would land above the interval if July Total IP prints above 0.8 percent. Downside risk is a reversal in durable manufacturing or utilities after June strength, which would land below the interval if the first print is below -0.6 percent; outside the interval would require a broad sector move rather than ordinary month-to-month noise."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for July 2026 Total Industrial Production MoM","The target is the Federal Reserve G.17 Total IP monthly percent change, seasonally adjusted, for July 2026 on the first official print. The same seasonally adjusted Total IP variant is used for the anchors and interval; the ledger sourceBinding names INDPRO, while the forecasted value is the G.17 monthly percent-change print derived from that total index target."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: fed-g17-industrial-production-total-index-mom-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-18\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.fed-g17-capacity-utilization-total-industry-july-2026.2026-07-25T16-02-12Z.227c8fd7489d1521","runId":"run.fed-g17-capacity-utilization-total-industry-july-2026.2026-07-25T16-02-12Z.227c8fd7489d1521","predictionId":"fed-g17-capacity-utilization-total-industry-july-2026","specId":"spec.fed-g17-capacity-utilization-total-industry-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Reference class/base rate: before applying sector details, I anchor on persistence of the latest official total-industry utilization level for this rate series and on recent same-series monthly changes, not on the long-run 79.4 average, because capacity utilization gaps tend to close slowly absent a large output shock.","Prior/update/interval: persistence prior = latest TCU 76.0937 from the official/FRED history; historical sample = detailed monthly TCU Dec 2025-Jun 2026 values 75.6422, 75.2420, 75.8299, 75.5313, 76.0625, 76.1019, 76.0937; adjustment components = +0.03 for recent IP/utilization momentum, +0.02 for mining/utilities strength, -0.00 for flat manufacturing net, so point = 76.0937 + 0.05 = 76.1437, rounded to 76.14. Interval method = sample standard deviation of successive monthly changes -0.4002, +0.5879, -0.2986, +0.5312, +0.0394, -0.0082; sigma = 0.411 percentage point, 80 percent half-width = 1.28*sigma = 0.526, so interval = 76.1437 +/- 0.526 = 75.62 to 76.66 after rounding."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this forecast is for Federal Reserve G.17 Table 7, Capacity Utilization, Total industry, seasonally adjusted percent of capacity, July 2026 first print. The ledger target uses series code TCU and first_print policy; FRED/ALFRED can mirror the history, but resolution should cite the Federal Reserve G.17 release. The official rounded Table 7 value may be one decimal while the ALFRED TCU binding preserves more decimals; the target remains percent either way.","Reference class/base rate: before applying sector details, I anchor on persistence of the latest official total-industry utilization level for this rate series and on recent same-series monthly changes, not on the long-run 79.4 average, because capacity utilization gaps tend to close slowly absent a large output shock."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["US Total Industry Capacity Utilization, July 2026 First Print","Framing and exact resolver: this forecast is for Federal Reserve G.17 Table 7, Capacity Utilization, Total industry, seasonally adjusted percent of capacity, July 2026 first print. The ledger target uses series code TCU and first_print policy; FRED/ALFRED can mirror the history, but resolution should cite the Federal Reserve G.17 release. The official rounded Table 7 value may be one decimal while the ALFRED TCU binding preserves more decimals; the target remains percent either way."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.04, distribution present, forecast step count 1.","evidence":["Reference class/base rate: before applying sector details, I anchor on persistence of the latest official total-industry utilization level for this rate series and on recent same-series monthly changes, not on the long-run 79.4 average, because capacity utilization gaps tend to close slowly absent a large output shock.","Tool call: FRED/ALFRED TCU recent observations used as detailed public history mirror for the official G.17 series"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Reference class/base rate: before applying sector details, I anchor on persistence of the latest official total-industry utilization level for this rate series and on recent same-series monthly changes, not on the long-run 79.4 average, because capacity utilization gaps tend to close slowly absent a large output shock.","Level, momentum, and mechanism: the level anchor is June TCU 76.0937. Momentum is mildly positive because April-June stayed near 76.1 after a March dip, total IP still rose 0.1 percent in June, and mining/utilities rose 0.4 percent each; the offset is flat manufacturing output and manufacturing utilization easing to 75.7. I add only +0.05 percentage point for July because the target is a monthly rate and capacity growth mechanically dampens a small output increase."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Framing and exact resolver: this forecast is for Federal Reserve G.17 Table 7, Capacity Utilization, Total industry, seasonally adjusted percent of capacity, July 2026 first print. The ledger target uses series code TCU and first_print policy; FRED/ALFRED can mirror the history, but resolution should cite the Federal Reserve G.17 release. The official rounded Table 7 value may be one decimal while the ALFRED TCU binding preserves more decimals; the target remains percent either way.","Level, momentum, and mechanism: the level anchor is June TCU 76.0937. Momentum is mildly positive because April-June stayed near 76.1 after a March dip, total IP still rose 0.1 percent in June, and mining/utilities rose 0.4 percent each; the offset is flat manufacturing output and manufacturing utilization easing to 75.7. I add only +0.05 percentage point for July because the target is a monthly rate and capacity growth mechanically dampens a small output increase."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Framing and exact resolver: this forecast is for Federal Reserve G.17 Table 7, Capacity Utilization, Total industry, seasonally adjusted percent of capacity, July 2026 first print. The ledger target uses series code TCU and first_print policy; FRED/ALFRED can mirror the history, but resolution should cite the Federal Reserve G.17 release. The official rounded Table 7 value may be one decimal while the ALFRED TCU binding preserves more decimals; the target remains percent either way.","Tool result: The July 17, 2026 G.17 release says total capacity utilization was unchanged at 76.1 percent in June, 3.3 percentage points below its 1972-2025 average of 79.4; Table 7 shows total industry 2026 Jan 75.2, Feb 75.8, Mar 75.5, Apr 76.1, May 76.1, June 76.1."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: fed-g17-capacity-utilization-total-industry-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-18\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.census-housing-starts-saar-july-2026.2026-07-25T16-04-14Z.20ca129156b34193","runId":"run.census-housing-starts-saar-july-2026.2026-07-25T16-04-14Z.20ca129156b34193","predictionId":"census-housing-starts-saar-july-2026","specId":"spec.census-housing-starts-saar-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Tool call: Checked ALFRED/FRED HOUST release/history pages and Census historical series context for recent first-print/reference values.","Base rate/reference class: the recent first-print level reference class averages about 1.401 million over January-June 2026, with values oscillating between 1.177 million and 1.502 million. That base rate says a July print near 1.35-1.45 million is more plausible than either a new collapse or a durable break above 1.55 million."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing and exact resolver: the target is Census/HUD New Residential Construction Table 3, privately owned housing starts, total units, seasonally adjusted annual rate, for July 2026, first print. The ledger unit is millions, so HOUST thousands are multiplied by 0.001. ALFRED/FRED HOUST is used as the first-print retrieval/history adapter; Census/HUD remains the official release source.","Tool call: Checked the Census Survey of Construction release schedule for the July 2026 New Residential Construction release."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: the target is Census/HUD New Residential Construction Table 3, privately owned housing starts, total units, seasonally adjusted annual rate, for July 2026, first print. The ledger unit is millions, so HOUST thousands are multiplied by 0.001. ALFRED/FRED HOUST is used as the first-print retrieval/history adapter; Census/HUD remains the official release source.","Tool call: Checked the Census Survey of Construction release schedule for the July 2026 New Residential Construction release."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.56, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is the latest official first print, 1.427 million, cross-checked against the six-month first-print mean of 1.401 million. Adjustment components: -0.04 million for likely giveback from June's volatile multifamily jump from 0.284 million in May to 0.513 million in June, -0.02 million because June permits at 1.367 million trail starts, and about +0.00 to +0.01 million because single-family starts were stable near 0.895 million. This gives a point near 1.37 million. Interval method uses successive first-print changes from Jan-Jun: -0.141, +0.156, -0.037, -0.288, +0.250 million; sigma = 0.218 million, so 1.28*sigma = 0.279 million. Rounded 80% bounds are 1.37 - 0.28 = 1.09 and 1.37 + 0.28 = 1.65 million.","Counter-considerations: upside risk is another multifamily-heavy month or faster conversion of permits to starts, which would land above the interval if total starts exceed 1.65 million. Downside risk is a reversal of June multifamily starts plus weaker single-family starts under high mortgage rates, which would land below the interval if total starts fall under 1.09 million."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior is the latest official first print, 1.427 million, cross-checked against the six-month first-print mean of 1.401 million. Adjustment components: -0.04 million for likely giveback from June's volatile multifamily jump from 0.284 million in May to 0.513 million in June, -0.02 million because June permits at 1.367 million trail starts, and about +0.00 to +0.01 million because single-family starts were stable near 0.895 million. This gives a point near 1.37 million. Interval method uses successive first-print changes from Jan-Jun: -0.141, +0.156, -0.037, -0.288, +0.250 million; sigma = 0.218 million, so 1.28*sigma = 0.279 million. Rounded 80% bounds are 1.37 - 0.28 = 1.09 and 1.37 + 0.28 = 1.65 million."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-considerations: upside risk is another multifamily-heavy month or faster conversion of permits to starts, which would land above the interval if total starts exceed 1.65 million. Downside risk is a reversal of June multifamily starts plus weaker single-family starts under high mortgage rates, which would land below the interval if total starts fall under 1.09 million."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["July 2026 US housing starts SAAR forecast","Prior/update/interval: persistence prior is the latest official first print, 1.427 million, cross-checked against the six-month first-print mean of 1.401 million. Adjustment components: -0.04 million for likely giveback from June's volatile multifamily jump from 0.284 million in May to 0.513 million in June, -0.02 million because June permits at 1.367 million trail starts, and about +0.00 to +0.01 million because single-family starts were stable near 0.895 million. This gives a point near 1.37 million. Interval method uses successive first-print changes from Jan-Jun: -0.141, +0.156, -0.037, -0.288, +0.250 million; sigma = 0.218 million, so 1.28*sigma = 0.279 million. Rounded 80% bounds are 1.37 - 0.28 = 1.09 and 1.37 + 0.28 = 1.65 million."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: census-housing-starts-saar-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-18\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bls-import-price-index-all-imports-mom-july-2026.2026-07-25T16-09-43Z.ae2d44482297601d","runId":"run.bls-import-price-index-all-imports-mom-july-2026.2026-07-25T16-09-43Z.ae2d44482297601d","predictionId":"bls-import-price-index-all-imports-mom-july-2026","specId":"spec.bls-import-price-index-all-imports-mom-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Reference class/base rate: the immediate six-month all-imports MoM reference class is 0.5, 1.0, 0.9, 2.1, 1.7, and 0.3, with a mean near 1.08. The June print cooled sharply, but the regime is still above the pre-2026 flat readings because fuel and nonfuel import prices have both been contributing at times.","Prior/update/interval: Use a recent-realized-value persistence prior on Jan-Jun 2026 BLS all-imports monthly changes [0.5, 1.0, 0.9, 2.1, 1.7, 0.3], whose sample mean is 1.08 and sample sigma = 0.69 percentage points; 1.28*sigma = 0.88 percentage points. Update the point from the 1.08 base rate to 1.0: -0.2 for June cooling and a firmer dollar/nonfuel moderation, +0.1 to +0.2 for late-July oil/fuel upside with about 10% fuel weight and still-positive nonfuel goods. Rounded 80% bounds are 1.0 +/- 0.9, or 0.1 to 1.9. This interval is based on only six recent monthly observations, so it should be read as a current-regime realized-dispersion estimate rather than a long-history volatility estimate."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["BLS July 2026 All-Imports Monthly Price Forecast","Resolver framing: this targets BLS Import Price Index (End Use): All Commodities, series IR, not seasonally adjusted, Table 1 monthly percent change for July 2026, first print only. FRED/ALFRED can mirror history, but final resolution should cite the BLS release table."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Resolver framing: this targets BLS Import Price Index (End Use): All Commodities, series IR, not seasonally adjusted, Table 1 monthly percent change for July 2026, first print only. FRED/ALFRED can mirror history, but final resolution should cite the BLS release table.","Tool call: Checked BLS schedule for U.S. Import and Export Price Indexes release dates."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.8, distribution present, forecast step count 1.","evidence":["Prior/update/interval: Use a recent-realized-value persistence prior on Jan-Jun 2026 BLS all-imports monthly changes [0.5, 1.0, 0.9, 2.1, 1.7, 0.3], whose sample mean is 1.08 and sample sigma = 0.69 percentage points; 1.28*sigma = 0.88 percentage points. Update the point from the 1.08 base rate to 1.0: -0.2 for June cooling and a firmer dollar/nonfuel moderation, +0.1 to +0.2 for late-July oil/fuel upside with about 10% fuel weight and still-positive nonfuel goods. Rounded 80% bounds are 1.0 +/- 0.9, or 0.1 to 1.9. This interval is based on only six recent monthly observations, so it should be read as a current-regime realized-dispersion estimate rather than a long-history volatility estimate.","Counter-considerations: upside risk is a sustained late-July fuel-import jump if Brent near the high-$90s feeds directly into the BLS pricing month, which would land above the interval. Downside risk is a rapid oil reversal plus weaker nonfuel industrial supplies or automotive import prices, which would land below the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Read BLS June 2026 release summary for component momentum.","Tool call: Checked public oil-price context because fuel imports are the volatile July mechanism."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Resolver framing: this targets BLS Import Price Index (End Use): All Commodities, series IR, not seasonally adjusted, Table 1 monthly percent change for July 2026, first print only. FRED/ALFRED can mirror history, but final resolution should cite the BLS release table.","Reference class/base rate: the immediate six-month all-imports MoM reference class is 0.5, 1.0, 0.9, 2.1, 1.7, and 0.3, with a mean near 1.08. The June print cooled sharply, but the regime is still above the pre-2026 flat readings because fuel and nonfuel import prices have both been contributing at times."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["BLS July 2026 All-Imports Monthly Price Forecast","Prior/update/interval: Use a recent-realized-value persistence prior on Jan-Jun 2026 BLS all-imports monthly changes [0.5, 1.0, 0.9, 2.1, 1.7, 0.3], whose sample mean is 1.08 and sample sigma = 0.69 percentage points; 1.28*sigma = 0.88 percentage points. Update the point from the 1.08 base rate to 1.0: -0.2 for June cooling and a firmer dollar/nonfuel moderation, +0.1 to +0.2 for late-July oil/fuel upside with about 10% fuel weight and still-positive nonfuel goods. Rounded 80% bounds are 1.0 +/- 0.9, or 0.1 to 1.9. This interval is based on only six recent monthly observations, so it should be read as a current-regime realized-dispersion estimate rather than a long-history volatility estimate."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bls-import-price-index-all-imports-mom-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-18\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-new-home-sales-saar-july-2026.2026-07-25T16-06-02Z.089c18f6d6aa064f","runId":"run.us-new-home-sales-saar-july-2026.2026-07-25T16-06-02Z.089c18f6d6aa064f","predictionId":"us-new-home-sales-saar-july-2026","specId":"spec.us-new-home-sales-saar-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: recent same-variant monthly SAAR changes are very noisy. A persistence prior from the latest 628 thousand is the natural base rate, with recent changes of -17, +50, +16, -62, +105, -34, -147, +54, +29, -13, -28, and +10 thousand across the fetched 2025-06 to 2026-06 sequence.","Prior/update/interval: persistence prior = 628. Adjustment components: -5 for soft single-family permits, -3 for elevated 9.3 months' supply and below-year-ago sales, giving point = 628 - 8 = 620. Historical sample = same-variant monthly SAAR changes from 2025-06 through 2026-06. The sample standard deviation of successive changes is sigma = 64.25 thousand. 80% half-width = 1.28*sigma = 1.28*64.25 = 82.24 thousand, rounded to 82. Interval = 620 - 82 to 620 + 82 = 538 to 702."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: the target is Census/HUD New Residential Sales Table 1a, United States new single-family houses sold, seasonally adjusted annual rate, in thousands, first print for July 2026. The Census release schedule verifies the July 2026 New Residential Sales release for August 25, 2026 at 10:00 AM; the June release also says the July report is scheduled for August 25, 2026.","Tool call: Read Census New Residential Sales current release for latest headline and revision context."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: the target is Census/HUD New Residential Sales Table 1a, United States new single-family houses sold, seasonally adjusted annual rate, in thousands, first print for July 2026. The Census release schedule verifies the July 2026 New Residential Sales release for August 25, 2026 at 10:00 AM; the June release also says the July report is scheduled for August 25, 2026.","Tool call: Read Census New Residential Sales current release for latest headline and revision context."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 164, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = 628. Adjustment components: -5 for soft single-family permits, -3 for elevated 9.3 months' supply and below-year-ago sales, giving point = 628 - 8 = 620. Historical sample = same-variant monthly SAAR changes from 2025-06 through 2026-06. The sample standard deviation of successive changes is sigma = 64.25 thousand. 80% half-width = 1.28*sigma = 1.28*64.25 = 82.24 thousand, rounded to 82. Interval = 620 - 82 to 620 + 82 = 538 to 702.","Counter-consideration: upside risk is a July demand rebound from rate relief or builder incentives that would land above the interval, above 702 thousand, especially if the South recovers from June weakness. Downside risk is a renewed sales drop from high mortgage rates, cancellations, or excess inventory that would land below the interval, below 538 thousand. Values outside the interval are plausible because this series has large sampling and month-to-month volatility."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level and momentum: the latest print improved only 10 thousand from May and remained 37 thousand below June 2025. The May-to-June rebound argues against extrapolating the May weakness, but the year-over-year decline and high 9.3 months' supply argue against a strong July acceleration.","Counter-consideration: upside risk is a July demand rebound from rate relief or builder incentives that would land above the interval, above 702 thousand, especially if the South recovers from June weakness. Downside risk is a renewed sales drop from high mortgage rates, cancellations, or excess inventory that would land below the interval, below 538 thousand. Values outside the interval are plausible because this series has large sampling and month-to-month volatility."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level and momentum: the latest print improved only 10 thousand from May and remained 37 thousand below June 2025. The May-to-June rebound argues against extrapolating the May weakness, but the year-over-year decline and high 9.3 months' supply argue against a strong July acceleration.","Mechanism adjustment: June single-family permits fell to 871 thousand from 892 thousand, and total permits fell to 1,367 thousand from 1,410 thousand. That does not mechanically determine sales, but it supports a small downward adjustment from pure 628 persistence rather than an upward continuation."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: persistence prior = 628. Adjustment components: -5 for soft single-family permits, -3 for elevated 9.3 months' supply and below-year-ago sales, giving point = 628 - 8 = 620. Historical sample = same-variant monthly SAAR changes from 2025-06 through 2026-06. The sample standard deviation of successive changes is sigma = 64.25 thousand. 80% half-width = 1.28*sigma = 1.28*64.25 = 82.24 thousand, rounded to 82. Interval = 620 - 82 to 620 + 82 = 538 to 702.","Counter-consideration: upside risk is a July demand rebound from rate relief or builder incentives that would land above the interval, above 702 thousand, especially if the South recovers from June weakness. Downside risk is a renewed sales drop from high mortgage rates, cancellations, or excess inventory that would land below the interval, below 538 thousand. Values outside the interval are plausible because this series has large sampling and month-to-month volatility."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-new-home-sales-saar-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-25\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-goods-services-trade-deficit-july-2026.2026-07-25T16-07-46Z.b5b7d7d56d48df25","runId":"run.us-goods-services-trade-deficit-july-2026.2026-07-25T16-07-46Z.b5b7d7d56d48df25","predictionId":"us-goods-services-trade-deficit-july-2026","specId":"spec.us-goods-services-trade-deficit-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: the same-variant 2026 monthly first/latest-reference sample after the annual-revision release context has a positive-deficit mean of about 59.6 billion, while the January-April cluster alone averages about 55.1 billion. May's 77.6 billion print says the immediate trade-flow regime is above that base rate, so the point forecast uses May persistence as the primary prior and pulls it partway back toward the pre-May cluster.","Prior/update/interval: base-rate sample = Jan-May 2026 positive BOPGSTB deficits of 54.185, 54.980, 56.585, 54.570, and 77.585, with full-sample mean 59.6 and January-April mean 55.1; chosen prior = May persistence at 77.6 because July is only two months after the latest observed same-variant shock and the May release showed broad goods import/export movement; adjustment components = -8.0 for partial mean reversion toward the 55.1 January-April base-rate cluster, -0.5 for some normalization of the goods shock after nonmonetary gold/capital-goods volatility, and -0.1 for a roughly stable services surplus near 28.9, giving 77.6 - 8.6 = 69.0. For this flow series I use the short-sample value dispersion as an uncertainty proxy: sample sigma = 10.1 usd_billions, so 80% half-width is about 1.28*sigma = 1.28*10.1 = 12.9; final bounds are 69.0 - 12.9 = 56.1 and 69.0 + 12.9 = 81.9."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this targets the July 2026 first print of the U.S. International Trade in Goods and Services headline goods-and-services balance, seasonally adjusted and on a balance of payments basis, reported in Exhibit 1. The ledger transform turns BOPGSTB's negative millions-of-dollars balance into a positive usd_billions deficit; the agency first print is authoritative over later revisions.","Tool call: Fetched the latest official BEA/Census release for May 2026 to anchor the same variant and near-term components."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this targets the July 2026 first print of the U.S. International Trade in Goods and Services headline goods-and-services balance, seasonally adjusted and on a balance of payments basis, reported in Exhibit 1. The ledger transform turns BOPGSTB's negative millions-of-dollars balance into a positive usd_billions deficit; the agency first print is authoritative over later revisions.","Tool call: Checked BEA 2026 release schedule and the BEA scheduled-release node for U.S. International Trade in Goods and Services, July 2026."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 25.8, distribution present, forecast step count 1.","evidence":["Tool call: Read May 2026 release detail for goods/services decomposition and one-off movement clues.","Prior/update/interval: base-rate sample = Jan-May 2026 positive BOPGSTB deficits of 54.185, 54.980, 56.585, 54.570, and 77.585, with full-sample mean 59.6 and January-April mean 55.1; chosen prior = May persistence at 77.6 because July is only two months after the latest observed same-variant shock and the May release showed broad goods import/export movement; adjustment components = -8.0 for partial mean reversion toward the 55.1 January-April base-rate cluster, -0.5 for some normalization of the goods shock after nonmonetary gold/capital-goods volatility, and -0.1 for a roughly stable services surplus near 28.9, giving 77.6 - 8.6 = 69.0. For this flow series I use the short-sample value dispersion as an uncertainty proxy: sample sigma = 10.1 usd_billions, so 80% half-width is about 1.28*sigma = 1.28*10.1 = 12.9; final bounds are 69.0 - 12.9 = 56.1 and 69.0 + 12.9 = 81.9."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: base-rate sample = Jan-May 2026 positive BOPGSTB deficits of 54.185, 54.980, 56.585, 54.570, and 77.585, with full-sample mean 59.6 and January-April mean 55.1; chosen prior = May persistence at 77.6 because July is only two months after the latest observed same-variant shock and the May release showed broad goods import/export movement; adjustment components = -8.0 for partial mean reversion toward the 55.1 January-April base-rate cluster, -0.5 for some normalization of the goods shock after nonmonetary gold/capital-goods volatility, and -0.1 for a roughly stable services surplus near 28.9, giving 77.6 - 8.6 = 69.0. For this flow series I use the short-sample value dispersion as an uncertainty proxy: sample sigma = 10.1 usd_billions, so 80% half-width is about 1.28*sigma = 1.28*10.1 = 12.9; final bounds are 69.0 - 12.9 = 56.1 and 69.0 + 12.9 = 81.9.","Review disposition: accepted the critique to make the base-rate and persistence-prior bridge explicit, treating May persistence as the chosen prior because of release proximity while using the 2026 reference-class base rate for the mean-reversion update; retained the resolver, source grounding, release date, and interval arithmetic."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: base-rate sample = Jan-May 2026 positive BOPGSTB deficits of 54.185, 54.980, 56.585, 54.570, and 77.585, with full-sample mean 59.6 and January-April mean 55.1; chosen prior = May persistence at 77.6 because July is only two months after the latest observed same-variant shock and the May release showed broad goods import/export movement; adjustment components = -8.0 for partial mean reversion toward the 55.1 January-April base-rate cluster, -0.5 for some normalization of the goods shock after nonmonetary gold/capital-goods volatility, and -0.1 for a roughly stable services surplus near 28.9, giving 77.6 - 8.6 = 69.0. For this flow series I use the short-sample value dispersion as an uncertainty proxy: sample sigma = 10.1 usd_billions, so 80% half-width is about 1.28*sigma = 1.28*10.1 = 12.9; final bounds are 69.0 - 12.9 = 56.1 and 69.0 + 12.9 = 81.9.","Counter-considerations: upside risk for a larger positive deficit would be another July import surge in consumer goods, autos, semiconductors, crude oil, or a further export slump, which would land above the interval if the deficit exceeds 81.9 billion. Downside risk would be a quick reversal of May's import jump, a rebound in goods exports, or weaker domestic demand for imported goods, which would land below the interval if the deficit is under 56.1 billion."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: July 2026 U.S. goods and services trade deficit","Reference class and base rate: the same-variant 2026 monthly first/latest-reference sample after the annual-revision release context has a positive-deficit mean of about 59.6 billion, while the January-April cluster alone averages about 55.1 billion. May's 77.6 billion print says the immediate trade-flow regime is above that base rate, so the point forecast uses May persistence as the primary prior and pulls it partway back toward the pre-May cluster."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-goods-services-trade-deficit-july-2026\nrunLabel: Headline\nresolutionDate: 2026-09-03\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.initial-claims-week-2026-07-25.2026-07-21T01-03-01Z.9676d5b12b26e120","runId":"run.initial-claims-week-2026-07-25.2026-07-21T01-03-01Z.9676d5b12b26e120","predictionId":"initial-claims-week-2026-07-25","specId":"spec.initial-claims-week-2026-07-25","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The five-week reference class has a 216.8-thousand mean and a 208-thousand latest observation. The base rate is short-horizon persistence with modest mean reversion: the level is low relative to that recent mean, while the sequence 227, 216, 217, 216, 208 does not show an accelerating rise.","Level contributes a 208-thousand anchor; momentum is mildly negative; mean reversion contributes about +4 thousand; no verified policy mechanism warrants a large displacement. Holiday-related seasonal adjustment around early July is the main one-off uncertainty. The historical anchors are latest available, potentially revised, seasonally adjusted ICSA levels; only the forecast target is restricted to the advance first print."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The target is the advance first print of national seasonally adjusted initial claims, series ICSA, for the week ending Saturday, July 25, 2026. The DOL publication schedule says the report is issued Thursday at 8:30 a.m. Eastern and lists only November 25 as a 2026 exception; the release calendar confirms July 30. Resolution therefore uses the July 30 DOL report without later revisions.","Tool call: Fetch recent ICSA observations from the public ALFRED history mirror."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the advance first print of national seasonally adjusted initial claims, series ICSA, for the week ending Saturday, July 25, 2026. The DOL publication schedule says the report is issued Thursday at 8:30 a.m. Eastern and lists only November 25 as a 2026 exception; the release calendar confirms July 30. Resolution therefore uses the July 30 DOL report without later revisions.","Tool result: The schedule states weekly publication on Thursday at 8:30 a.m. Eastern and identifies 1 exceptional 2026 release date, November 25; therefore the July 25 reference week is scheduled for July 30, 2026."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 20, distribution present, forecast step count 1.","evidence":["Level contributes a 208-thousand anchor; momentum is mildly negative; mean reversion contributes about +4 thousand; no verified policy mechanism warrants a large displacement. Holiday-related seasonal adjustment around early July is the main one-off uncertainty. The historical anchors are latest available, potentially revised, seasonally adjusted ICSA levels; only the forecast target is restricted to the advance first print.","Prior/update/interval: The model is persistence plus partial mean reversion, using the five fetched observations 227, 216, 217, 216, and 208. Successive changes are -11, +1, -1, and -8 thousand; their sample standard deviation is sigma = sqrt(96.75/3) = 5.7 thousand per week. The July 18 observation is not yet available at run time, making this effectively a two-step forecast, so the horizon-adjusted sigma is 5.7*sqrt(2) = 8.1 and the 80% half-width is roughly 1.28*sigma = 10.4 thousand. The 208 persistence prior plus a +4-thousand mean-reversion adjustment and approximately zero net momentum, one-off, and policy adjustments gives 212; rounding 212 ± 10.4 to whole thousands implies bounds of 202 and 222."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level contributes a 208-thousand anchor; momentum is mildly negative; mean reversion contributes about +4 thousand; no verified policy mechanism warrants a large displacement. Holiday-related seasonal adjustment around early July is the main one-off uncertainty. The historical anchors are latest available, potentially revised, seasonally adjusted ICSA levels; only the forecast target is restricted to the advance first print.","Prior/update/interval: The model is persistence plus partial mean reversion, using the five fetched observations 227, 216, 217, 216, and 208. Successive changes are -11, +1, -1, and -8 thousand; their sample standard deviation is sigma = sqrt(96.75/3) = 5.7 thousand per week. The July 18 observation is not yet available at run time, making this effectively a two-step forecast, so the horizon-adjusted sigma is 5.7*sqrt(2) = 8.1 and the 80% half-width is roughly 1.28*sigma = 10.4 thousand. The 208 persistence prior plus a +4-thousand mean-reversion adjustment and approximately zero net momentum, one-off, and policy adjustments gives 212; rounding 212 ± 10.4 to whole thousands implies bounds of 202 and 222."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level contributes a 208-thousand anchor; momentum is mildly negative; mean reversion contributes about +4 thousand; no verified policy mechanism warrants a large displacement. Holiday-related seasonal adjustment around early July is the main one-off uncertainty. The historical anchors are latest available, potentially revised, seasonally adjusted ICSA levels; only the forecast target is restricted to the advance first print.","Upside risk comes from a renewed burst of layoffs or unusually adverse seasonal adjustment and would land above the interval if the first print exceeds 222 thousand. Downside risk comes from continued unusually low filings or favorable seasonal adjustment and would land below the interval if the first print is under 202 thousand."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Advance initial claims forecast for the week ending July 25, 2026","Tool result: Latest available seasonally adjusted ICSA values, in thousands, were 227 on 2026-06-13, 216 on 2026-06-20, 217 on 2026-06-27, 216 on 2026-07-04, and 208 on 2026-07-11; these may incorporate revisions and are forecasting inputs, not first-print targets."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: initial-claims-week-2026-07-25\nrunLabel: Headline\nresolutionDate: 2026-07-30\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.initial-claims-week-2026-07-25.2026-07-21T01-03-01Z.time-series-prior.c99343ff097bed09","runId":"run.initial-claims-week-2026-07-25.2026-07-21T01-03-01Z.time-series-prior.c99343ff097bed09","predictionId":"initial-claims-week-2026-07-25","specId":"spec.initial-claims-week-2026-07-25","runLabel":"Ledger persistence baseline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.16,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Time-series prior","Tool call: brier.timeseries.prior({ target: \"us.dol.initial_claims.sa.week_2026-07-25\", model: \"persistence.last_print\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Tool result: latest=208 (2026-07-11); history_points=4; interval_method=ledger_realized_step_change_p80; ledger_refs=us.dol.initial_claims.sa.week_2026-06-13,us.dol.initial_claims.sa.week_2026-06-20,us.dol.initial_claims.sa.week_2026-07-04,us.dol.initial_claims.sa.week_2026-07-11"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 18.8, distribution present, forecast step count 1.","evidence":["Tool result: latest=208 (2026-07-11); history_points=4; interval_method=ledger_realized_step_change_p80; ledger_refs=us.dol.initial_claims.sa.week_2026-06-13,us.dol.initial_claims.sa.week_2026-06-20,us.dol.initial_claims.sa.week_2026-07-04,us.dol.initial_claims.sa.week_2026-07-11","Prior point = latest observed value = 208; 80% interval = [199, 217]."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: latest=208 (2026-07-11); history_points=4; interval_method=ledger_realized_step_change_p80; ledger_refs=us.dol.initial_claims.sa.week_2026-06-13,us.dol.initial_claims.sa.week_2026-06-20,us.dol.initial_claims.sa.week_2026-07-04,us.dol.initial_claims.sa.week_2026-07-11","Prior point = latest observed value = 208; 80% interval = [199, 217]."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: initial-claims-week-2026-07-25\nrunLabel: Ledger persistence baseline\nresolutionDate: 2026-07-30\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.continued-claims-week-2026-07-25.2026-07-21T01-04-32Z.6e2312977debe616","runId":"run.continued-claims-week-2026-07-25.2026-07-21T01-04-32Z.6e2312977debe616","predictionId":"continued-claims-week-2026-07-25","specId":"spec.continued-claims-week-2026-07-25","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 12 historical point(s) and explicit outside-view language.","evidence":["Tool result: For the week ending July 4, advance seasonally adjusted insured unemployment was 1,805,000, down 16,000; the prior week was revised to 1,821,000, and the four-week average was 1,811,000.","Tool result: June payroll employment increased 57,000, the unemployment rate was 4.2%, and average payroll growth over the prior 12 months was 36,000."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["The target is ETA insured unemployment (continued claims), seasonally adjusted, for the week ending July 25—not initial claims, unadjusted claims, or all-program continued weeks. The canonical machine resolver uses the ALFRED CCSA advance vintage, whose underlying observation is the DOL ETA first print; later revisions do not alter the outcome.","Tool result: ETA states publication is Thursday at 8:30 a.m. ET except federal-holiday adjustments, and the 2026 calendar lists Thursday, August 6, 2026 for the weekly claims release, within the ledger window of August 4–8."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is ETA insured unemployment (continued claims), seasonally adjusted, for the week ending July 25—not initial claims, unadjusted claims, or all-program continued weeks. The canonical machine resolver uses the ALFRED CCSA advance vintage, whose underlying observation is the DOL ETA first print; later revisions do not alter the outcome.","Tool call: Read the July 16, 2026 ETA Unemployment Insurance Weekly Claims release."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.04, distribution present, forecast step count 1.","evidence":["The reference class/base rate is short-horizon persistence in this slow-moving stock series. Its latest level was 1.805 million and four-week average 1.811 million. Level and momentum therefore favor roughly 1.81 million. Falling initial claims reduce near-term inflow, while modest payroll growth and a still-low 4.2% unemployment rate argue against a sharp accumulation. Holiday-related seasonal noise is the main one-off risk.","Prior/update/interval: persistence model prior = 1.805 million, using the 12 fetched ETA levels from April 18 through July 4. The 11 successive changes were -18, +18, -5, +14, -14, +15, +14, +12, -6, +15, and -16 thousand; their sample standard deviation gives sigma = 14.4 thousand. Add 0.005 million for reversion toward the 1.811 million four-week average and broadly stable labor conditions, yielding 1.810 million. This adjustment is small relative to the interval half-width, so the forecast remains mostly persistence-driven. The 80% half-width is 1.28*sigma = 1.28*0.0144 = 0.0184 million, rounded to 0.018, implying 1.792 to 1.828 million."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The reference class/base rate is short-horizon persistence in this slow-moving stock series. Its latest level was 1.805 million and four-week average 1.811 million. Level and momentum therefore favor roughly 1.81 million. Falling initial claims reduce near-term inflow, while modest payroll growth and a still-low 4.2% unemployment rate argue against a sharp accumulation. Holiday-related seasonal noise is the main one-off risk."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The reference class/base rate is short-horizon persistence in this slow-moving stock series. Its latest level was 1.805 million and four-week average 1.811 million. Level and momentum therefore favor roughly 1.81 million. Falling initial claims reduce near-term inflow, while modest payroll growth and a still-low 4.2% unemployment rate argue against a sharp accumulation. Holiday-related seasonal noise is the main one-off risk.","Upside risk is slower benefit exits or an unexpected layoff wave, which could land above 1.828 million. Downside risk is faster reemployment combined with continued low initial claims, which could land below 1.792 million. Either outcome would be outside the interval and falsify the persistence-centered view."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: persistence model prior = 1.805 million, using the 12 fetched ETA levels from April 18 through July 4. The 11 successive changes were -18, +18, -5, +14, -14, +15, +14, +12, -6, +15, and -16 thousand; their sample standard deviation gives sigma = 14.4 thousand. Add 0.005 million for reversion toward the 1.811 million four-week average and broadly stable labor conditions, yielding 1.810 million. This adjustment is small relative to the interval half-width, so the forecast remains mostly persistence-driven. The 80% half-width is 1.28*sigma = 1.28*0.0144 = 0.0184 million, rounded to 0.018, implying 1.792 to 1.828 million.","Upside risk is slower benefit exits or an unexpected layoff wave, which could land above 1.828 million. Downside risk is faster reemployment combined with continued low initial claims, which could land below 1.792 million. Either outcome would be outside the interval and falsify the persistence-centered view."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: continued-claims-week-2026-07-25\nrunLabel: Headline\nresolutionDate: 2026-08-06\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.cps-production-employment-july-2026.2026-07-21T01-13-09Z.6ab2108542cc0d40","runId":"run.cps-production-employment-july-2026.2026-07-21T01-13-09Z.6ab2108542cc0d40","predictionId":"cps-production-employment-july-2026","specId":"spec.cps-production-employment-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 8 historical point(s) and explicit outside-view language.","evidence":["The target is the first BLS print for total people employed in Production occupations in July 2026, not seasonally adjusted, from CPS Employment Situation Table A-19 (cpseea19.htm). BLS reports thousands; the resolver multiplies by 0.001. Later revisions do not replace the first print. Archived A-13 tables are used only as historical evidence where that numbering appeared.","The reference class/base rate is persistence around the latest NSA CPS occupation level with a negative July seasonal update. The January-June sequence is choppy but centered near 7.8 million, while July 2025 fell 0.276 million from June and remained 0.227 million below July 2024."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["The target is the first BLS print for total people employed in Production occupations in July 2026, not seasonally adjusted, from CPS Employment Situation Table A-19 (cpseea19.htm). BLS reports thousands; the resolver multiplies by 0.001. Later revisions do not replace the first print. Archived A-13 tables are used only as historical evidence where that numbering appeared.","Tool call: Read BLS archived Employment Situation releases for January through March 2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the first BLS print for total people employed in Production occupations in July 2026, not seasonally adjusted, from CPS Employment Situation Table A-19 (cpseea19.htm). BLS reports thousands; the resolver multiplies by 0.001. Later revisions do not replace the first print. Archived A-13 tables are used only as historical evidence where that numbering appeared.","Tool call: Read BLS archived Employment Situation releases for January through March 2026."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.38, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = June 2026 first print of 7.759 million; historical sample = January-June 2026 first prints [7.905, 7.742, 7.685, 7.883, 7.912, 7.759]. Successive changes are [-0.163, -0.057, +0.198, +0.029, -0.153] million, whose sample standard deviation is sigma = 0.149 million. Apply a -0.200 million update, mostly a judgmental shrinkage from the single observed June-to-July 2025 decline of -0.276 million, with recent soft year-over-year context and no separate policy adjustment: 7.759 - 0.200 = 7.559. The normal 80% half-width is 1.28*sigma = 1.28*0.149 = 0.191 million, implying bounds 7.559 +/- 0.191 = [7.368, 7.750].","Upside risk is an abrupt rebound like April 2026, which could put the print above 7.750 million. Downside risk is a July seasonal drop materially larger than 2025's 0.276 million or renewed manufacturing weakness; a decline exceeding 0.391 million from June would land below the interval. Either outcome would be outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The reference class/base rate is persistence around the latest NSA CPS occupation level with a negative July seasonal update. The January-June sequence is choppy but centered near 7.8 million, while July 2025 fell 0.276 million from June and remained 0.227 million below July 2024.","Upside risk is an abrupt rebound like April 2026, which could put the print above 7.750 million. Downside risk is a July seasonal drop materially larger than 2025's 0.276 million or renewed manufacturing weakness; a decline exceeding 0.391 million from June would land below the interval. Either outcome would be outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["July 2026 CPS production-occupation employment forecast","Prior/update/interval: persistence prior = June 2026 first print of 7.759 million; historical sample = January-June 2026 first prints [7.905, 7.742, 7.685, 7.883, 7.912, 7.759]. Successive changes are [-0.163, -0.057, +0.198, +0.029, -0.153] million, whose sample standard deviation is sigma = 0.149 million. Apply a -0.200 million update, mostly a judgmental shrinkage from the single observed June-to-July 2025 decline of -0.276 million, with recent soft year-over-year context and no separate policy adjustment: 7.759 - 0.200 = 7.559. The normal 80% half-width is 1.28*sigma = 1.28*0.149 = 0.191 million, implying bounds 7.559 +/- 0.191 = [7.368, 7.750]."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: cps-production-employment-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-06\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.cps-transport-material-moving-employment-july-2026.2026-07-21T01-14-28Z.0d871c5760b1cd0e","runId":"run.cps-transport-material-moving-employment-july-2026.2026-07-21T01-14-28Z.0d871c5760b1cd0e","predictionId":"cps-transport-material-moving-employment-july-2026","specId":"spec.cps-transport-material-moving-employment-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool result: The first-print transportation and material-moving employment values were 12,214 thousand in March 2026 and 12,127 thousand in April 2026; the corresponding prior-year values were 11,958 thousand and 12,059 thousand.","The reference class and base rate are short-horizon forecasts of this noisy NSA CPS occupation level. March-June 2026 declined 12.214 to 12.127 to 12.120 to 12.010 million, while June remained 0.391 million above June 2025. Persistence therefore deserves more weight than extrapolating the latest decline. A separate July-specific seasonal prior was not established from the cited observations."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["The resolver is BLS CPS Table A-19, Transportation and material moving occupations, Total age 16+, not seasonally adjusted, first July 2026 print in thousands converted to millions. This is distinct from seasonally adjusted establishment-survey transportation and warehousing payrolls.","Tool call: Read the current BLS CPS Table A-19 and June 2026 Employment Situation archive."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is BLS CPS Table A-19, Transportation and material moving occupations, Total age 16+, not seasonally adjusted, first July 2026 print in thousands converted to millions. This is distinct from seasonally adjusted establishment-survey transportation and warehousing payrolls.","Tool result: The first-print transportation and material-moving employment values were 12,214 thousand in March 2026 and 12,127 thousand in April 2026; the corresponding prior-year values were 11,958 thousand and 12,059 thousand."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.36, distribution present, forecast step count 1.","evidence":["Prior/update/interval: The model is level persistence at June's 12.010 million. The historical sample comprises six month-to-month changes from the fetched 2025 and 2026 occupation sequences: +0.101, -0.317, -0.123, -0.087, -0.007, and -0.110 million. Their sample dispersion is sigma = 0.139 million. The recent downward momentum adjustment (-0.04) is offset by positive year-over-year level and mean reversion (+0.04), leaving 12.010 million. The normal 80% half-width is 1.28*sigma = 1.28*0.139 = 0.178 million, rounded to 0.18, implying 11.83 to 12.19 million.","A stronger-than-normal summer expansion in delivery, warehousing, or passenger transport is the upside risk and would land above the interval. Broad household-employment weakness, accelerated logistics layoffs, or an adverse CPS sampling swing is the downside risk and could land below the interval; either outcome would be outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: The model is level persistence at June's 12.010 million. The historical sample comprises six month-to-month changes from the fetched 2025 and 2026 occupation sequences: +0.101, -0.317, -0.123, -0.087, -0.007, and -0.110 million. Their sample dispersion is sigma = 0.139 million. The recent downward momentum adjustment (-0.04) is offset by positive year-over-year level and mean reversion (+0.04), leaving 12.010 million. The normal 80% half-width is 1.28*sigma = 1.28*0.139 = 0.178 million, rounded to 0.18, implying 11.83 to 12.19 million."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: The model is level persistence at June's 12.010 million. The historical sample comprises six month-to-month changes from the fetched 2025 and 2026 occupation sequences: +0.101, -0.317, -0.123, -0.087, -0.007, and -0.110 million. Their sample dispersion is sigma = 0.139 million. The recent downward momentum adjustment (-0.04) is offset by positive year-over-year level and mean reversion (+0.04), leaving 12.010 million. The normal 80% half-width is 1.28*sigma = 1.28*0.139 = 0.178 million, rounded to 0.18, implying 11.83 to 12.19 million.","A stronger-than-normal summer expansion in delivery, warehousing, or passenger transport is the upside risk and would land above the interval. Broad household-employment weakness, accelerated logistics layoffs, or an adverse CPS sampling swing is the downside risk and could land below the interval; either outcome would be outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["July 2026 CPS transportation and material-moving employment forecast","The reference class and base rate are short-horizon forecasts of this noisy NSA CPS occupation level. March-June 2026 declined 12.214 to 12.127 to 12.120 to 12.010 million, while June remained 0.391 million above June 2025. Persistence therefore deserves more weight than extrapolating the latest decline. A separate July-specific seasonal prior was not established from the cited observations."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: cps-transport-material-moving-employment-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-06\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.cps-business-financial-employment-july-2026.2026-07-21T01-06-12Z.ccfad1ced6b72261","runId":"run.cps-business-financial-employment-july-2026.2026-07-21T01-06-12Z.ccfad1ced6b72261","predictionId":"cps-business-financial-employment-july-2026","specId":"spec.cps-business-financial-employment-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["The reference class and base rate are persistence around the latest exact-series level, with substantial CPS sampling noise. The official observations show a lower June 2026 level than June 2025, while the 2024 annual average was 9.945 million.","Prior/update/interval: persistence model prior = 9.720 million; historical sample = 10.205, 9.857, and 9.720 million. Successive observed changes are -0.348 and -0.137 million, giving RMS sigma = sqrt((0.348^2 + 0.137^2)/2) = 0.264 million. Apply a -0.030 million momentum adjustment and no separate one-off or policy adjustment, yielding 9.690 million. The 80% half-width is approximately 1.28*sigma = 1.28*0.264 = 0.338 million, rounded to 0.34, implying 9.35 to 10.03 million. A longer consistent monthly or June-to-July exact-row sample was unavailable in the fetched pre-resolution evidence, so this thin, irregular two-change proxy is retained as a judgmental uncertainty estimate rather than presented as a robust seasonal-volatility estimate."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["July 2026 business and financial operations employment forecast","The resolver is the first July 2026 print in BLS CPS Table A-19 for Business and financial operations occupations, total age 16 years and over, not seasonally adjusted. Table values are thousands and are converted to millions by multiplying by 0.001."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The resolver is the first July 2026 print in BLS CPS Table A-19 for Business and financial operations occupations, total age 16 years and over, not seasonally adjusted. Table values are thousands and are converted to millions by multiplying by 0.001.","Tool result: The BLS 2026 release schedule and CPS calendar both list the July 2026 Employment Situation for August 7, 2026 at 8:30 a.m. ET; the registered expected window ends August 6, one day too early."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.68, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence model prior = 9.720 million; historical sample = 10.205, 9.857, and 9.720 million. Successive observed changes are -0.348 and -0.137 million, giving RMS sigma = sqrt((0.348^2 + 0.137^2)/2) = 0.264 million. Apply a -0.030 million momentum adjustment and no separate one-off or policy adjustment, yielding 9.690 million. The 80% half-width is approximately 1.28*sigma = 1.28*0.264 = 0.338 million, rounded to 0.34, implying 9.35 to 10.03 million. A longer consistent monthly or June-to-July exact-row sample was unavailable in the fetched pre-resolution evidence, so this thin, irregular two-change proxy is retained as a judgmental uncertainty estimate rather than presented as a robust seasonal-volatility estimate.","Upside risk is a rebound in sampled professional hiring or July occupational reclassification, which would land above 10.03 million. Downside risk is continued labor-market weakness combined with adverse CPS sampling, which would land below 9.35 million and outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level effect: anchor at June's 9.720 million. Momentum effect: the observed sequence from 10.205 to 9.857 to 9.720 is negative. One-off effect: noisy CPS occupational allocation argues against extrapolating the full decline. Policy mechanism: no discrete policy change was identified, so only a small judgmental negative adjustment is applied.","Prior/update/interval: persistence model prior = 9.720 million; historical sample = 10.205, 9.857, and 9.720 million. Successive observed changes are -0.348 and -0.137 million, giving RMS sigma = sqrt((0.348^2 + 0.137^2)/2) = 0.264 million. Apply a -0.030 million momentum adjustment and no separate one-off or policy adjustment, yielding 9.690 million. The 80% half-width is approximately 1.28*sigma = 1.28*0.264 = 0.338 million, rounded to 0.34, implying 9.35 to 10.03 million. A longer consistent monthly or June-to-July exact-row sample was unavailable in the fetched pre-resolution evidence, so this thin, irregular two-change proxy is retained as a judgmental uncertainty estimate rather than presented as a robust seasonal-volatility estimate."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence model prior = 9.720 million; historical sample = 10.205, 9.857, and 9.720 million. Successive observed changes are -0.348 and -0.137 million, giving RMS sigma = sqrt((0.348^2 + 0.137^2)/2) = 0.264 million. Apply a -0.030 million momentum adjustment and no separate one-off or policy adjustment, yielding 9.690 million. The 80% half-width is approximately 1.28*sigma = 1.28*0.264 = 0.338 million, rounded to 0.34, implying 9.35 to 10.03 million. A longer consistent monthly or June-to-July exact-row sample was unavailable in the fetched pre-resolution evidence, so this thin, irregular two-change proxy is retained as a judgmental uncertainty estimate rather than presented as a robust seasonal-volatility estimate.","Upside risk is a rebound in sampled professional hiring or July occupational reclassification, which would land above 10.03 million. Downside risk is continued labor-market weakness combined with adverse CPS sampling, which would land below 9.35 million and outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["July 2026 business and financial operations employment forecast","Prior/update/interval: persistence model prior = 9.720 million; historical sample = 10.205, 9.857, and 9.720 million. Successive observed changes are -0.348 and -0.137 million, giving RMS sigma = sqrt((0.348^2 + 0.137^2)/2) = 0.264 million. Apply a -0.030 million momentum adjustment and no separate one-off or policy adjustment, yielding 9.690 million. The 80% half-width is approximately 1.28*sigma = 1.28*0.264 = 0.338 million, rounded to 0.34, implying 9.35 to 10.03 million. A longer consistent monthly or June-to-July exact-row sample was unavailable in the fetched pre-resolution evidence, so this thin, irregular two-change proxy is retained as a judgmental uncertainty estimate rather than presented as a robust seasonal-volatility estimate."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: cps-business-financial-employment-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-07\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.cps-computer-math-employment-july-2026.2026-07-21T01-08-26Z.a4c8dd6f2a658033","runId":"run.cps-computer-math-employment-july-2026.2026-07-21T01-08-26Z.a4c8dd6f2a658033","predictionId":"cps-computer-math-employment-july-2026","specId":"spec.cps-computer-math-employment-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 7 historical point(s) and explicit outside-view language.","evidence":["The outside-view base rate is gradual growth with substantial CPS noise: annual-average employment rose from 5.688 million in 2021 to 6.711 million in 2025, while June 2026 was 0.348 million above June 2025.","Prior/update/interval: persistence model prior = June 2026's 6.950 million; historical sample = 2021-2025 annual averages of 5.688, 6.171, 6.502, 6.386, and 6.711 million. Their successive changes are +0.483, +0.331, -0.116, and +0.325 million, giving trend sigma = 0.236 million. Because annual averages smooth the monthly CPS target, add a monthly sampling/noise proxy of 0.239 million, the absolute gap between June 2026's 6.950 million and the latest 2025 annual average of 6.711 million. Combining these independent components gives sigma = sqrt(0.236^2 + 0.239^2) = 0.336 million. Adjustments are +0.050 million for longer-run momentum and -0.020 million for soft hiring, yielding 6.950 + 0.050 - 0.020 = 6.980 million. The 80% half-width is 1.28*sigma = 1.28*0.336 = 0.430 million, implying 6.550 to 7.410 million."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["The target is the total, age 16 and over, for Computer and mathematical occupations in CPS Table A-19, reported in thousands and not seasonally adjusted. Resolution uses the strict August 7 first print and the table's 0.001 conversion to millions.","Tool call: Fetch the latest BLS CPS Table A-19 observation and matched year-earlier value."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the total, age 16 and over, for Computer and mathematical occupations in CPS Table A-19, reported in thousands and not seasonally adjusted. Resolution uses the strict August 7 first print and the table's 0.001 conversion to millions.","Tool call: Verify the official release date from the BLS CPS calendar and latest Employment Situation notice."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.86, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence model prior = June 2026's 6.950 million; historical sample = 2021-2025 annual averages of 5.688, 6.171, 6.502, 6.386, and 6.711 million. Their successive changes are +0.483, +0.331, -0.116, and +0.325 million, giving trend sigma = 0.236 million. Because annual averages smooth the monthly CPS target, add a monthly sampling/noise proxy of 0.239 million, the absolute gap between June 2026's 6.950 million and the latest 2025 annual average of 6.711 million. Combining these independent components gives sigma = sqrt(0.236^2 + 0.239^2) = 0.336 million. Adjustments are +0.050 million for longer-run momentum and -0.020 million for soft hiring, yielding 6.950 + 0.050 - 0.020 = 6.980 million. The 80% half-width is 1.28*sigma = 1.28*0.336 = 0.430 million, implying 6.550 to 7.410 million.","Upside risk comes from faster AI-related hiring, labor-force re-entry, or favorable CPS sampling and would land above the interval if employment exceeds 7.41 million. Downside risk comes from layoffs, weak hiring, or adverse sampling and would land below the interval if employment is under 6.55 million; either outcome would be outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: BLS CPS Table 9 reports 6,386 thousand in 2024 and 6,711 thousand in 2025; the 2025 figure is an 11-month average because October data were not collected.","Level, momentum, one-off, and mechanism effects: the 6.950 million June level supplies the persistence anchor; positive multi-year growth adds 0.050 million; a judgmental small offset for weak technology hiring subtracts 0.020 million; no identified July-specific policy or classification change warrants another adjustment."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, one-off, and mechanism effects: the 6.950 million June level supplies the persistence anchor; positive multi-year growth adds 0.050 million; a judgmental small offset for weak technology hiring subtracts 0.020 million; no identified July-specific policy or classification change warrants another adjustment.","Upside risk comes from faster AI-related hiring, labor-force re-entry, or favorable CPS sampling and would land above the interval if employment exceeds 7.41 million. Downside risk comes from layoffs, weak hiring, or adverse sampling and would land below the interval if employment is under 6.55 million; either outcome would be outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["July 2026 computer and mathematical employment forecast","Prior/update/interval: persistence model prior = June 2026's 6.950 million; historical sample = 2021-2025 annual averages of 5.688, 6.171, 6.502, 6.386, and 6.711 million. Their successive changes are +0.483, +0.331, -0.116, and +0.325 million, giving trend sigma = 0.236 million. Because annual averages smooth the monthly CPS target, add a monthly sampling/noise proxy of 0.239 million, the absolute gap between June 2026's 6.950 million and the latest 2025 annual average of 6.711 million. Combining these independent components gives sigma = sqrt(0.236^2 + 0.239^2) = 0.336 million. Adjustments are +0.050 million for longer-run momentum and -0.020 million for soft hiring, yielding 6.950 + 0.050 - 0.020 = 6.980 million. The 80% half-width is 1.28*sigma = 1.28*0.336 = 0.430 million, implying 6.550 to 7.410 million."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: cps-computer-math-employment-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-07\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.cps-healthcare-support-employment-july-2026.2026-07-21T01-10-02Z.96b6169fb23af9c9","runId":"run.cps-healthcare-support-employment-july-2026.2026-07-21T01-10-02Z.96b6169fb23af9c9","predictionId":"cps-healthcare-support-employment-july-2026","specId":"spec.cps-healthcare-support-employment-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 3 historical point(s) and explicit outside-view language.","evidence":["The outside-view base rate/reference class is persistence around the latest 5.691 million level, with substantial CPS subgroup noise. The sparse same-variant official history spans 4.911 million in July 2023, 5.950 million in June 2025, and 5.691 million in June 2026.","Prior/update/interval: persistence model prior = 5.691 million; historical sample = 4.911, 5.950, and 5.691 million. Successive changes are +1.039 and -0.259 million; their sample standard deviation gives sigma = sqrt(((1.039-0.390)^2+(-0.259-0.390)^2)/(2-1)) = 0.918 million. Updates are +0.080 judgmental July uplift and +0.030 judgmental structural healthcare-demand uplift, so point = 5.691+0.080+0.030 = 5.801 million. The 80% half-width is 1.28*sigma = 1.28*0.918 = 1.175 million, implying 5.801-1.175 = 4.626 and 5.801+1.175 = 6.976 million."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The resolver is the first July 2026 print for Total employed people age 16 and over in 'Healthcare support occupations' in CPS Table A-19, measured in thousands and not seasonally adjusted, then multiplied by 0.001. All anchors below use that same CPS occupation/NSA variant. The ledger expectedReleaseWindow ending 2026-08-06 conflicts with the official August 7 release date; the forecast remains tied to the registered target and uses the verified official date.","Tool call: Read current BLS CPS Employment Situation Table A-19 for the healthcare support occupations row."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The resolver is the first July 2026 print for Total employed people age 16 and over in 'Healthcare support occupations' in CPS Table A-19, measured in thousands and not seasonally adjusted, then multiplied by 0.001. All anchors below use that same CPS occupation/NSA variant. The ledger expectedReleaseWindow ending 2026-08-06 conflicts with the official August 7 release date; the forecast remains tied to the registered target and uses the verified official date.","Tool call: Verify the July 2026 Employment Situation publication date using the BLS 2026 release calendar and latest release announcement."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.35, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence model prior = 5.691 million; historical sample = 4.911, 5.950, and 5.691 million. Successive changes are +1.039 and -0.259 million; their sample standard deviation gives sigma = sqrt(((1.039-0.390)^2+(-0.259-0.390)^2)/(2-1)) = 0.918 million. Updates are +0.080 judgmental July uplift and +0.030 judgmental structural healthcare-demand uplift, so point = 5.691+0.080+0.030 = 5.801 million. The 80% half-width is 1.28*sigma = 1.28*0.918 = 1.175 million, implying 5.801-1.175 = 4.626 and 5.801+1.175 = 6.976 million.","Upside risk comes from unusually strong household-survey sampling, labor-force entry, or faster caregiving hiring and would land above the interval at more than 6.976 million. Downside risk comes from a sharp participation decline, healthcare funding disruption, or an adverse CPS sampling swing and would land below the interval at less than 4.626 million. The wide interval reflects realized occupation-level dispersion rather than a rounded hedge."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level contributes 5.691 million. Momentum is mixed: the latest year-over-year change is -0.259 million. Because the available official observations do not identify a reliable July seasonal effect or a precise recent occupation-specific trend, the +0.080 million July adjustment and +0.030 million structural-demand adjustment are judgmental and deliberately small relative to sigma; no discrete policy or one-off shock is added."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level contributes 5.691 million. Momentum is mixed: the latest year-over-year change is -0.259 million. Because the available official observations do not identify a reliable July seasonal effect or a precise recent occupation-specific trend, the +0.080 million July adjustment and +0.030 million structural-demand adjustment are judgmental and deliberately small relative to sigma; no discrete policy or one-off shock is added.","Upside risk comes from unusually strong household-survey sampling, labor-force entry, or faster caregiving hiring and would land above the interval at more than 6.976 million. Downside risk comes from a sharp participation decline, healthcare funding disruption, or an adverse CPS sampling swing and would land below the interval at less than 4.626 million. The wide interval reflects realized occupation-level dispersion rather than a rounded hedge."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["July 2026 healthcare support employment forecast","The resolver is the first July 2026 print for Total employed people age 16 and over in 'Healthcare support occupations' in CPS Table A-19, measured in thousands and not seasonally adjusted, then multiplied by 0.001. All anchors below use that same CPS occupation/NSA variant. The ledger expectedReleaseWindow ending 2026-08-06 conflicts with the official August 7 release date; the forecast remains tied to the registered target and uses the verified official date."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: cps-healthcare-support-employment-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-07\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.cps-office-admin-employment-july-2026.2026-07-21T01-11-54Z.a8aec682194c6de0","runId":"run.cps-office-admin-employment-july-2026.2026-07-21T01-11-54Z.a8aec682194c6de0","predictionId":"cps-office-admin-employment-july-2026","specId":"spec.cps-office-admin-employment-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 7 historical point(s) and explicit outside-view language.","evidence":["The outside-view base rate is the recent June-to-July reference class: the two observed increases average (+0.246 + 0.096)/2 = +0.171 million. Applied mechanically to June 2026's 16.184 million, that gives 16.355 million.","Level is 16.184 million in June. Momentum is negative: the March-to-June path fell 0.379 million. The one-off seasonal mechanism points upward in July, while policy and aggregate labor-market effects are modestly negative because June household employment weakened. I therefore trim the seasonal prior by 0.015 million to 16.340 million."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 11 source-context item(s), activity log present.","evidence":["The target is the total employed count for Office and administrative support occupations in CPS Table A-19, not seasonally adjusted and reported in thousands, converted to millions. Resolution uses the first July 2026 print only. The official BLS calendar schedules it for August 7, 2026; this conflicts with the ledger sourceBinding window ending August 6, so the verified official date is used without changing the target.","Tool call: Fetch the BLS Employment Situation release schedule for the July 2026 reference month."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the total employed count for Office and administrative support occupations in CPS Table A-19, not seasonally adjusted and reported in thousands, converted to millions. Resolution uses the first July 2026 print only. The official BLS calendar schedules it for August 7, 2026; this conflicts with the ledger sourceBinding window ending August 6, so the verified official date is used without changing the target.","Tool call: Fetch the BLS Employment Situation release schedule for the July 2026 reference month."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.36, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence-plus-July-seasonality prior, using January-June 2026 first-print NSA levels and the 2024-2025 June-to-July reference class; adjustments are +0.171 million seasonal, -0.015 million for recent negative momentum, and 0.000 million for other mechanisms, yielding 16.184 + 0.171 - 0.015 = 16.340 million. Successive 2026 changes are +0.025, +0.183, -0.092, -0.136, and -0.151 million; their sample standard deviation is sigma = 0.140 million. The normal 80% half-width is 1.28*sigma = 1.28*0.140 = 0.179 million, implying 16.161 to 16.519 million, rounded outward to final bounds of 16.16 to 16.52 million.","Upside risk comes from a July seasonal increase nearer 2024's +0.246 million, which could push the print toward the upper bound. Downside risk comes from continuation of the March-June contraction. An unusually large CPS sampling move or a decline exceeding about 0.024 million from June would land outside the interval below 16.16; a gain above about 0.336 million would land outside the interval above 16.52."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level is 16.184 million in June. Momentum is negative: the March-to-June path fell 0.379 million. The one-off seasonal mechanism points upward in July, while policy and aggregate labor-market effects are modestly negative because June household employment weakened. I therefore trim the seasonal prior by 0.015 million to 16.340 million.","Prior/update/interval: persistence-plus-July-seasonality prior, using January-June 2026 first-print NSA levels and the 2024-2025 June-to-July reference class; adjustments are +0.171 million seasonal, -0.015 million for recent negative momentum, and 0.000 million for other mechanisms, yielding 16.184 + 0.171 - 0.015 = 16.340 million. Successive 2026 changes are +0.025, +0.183, -0.092, -0.136, and -0.151 million; their sample standard deviation is sigma = 0.140 million. The normal 80% half-width is 1.28*sigma = 1.28*0.140 = 0.179 million, implying 16.161 to 16.519 million, rounded outward to final bounds of 16.16 to 16.52 million."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Upside risk comes from a July seasonal increase nearer 2024's +0.246 million, which could push the print toward the upper bound. Downside risk comes from continuation of the March-June contraction. An unusually large CPS sampling move or a decline exceeding about 0.024 million from June would land outside the interval below 16.16; a gain above about 0.336 million would land outside the interval above 16.52."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["July 2026 office and administrative support employment forecast","Level is 16.184 million in June. Momentum is negative: the March-to-June path fell 0.379 million. The one-off seasonal mechanism points upward in July, while policy and aggregate labor-market effects are modestly negative because June household employment weakened. I therefore trim the seasonal prior by 0.015 million to 16.340 million."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: cps-office-admin-employment-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-07\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bls-bed-opening-establishment-gross-job-gains-q4-2025.2026-07-15T21-23-07Z.fe9581501020405c","runId":"run.bls-bed-opening-establishment-gross-job-gains-q4-2025.2026-07-15T21-23-07Z.fe9581501020405c","predictionId":"bls-bed-opening-establishment-gross-job-gains-q4-2025","specId":"spec.bls-bed-opening-establishment-gross-job-gains-q4-2025","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 11 historical point(s) and explicit outside-view language.","evidence":["The outside-view base rate is the recent 2023-Q1 through 2025-Q3 reference class: opening-establishment gains have centered near 1.585 million, while the two latest Q4 observations were higher at 1.637 million and 1.660 million.","Prior/update/interval: A recent-Q4 persistence model uses the 2023-Q4 and 2024-Q4 average, (1,637 + 1,660) / 2 = 1,648.5 thousand, based on the 11-quarter 2023-Q1–2025-Q3 historical sample. Apply the sole adjustment component, -13.5 thousand for softer 2025 total gross gains, giving 1,635.0. Because this is a flow series, dispersion is computed from all 11 listed quarterly values themselves: sample sigma = 40.7 thousand. The normal 80% half-width is 1.28*sigma = 1.28*40.7 = 52.1 thousand, implying 1,635 ± 52, or final bounds of 1,583 to 1,687 thousand."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["BLS opening-establishment gross job gains, 2025 Q4","The target is BLS BED Table 1, total-private gross job gains at opening establishments, seasonally adjusted and measured in thousands—not the opening-firm series or an unadjusted variant. Resolution uses the strict first 2025-Q4 print without correction-day or revision exceptions."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is BLS BED Table 1, total-private gross job gains at opening establishments, seasonally adjusted and measured in thousands—not the opening-firm series or an unadjusted variant. Resolution uses the strict first 2025-Q4 print without correction-day or revision exceptions.","Tool call: Check related total gross job gains and the official release schedule."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 104, distribution present, forecast step count 1.","evidence":["Prior/update/interval: A recent-Q4 persistence model uses the 2023-Q4 and 2024-Q4 average, (1,637 + 1,660) / 2 = 1,648.5 thousand, based on the 11-quarter 2023-Q1–2025-Q3 historical sample. Apply the sole adjustment component, -13.5 thousand for softer 2025 total gross gains, giving 1,635.0. Because this is a flow series, dispersion is computed from all 11 listed quarterly values themselves: sample sigma = 40.7 thousand. The normal 80% half-width is 1.28*sigma = 1.28*40.7 = 52.1 thousand, implying 1,635 ± 52, or final bounds of 1,583 to 1,687 thousand.","Upside risk comes from another Q4 opening surge comparable to or stronger than 2024 and would land above the interval if the first print exceeds 1,687 thousand. Downside risk comes from broad-based establishment-formation weakness or reversal of the Q3 rebound and would land below the interval if the print is under 1,583 thousand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level and momentum point in different directions: the series remains near 1.6 million and rebounded 70 thousand in Q3, but total gross gains eased from 7.585 million to 7.475 million. Recent Q4 strength supports an elevated anchor, while the softer 2025 labor-flow backdrop warrants a modest downward adjustment. No discrete policy or identifiable one-off mechanism justifies a larger shift.","Prior/update/interval: A recent-Q4 persistence model uses the 2023-Q4 and 2024-Q4 average, (1,637 + 1,660) / 2 = 1,648.5 thousand, based on the 11-quarter 2023-Q1–2025-Q3 historical sample. Apply the sole adjustment component, -13.5 thousand for softer 2025 total gross gains, giving 1,635.0. Because this is a flow series, dispersion is computed from all 11 listed quarterly values themselves: sample sigma = 40.7 thousand. The normal 80% half-width is 1.28*sigma = 1.28*40.7 = 52.1 thousand, implying 1,635 ± 52, or final bounds of 1,583 to 1,687 thousand."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level and momentum point in different directions: the series remains near 1.6 million and rebounded 70 thousand in Q3, but total gross gains eased from 7.585 million to 7.475 million. Recent Q4 strength supports an elevated anchor, while the softer 2025 labor-flow backdrop warrants a modest downward adjustment. No discrete policy or identifiable one-off mechanism justifies a larger shift.","Upside risk comes from another Q4 opening surge comparable to or stronger than 2024 and would land above the interval if the first print exceeds 1,687 thousand. Downside risk comes from broad-based establishment-formation weakness or reversal of the Q3 rebound and would land below the interval if the print is under 1,583 thousand."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Level and momentum point in different directions: the series remains near 1.6 million and rebounded 70 thousand in Q3, but total gross gains eased from 7.585 million to 7.475 million. Recent Q4 strength supports an elevated anchor, while the softer 2025 labor-flow backdrop warrants a modest downward adjustment. No discrete policy or identifiable one-off mechanism justifies a larger shift.","Prior/update/interval: A recent-Q4 persistence model uses the 2023-Q4 and 2024-Q4 average, (1,637 + 1,660) / 2 = 1,648.5 thousand, based on the 11-quarter 2023-Q1–2025-Q3 historical sample. Apply the sole adjustment component, -13.5 thousand for softer 2025 total gross gains, giving 1,635.0. Because this is a flow series, dispersion is computed from all 11 listed quarterly values themselves: sample sigma = 40.7 thousand. The normal 80% half-width is 1.28*sigma = 1.28*40.7 = 52.1 thousand, implying 1,635 ± 52, or final bounds of 1,583 to 1,687 thousand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bls-bed-opening-establishment-gross-job-gains-q4-2025\nrunLabel: Headline\nresolutionDate: 2026-07-29\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bls-ecec-private-total-compensation-hourly-cost-q2-2026.2026-07-15T21-24-37Z.bf788b00ccad07e5","runId":"run.bls-ecec-private-total-compensation-hourly-cost-q2-2026.2026-07-15T21-24-37Z.bf788b00ccad07e5","predictionId":"bls-ecec-private-total-compensation-hourly-cost-q2-2026","specId":"spec.bls-ecec-private-total-compensation-hourly-cost-q2-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 9 historical point(s) and explicit outside-view language.","evidence":["Tool result: The BLS calendar schedules Employer Costs for Employee Compensation for June 2026 for September 9, 2026 at 10:00 AM ET; it also lists the prior March 2026 release on June 12, 2026 at 10:00 AM.","The outside-view base rate is persistent quarterly growth: across the eight changes from March 2024 through March 2026, the increases were $0.16, $0.46, $0.27, $0.71, $0.27, $0.40, $0.10, and $0.45, averaging about $0.35 per quarter. The level effect starts at $46.60; momentum contributes about $0.35. Wage and benefit inflation support continued growth, while no specific one-off or policy mechanism warrants a separate adjustment."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 10 source-context item(s), activity log present.","evidence":["The target is the first-print current-dollar cost per hour for private industry workers’ total compensation in BLS ECEC Table 1, June 2026. This is the published ECEC level rather than the seasonally adjusted Employment Cost Index; later revisions do not count.","Tool call: Fetch the latest BLS ECEC Table 1 release."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the first-print current-dollar cost per hour for private industry workers’ total compensation in BLS ECEC Table 1, June 2026. This is the published ECEC level rather than the seasonally adjusted Employment Cost Index; later revisions do not count.","Tool call: Fetch the latest BLS ECEC Table 1 release."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.5, distribution present, forecast step count 1.","evidence":["Prior/update/interval: a persistence model uses the latest $46.60 level plus the $0.35 mean change from the eight-quarter historical sample, with adjustment components of $0.00 for one-offs and $0.00 for policy mechanisms, yielding $46.95. The sample standard deviation of successive changes is sigma = $0.195; 1.28*sigma = $0.250, so the realized-dispersion 80% interval is $46.95 ± $0.25 = [$46.70, $47.20].","Upside risk comes from unusually strong wage growth, benefits inflation, or a composition shift toward high-compensation jobs and would land above $47.20. Downside risk comes from weak hours-adjusted compensation growth or a composition shift toward lower-cost jobs and would land below $46.70; either outcome outside the interval would falsify the recent-change reference class."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The outside-view base rate is persistent quarterly growth: across the eight changes from March 2024 through March 2026, the increases were $0.16, $0.46, $0.27, $0.71, $0.27, $0.40, $0.10, and $0.45, averaging about $0.35 per quarter. The level effect starts at $46.60; momentum contributes about $0.35. Wage and benefit inflation support continued growth, while no specific one-off or policy mechanism warrants a separate adjustment.","Review disposition: Accepted the suggestion to state explicit $47.20 and $46.70 tail thresholds. Did not add an exact archived March 2026 release URL because none was verified in the available draft evidence; the cited live BLS Table 1 remains the source for the latest level."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The outside-view base rate is persistent quarterly growth: across the eight changes from March 2024 through March 2026, the increases were $0.16, $0.46, $0.27, $0.71, $0.27, $0.40, $0.10, and $0.45, averaging about $0.35 per quarter. The level effect starts at $46.60; momentum contributes about $0.35. Wage and benefit inflation support continued growth, while no specific one-off or policy mechanism warrants a separate adjustment.","Upside risk comes from unusually strong wage growth, benefits inflation, or a composition shift toward high-compensation jobs and would land above $47.20. Downside risk comes from weak hours-adjusted compensation growth or a composition shift toward lower-cost jobs and would land below $46.70; either outcome outside the interval would falsify the recent-change reference class."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: private-industry total compensation cost in June 2026","Prior/update/interval: a persistence model uses the latest $46.60 level plus the $0.35 mean change from the eight-quarter historical sample, with adjustment components of $0.00 for one-offs and $0.00 for policy mechanisms, yielding $46.95. The sample standard deviation of successive changes is sigma = $0.195; 1.28*sigma = $0.250, so the realized-dispersion 80% interval is $46.95 ± $0.25 = [$46.70, $47.20]."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bls-ecec-private-total-compensation-hourly-cost-q2-2026\nrunLabel: Headline\nresolutionDate: 2026-09-09\ntraceLineCount: 13\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-defense-capital-goods-inventories-june-2026.2026-07-15T19-35-18Z.4be8c0fb26da25d5","runId":"run.us-defense-capital-goods-inventories-june-2026.2026-07-15T19-35-18Z.4be8c0fb26da25d5","predictionId":"us-defense-capital-goods-inventories-june-2026","specId":"spec.us-defense-capital-goods-inventories-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Outside view/base rate: the seven-month first-print reference class from November 2025 through May 2026 is 27.738, 27.668, 27.820, 27.877, 28.088, 28.121, and 28.257 billion. Six monthly changes average +0.0865 billion and are positive in five of six months, favoring another moderate increase over pure level persistence.","Prior/update/interval: persistence-plus-drift prior using seven first-print observations from November 2025-May 2026; successive changes are -0.070, +0.152, +0.057, +0.211, +0.033, and +0.136 billion. Their mean is +0.0865 and sample sigma = 0.101 billion. The mechanical point is 28.257 + 0.0865 = 28.3435; a small +0.0065 billion discretionary adjustment for persistent long-cycle inventory accumulation gives 28.350. The normal 80% half-width is 1.28*sigma = 1.28*0.101 = 0.129 billion, rounded to 0.13, giving 28.35 ± 0.13 = [28.22, 28.48]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 7 source-context item(s), activity log present.","evidence":["The resolver is Census M3 Advance Table 2 series M3_ADV_TABLE2_DEFENSE_CAPITAL_GOODS_INVENTORY_SA: preliminary June 2026 defense capital goods total inventories, seasonally adjusted, reported in millions and converted to USD billions. The first official print alone controls; later revisions do not.","The Census economic-indicator calendar explicitly schedules the June 2026 Advance Report on Durable Goods for July 27, 2026 at 8:30 a.m. EDT, verifying the ledger resolution date rather than inferring it from monthly cadence."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is Census M3 Advance Table 2 series M3_ADV_TABLE2_DEFENSE_CAPITAL_GOODS_INVENTORY_SA: preliminary June 2026 defense capital goods total inventories, seasonally adjusted, reported in millions and converted to USD billions. The first official print alone controls; later revisions do not.","Tool call: Fetch first-print defense capital-goods inventories from the February, March, and April 2026 Census advance releases."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.26, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence-plus-drift prior using seven first-print observations from November 2025-May 2026; successive changes are -0.070, +0.152, +0.057, +0.211, +0.033, and +0.136 billion. Their mean is +0.0865 and sample sigma = 0.101 billion. The mechanical point is 28.257 + 0.0865 = 28.3435; a small +0.0065 billion discretionary adjustment for persistent long-cycle inventory accumulation gives 28.350. The normal 80% half-width is 1.28*sigma = 1.28*0.101 = 0.129 billion, rounded to 0.13, giving 28.35 ± 0.13 = [28.22, 28.48].","Upside risk comes from unusually rapid accumulation tied to aircraft, missile, ship, or communications production and would land above the interval if June adds more than about 0.22 billion. Downside risk is a drawdown, delivery-driven liquidation, or noisy seasonal adjustment; a fall of more than about 0.04 billion from May would land below the interval. Either would be outside the interval and falsify the smooth-accumulation reference class."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level is anchored at May's 28.257 billion. Momentum contributes about +0.087 billion from the mean monthly change. No identified one-off warrants a large adjustment; the policy/production mechanism is gradual accumulation in long-cycle defense manufacturing.","Review disposition: Accepted the coherence critique by replacing the incorrect rounding claim with an explicit +0.0065 billion judgmental adjustment, and clarified that the March and April historical observations are first prints rather than later revised values. The optional May-PDF addition was not used because the existing official current-release table was the source actually consulted."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level is anchored at May's 28.257 billion. Momentum contributes about +0.087 billion from the mean monthly change. No identified one-off warrants a large adjustment; the policy/production mechanism is gradual accumulation in long-cycle defense manufacturing.","Upside risk comes from unusually rapid accumulation tied to aircraft, missile, ship, or communications production and would land above the interval if June adds more than about 0.22 billion. Downside risk is a drawdown, delivery-driven liquidation, or noisy seasonal adjustment; a fall of more than about 0.04 billion from May would land below the interval. Either would be outside the interval and falsify the smooth-accumulation reference class."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["June 2026 defense capital-goods inventories forecast","Prior/update/interval: persistence-plus-drift prior using seven first-print observations from November 2025-May 2026; successive changes are -0.070, +0.152, +0.057, +0.211, +0.033, and +0.136 billion. Their mean is +0.0865 and sample sigma = 0.101 billion. The mechanical point is 28.257 + 0.0865 = 28.3435; a small +0.0065 billion discretionary adjustment for persistent long-cycle inventory accumulation gives 28.350. The normal 80% half-width is 1.28*sigma = 1.28*0.101 = 0.129 billion, rounded to 0.13, giving 28.35 ± 0.13 = [28.22, 28.48]."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-defense-capital-goods-inventories-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-27\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bea-pce-price-index-monthly-change-june-2026.2026-07-15T19-31-29Z.b6bf3d3647c53847","runId":"run.bea-pce-price-index-monthly-change-june-2026.2026-07-15T19-31-29Z.b6bf3d3647c53847","predictionId":"bea-pce-price-index-monthly-change-june-2026","specId":"spec.bea-pce-price-index-monthly-change-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 7 historical point(s) and explicit outside-view language.","evidence":["The reference class/base rate is the five first-print monthly headline PCE observations for January-May 2026: 0.3%, 0.4%, 0.7%, 0.4%, and 0.4%, averaging 0.44%. This establishes an elevated persistence prior before June-specific information.","Prior/update/interval: persistence model prior = 0.44%, using the January-May first-print historical sample [0.3, 0.4, 0.7, 0.4, 0.4]. Adjustment components are -0.40 percentage point for the June energy reversal and -0.14 point for flat core momentum plus PCE-weight translation, giving 0.44 - 0.40 - 0.14 = -0.10%. For this change series, dispersion uses the values themselves: sample sigma = sqrt(((0.3-0.44)^2+(0.4-0.44)^2+(0.7-0.44)^2+(0.4-0.44)^2+(0.4-0.44)^2)/4) = 0.152, rounded sigma = 0.15. Because five observations do not capture CPI-to-PCE translation and volatile-energy nowcast error, add an explicit 0.08-point uncertainty component in quadrature: combined sigma = sqrt(0.15^2+0.08^2) = 0.17. The 80% half-width is 1.28*sigma = 1.28*0.17 = 0.218, so -0.10 ± 0.218 gives final implied bounds of -0.318% and 0.118%, rounded to [-0.32%, 0.12%]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 7 source-context item(s), activity log present.","evidence":["The target is the first-published, seasonally adjusted one-month change in BEA's headline PCE price index, series PCEPI, from NIPA table 2.8.7—not core PCE or a year-over-year rate. The ledger has concrete resolver defects: BEA's official calendar schedules this release for July 30, 2026, not the registered July 29 resolutionDate, while the mandated ALFRED vintage URL is dated June 25 and therefore cannot contain June's first print. This forecast remains tied to the registered target fields pending correction or formal waiver.","Tool call: Fetched BLS June 2026 CPI release as contemporaneous public-price evidence."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the first-published, seasonally adjusted one-month change in BEA's headline PCE price index, series PCEPI, from NIPA table 2.8.7—not core PCE or a year-over-year rate. The ledger has concrete resolver defects: BEA's official calendar schedules this release for July 30, 2026, not the registered July 29 resolutionDate, while the mandated ALFRED vintage URL is dated June 25 and therefore cannot contain June's first print. This forecast remains tied to the registered target fields pending correction or formal waiver.","Tool call: Fetched BEA January and February 2026 Personal Income and Outlays releases."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.44, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence model prior = 0.44%, using the January-May first-print historical sample [0.3, 0.4, 0.7, 0.4, 0.4]. Adjustment components are -0.40 percentage point for the June energy reversal and -0.14 point for flat core momentum plus PCE-weight translation, giving 0.44 - 0.40 - 0.14 = -0.10%. For this change series, dispersion uses the values themselves: sample sigma = sqrt(((0.3-0.44)^2+(0.4-0.44)^2+(0.7-0.44)^2+(0.4-0.44)^2+(0.4-0.44)^2)/4) = 0.152, rounded sigma = 0.15. Because five observations do not capture CPI-to-PCE translation and volatile-energy nowcast error, add an explicit 0.08-point uncertainty component in quadrature: combined sigma = sqrt(0.15^2+0.08^2) = 0.17. The 80% half-width is 1.28*sigma = 1.28*0.17 = 0.218, so -0.10 ± 0.218 gives final implied bounds of -0.318% and 0.118%, rounded to [-0.32%, 0.12%].","Upside risk: stronger PCE-specific services or portfolio-management prices could produce 0.2% or more, above the interval. Downside risk: greater pass-through from gasoline and other energy declines could produce -0.4% or less, below the interval. Either outcome would land outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Inside-view update: June CPI momentum changed sharply. The 5.7% energy decline pulls headline inflation down, while flat core CPI indicates broad monthly disinflation. PCE's lower gasoline weight should make headline PCE less negative than CPI, so the -0.40 and -0.14 percentage-point adjustments are judgmental decompositions of the observed energy shock and incomplete CPI-to-PCE pass-through rather than a mechanical copy of the -0.4% CPI print.","Prior/update/interval: persistence model prior = 0.44%, using the January-May first-print historical sample [0.3, 0.4, 0.7, 0.4, 0.4]. Adjustment components are -0.40 percentage point for the June energy reversal and -0.14 point for flat core momentum plus PCE-weight translation, giving 0.44 - 0.40 - 0.14 = -0.10%. For this change series, dispersion uses the values themselves: sample sigma = sqrt(((0.3-0.44)^2+(0.4-0.44)^2+(0.7-0.44)^2+(0.4-0.44)^2+(0.4-0.44)^2)/4) = 0.152, rounded sigma = 0.15. Because five observations do not capture CPI-to-PCE translation and volatile-energy nowcast error, add an explicit 0.08-point uncertainty component in quadrature: combined sigma = sqrt(0.15^2+0.08^2) = 0.17. The 80% half-width is 1.28*sigma = 1.28*0.17 = 0.218, so -0.10 ± 0.218 gives final implied bounds of -0.318% and 0.118%, rounded to [-0.32%, 0.12%]."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence model prior = 0.44%, using the January-May first-print historical sample [0.3, 0.4, 0.7, 0.4, 0.4]. Adjustment components are -0.40 percentage point for the June energy reversal and -0.14 point for flat core momentum plus PCE-weight translation, giving 0.44 - 0.40 - 0.14 = -0.10%. For this change series, dispersion uses the values themselves: sample sigma = sqrt(((0.3-0.44)^2+(0.4-0.44)^2+(0.7-0.44)^2+(0.4-0.44)^2+(0.4-0.44)^2)/4) = 0.152, rounded sigma = 0.15. Because five observations do not capture CPI-to-PCE translation and volatile-energy nowcast error, add an explicit 0.08-point uncertainty component in quadrature: combined sigma = sqrt(0.15^2+0.08^2) = 0.17. The 80% half-width is 1.28*sigma = 1.28*0.17 = 0.218, so -0.10 ± 0.218 gives final implied bounds of -0.318% and 0.118%, rounded to [-0.32%, 0.12%].","Upside risk: stronger PCE-specific services or portfolio-management prices could produce 0.2% or more, above the interval. Downside risk: greater pass-through from gasoline and other energy declines could produce -0.4% or less, below the interval. Either outcome would land outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["June 2026 headline PCE price forecast","The target is the first-published, seasonally adjusted one-month change in BEA's headline PCE price index, series PCEPI, from NIPA table 2.8.7—not core PCE or a year-over-year rate. The ledger has concrete resolver defects: BEA's official calendar schedules this release for July 30, 2026, not the registered July 29 resolutionDate, while the mandated ALFRED vintage URL is dated June 25 and therefore cannot contain June's first print. This forecast remains tied to the registered target fields pending correction or formal waiver."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bea-pce-price-index-monthly-change-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-29\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bea-personal-current-taxes-level-june-2026.2026-07-15T19-33-28Z.2bd9dc9ab83e08d6","runId":"run.bea-personal-current-taxes-level-june-2026.2026-07-15T19-33-28Z.2bd9dc9ab83e08d6","predictionId":"bea-personal-current-taxes-level-june-2026","specId":"spec.bea-personal-current-taxes-level-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The reference class and base rate are the four successive changes from January through May 2026: 0.6, 14.2, 18.4, and 16.8 billion dollars. Their mean is 12.5, indicating positive recent momentum after the nearly flat January-February move.","Prior/update/interval: The model is a one-month persistence-plus-mean-change prior using the January-May 2026 historical sample. Starting from 3264.7, the base-rate increment is (0.6 + 14.2 + 18.4 + 16.8)/4 = 12.5. Level effect: 3264.7. Momentum effect: +12.5. One-off adjustment: 0.0 because no June-specific tax-policy discontinuity was identified. Policy-mechanism adjustment: 0.0. Point = 3264.7 + 12.5 = 3277.2. The sample standard deviation of those successive changes is sigma = sqrt(197.8/3) = 8.12. The normal 80% half-width is 1.28*sigma = 1.28*8.12 = 10.39, giving 3277.2 ± 10.39, or 3266.8 to 3287.6 after rounding. This relatively narrow interval reflects a short sample of four recent monthly changes."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The target is BEA series W055RC1: monthly personal current taxes, seasonally adjusted at an annual rate, billions of dollars, first print for June 2026. The registered binding names Personal Income and Outlays Table 1, while the detailed series mirror places W055RC1 in Table 2.6.","Tool call: Fetched the latest W055RC1 monthly reference-class observations from the BEA-sourced series and detailed table mirror."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is BEA series W055RC1: monthly personal current taxes, seasonally adjusted at an annual rate, billions of dollars, first print for June 2026. The registered binding names Personal Income and Outlays Table 1, while the detailed series mirror places W055RC1 in Table 2.6.","Tool call: Checked the BEA 2026 release schedule and the May Personal Income and Outlays release for the announced June 2026 publication date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 20.8, distribution present, forecast step count 1.","evidence":["The target is BEA series W055RC1: monthly personal current taxes, seasonally adjusted at an annual rate, billions of dollars, first print for June 2026. The registered binding names Personal Income and Outlays Table 1, while the detailed series mirror places W055RC1 in Table 2.6.","Tool call: Fetched the latest W055RC1 monthly reference-class observations from the BEA-sourced series and detailed table mirror."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The reference class and base rate are the four successive changes from January through May 2026: 0.6, 14.2, 18.4, and 16.8 billion dollars. Their mean is 12.5, indicating positive recent momentum after the nearly flat January-February move.","Prior/update/interval: The model is a one-month persistence-plus-mean-change prior using the January-May 2026 historical sample. Starting from 3264.7, the base-rate increment is (0.6 + 14.2 + 18.4 + 16.8)/4 = 12.5. Level effect: 3264.7. Momentum effect: +12.5. One-off adjustment: 0.0 because no June-specific tax-policy discontinuity was identified. Policy-mechanism adjustment: 0.0. Point = 3264.7 + 12.5 = 3277.2. The sample standard deviation of those successive changes is sigma = sqrt(197.8/3) = 8.12. The normal 80% half-width is 1.28*sigma = 1.28*8.12 = 10.39, giving 3277.2 ± 10.39, or 3266.8 to 3287.6 after rounding. This relatively narrow interval reflects a short sample of four recent monthly changes."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Upside risk from unusually strong wage withholding, capital-gains-related estimated payments, or stronger taxable income would require a June increase above about 22.9 billion dollars to land above the interval. Downside risk from refund timing, weaker withholding, or an adverse first-print seasonal adjustment would require an increase below about 2.1 billion dollars to land below the interval. A tax-policy or payment-timing discontinuity could place the result outside the interval.","Resolver discrepancy: the registered expected window ends July 29 and its fixed ALFRED vintage is June 25, but BEA's official schedule and release notice both give July 30. The June 25 vintage cannot contain the June first print. The canonical July 29 date and registered resolver fields are preserved pending correction through the target-registration process."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["June 2026 personal current taxes forecast","Prior/update/interval: The model is a one-month persistence-plus-mean-change prior using the January-May 2026 historical sample. Starting from 3264.7, the base-rate increment is (0.6 + 14.2 + 18.4 + 16.8)/4 = 12.5. Level effect: 3264.7. Momentum effect: +12.5. One-off adjustment: 0.0 because no June-specific tax-policy discontinuity was identified. Policy-mechanism adjustment: 0.0. Point = 3264.7 + 12.5 = 3277.2. The sample standard deviation of those successive changes is sigma = sqrt(197.8/3) = 8.12. The normal 80% half-width is 1.28*sigma = 1.28*8.12 = 10.39, giving 3277.2 ± 10.39, or 3266.8 to 3287.6 after rounding. This relatively narrow interval reflects a short sample of four recent monthly changes."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bea-personal-current-taxes-level-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-29\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bea-government-social-benefits-medicaid-june-2026.2026-07-15T16-32-50Z.1e5d1dd693eb12d2","runId":"run.bea-government-social-benefits-medicaid-june-2026.2026-07-15T16-32-50Z.1e5d1dd693eb12d2","predictionId":"bea-government-social-benefits-medicaid-june-2026","specId":"spec.bea-government-social-benefits-medicaid-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Prior/update/interval: base rate/reference class is a persistence-plus-June-change model using the same W729RC1 SAAR variant; recent May-to-June changes were +11.5 in 2025, +4.5 in 2024, -9.8 in 2023, +0.9 in 2022, and +6.0 in 2021, so I use a roughly +4.2 billion June base lift from May. Current-release adjustment subtracts 2.0 for 2026 downward momentum from Feb 1062.0 to May 1052.2 and adds 0.1 for the still-high level/policy baseline, giving 1052.2 + 4.2 - 2.0 + 0.1 = 1054.5. For the 80% interval, the 2024-01 through 2026-05 successive monthly changes have sigma = 8.35 billion; 1.28*sigma = 10.69, so 1054.5 +/- 10.7 gives 1043.8 to 1065.2.","Review disposition: accepted the resolver-coherence critique by using the ledger Table 1 wording in public-facing resolver fields while explicitly retaining the registered ALFRED URL and flagging the apparent date/vintage discrepancy; kept the prior/update/interval calculation unchanged because it already used the correct W729RC1 variant and stated sigma arithmetic."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: the target is BEA NIPA monthly series W729RC1, Medicaid under government social benefits to persons, in billions of dollars at a seasonally adjusted annual rate. I keep the registered slug, dataPointId, and ALFRED mirror URL. The BEA release schedule lists Personal Income and Outlays, June 2026 for July 30, 2026 at 8:30 AM; the registered ledger mirror URL uses ALFRED vintage_date=2026-06-25 and an expected window ending 2026-07-29, which appears to be a ledger-source discrepancy rather than evidence about the June value.","Tool result: Fetched W729RC1 values: May 2026 = 1052.2, Apr 2026 = 1055.7, Mar 2026 = 1061.1, Feb 2026 = 1062.0, Jan 2026 = 1057.4, units billions of dollars SAAR, monthly."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["BEA Medicaid Benefits June 2026 First Print","Framing and exact resolver: the target is BEA NIPA monthly series W729RC1, Medicaid under government social benefits to persons, in billions of dollars at a seasonally adjusted annual rate. I keep the registered slug, dataPointId, and ALFRED mirror URL. The BEA release schedule lists Personal Income and Outlays, June 2026 for July 30, 2026 at 8:30 AM; the registered ledger mirror URL uses ALFRED vintage_date=2026-06-25 and an expected window ending 2026-07-29, which appears to be a ledger-source discrepancy rather than evidence about the June value."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 21.4, distribution present, forecast step count 1.","evidence":["Prior/update/interval: base rate/reference class is a persistence-plus-June-change model using the same W729RC1 SAAR variant; recent May-to-June changes were +11.5 in 2025, +4.5 in 2024, -9.8 in 2023, +0.9 in 2022, and +6.0 in 2021, so I use a roughly +4.2 billion June base lift from May. Current-release adjustment subtracts 2.0 for 2026 downward momentum from Feb 1062.0 to May 1052.2 and adds 0.1 for the still-high level/policy baseline, giving 1052.2 + 4.2 - 2.0 + 0.1 = 1054.5. For the 80% interval, the 2024-01 through 2026-05 successive monthly changes have sigma = 8.35 billion; 1.28*sigma = 10.69, so 1054.5 +/- 10.7 gives 1043.8 to 1065.2.","Counter-considerations: upside risk is a renewed catch-up or accounting jump like mid-2025 that would land above the interval if June prints above 1065.2. Downside risk is a continuation of the spring 2026 slide or a redetermination-related drop like June 2023 that would land below the interval if June prints below 1043.8. Values outside the interval would most likely reflect an administrative timing change, not ordinary month-to-month drift."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: base rate/reference class is a persistence-plus-June-change model using the same W729RC1 SAAR variant; recent May-to-June changes were +11.5 in 2025, +4.5 in 2024, -9.8 in 2023, +0.9 in 2022, and +6.0 in 2021, so I use a roughly +4.2 billion June base lift from May. Current-release adjustment subtracts 2.0 for 2026 downward momentum from Feb 1062.0 to May 1052.2 and adds 0.1 for the still-high level/policy baseline, giving 1052.2 + 4.2 - 2.0 + 0.1 = 1054.5. For the 80% interval, the 2024-01 through 2026-05 successive monthly changes have sigma = 8.35 billion; 1.28*sigma = 10.69, so 1054.5 +/- 10.7 gives 1043.8 to 1065.2.","Review disposition: accepted the resolver-coherence critique by using the ledger Table 1 wording in public-facing resolver fields while explicitly retaining the registered ALFRED URL and flagging the apparent date/vintage discrepancy; kept the prior/update/interval calculation unchanged because it already used the correct W729RC1 variant and stated sigma arithmetic."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-considerations: upside risk is a renewed catch-up or accounting jump like mid-2025 that would land above the interval if June prints above 1065.2. Downside risk is a continuation of the spring 2026 slide or a redetermination-related drop like June 2023 that would land below the interval if June prints below 1043.8. Values outside the interval would most likely reflect an administrative timing change, not ordinary month-to-month drift."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Framing and exact resolver: the target is BEA NIPA monthly series W729RC1, Medicaid under government social benefits to persons, in billions of dollars at a seasonally adjusted annual rate. I keep the registered slug, dataPointId, and ALFRED mirror URL. The BEA release schedule lists Personal Income and Outlays, June 2026 for July 30, 2026 at 8:30 AM; the registered ledger mirror URL uses ALFRED vintage_date=2026-06-25 and an expected window ending 2026-07-29, which appears to be a ledger-source discrepancy rather than evidence about the June value.","Prior/update/interval: base rate/reference class is a persistence-plus-June-change model using the same W729RC1 SAAR variant; recent May-to-June changes were +11.5 in 2025, +4.5 in 2024, -9.8 in 2023, +0.9 in 2022, and +6.0 in 2021, so I use a roughly +4.2 billion June base lift from May. Current-release adjustment subtracts 2.0 for 2026 downward momentum from Feb 1062.0 to May 1052.2 and adds 0.1 for the still-high level/policy baseline, giving 1052.2 + 4.2 - 2.0 + 0.1 = 1054.5. For the 80% interval, the 2024-01 through 2026-05 successive monthly changes have sigma = 8.35 billion; 1.28*sigma = 10.69, so 1054.5 +/- 10.7 gives 1043.8 to 1065.2."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bea-government-social-benefits-medicaid-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-30\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bea-government-social-benefits-medicare-june-2026.2026-07-15T16-35-10Z.fc1812e23304018f","runId":"run.bea-government-social-benefits-medicare-june-2026.2026-07-15T16-35-10Z.fc1812e23304018f","predictionId":"bea-government-social-benefits-medicare-june-2026","specId":"spec.bea-government-social-benefits-medicare-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Framing and exact resolver: the target is BEA/FRED series W824RC1, personal current transfer receipts: government social benefits to persons: Medicare, monthly, billions of dollars, seasonally adjusted annual rate. I use the same SAAR billions variant for every historical anchor and forecast value.","Reference class/base rate: for this smooth level series, the useful base rate is the recent successive monthly change in the same W824RC1 SAAR billions series. The visible Aug 2025-May 2026 run is almost linear, with changes of about +10.3 to +10.7 billion per month."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: the target is BEA/FRED series W824RC1, personal current transfer receipts: government social benefits to persons: Medicare, monthly, billions of dollars, seasonally adjusted annual rate. I use the same SAAR billions variant for every historical anchor and forecast value.","Tool call: Checked current public W824RC1 series display for latest observations and release metadata."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast for BEA Medicare government social benefits, June 2026 first print","Tool call: Checked the BEA release schedule for Personal Income and Outlays, June 2026."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 8, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = latest May 2026 level plus recent mean monthly change; historical sample = fetched Aug 2025-May 2026 visible W824RC1 values; adjustment components = level 1332.0, momentum +10.38, one-off/policy-mechanism 0.0 because no fetched evidence of a June discontinuity; point = 1332.0 + 10.38 = 1342.38, rounded to 1342.3. For fetched successive changes 10.7, 10.6, 10.6, 10.6, 10.5, 10.4, 10.4, 10.3, 10.3, sigma = 0.13, so 1.28*sigma = 0.17. I widen the 80% half-width to 4.0 because the displayed recent run-rate is policy-smoothed and materially understates first-print/original-vintage and release-mechanics risk for a benefits accrual series; final implied bounds are 1342.3 - 4.0 = 1338.3 and 1342.3 + 4.0 = 1346.3.","Upside risk: a stronger Medicare accrual month, updated seasonal factors, or a June-specific trust-fund/payment adjustment would land above the interval if the first print exceeds 1346.3. Downside risk: a monthly accrual pause, offsetting seasonal revision, or weaker-than-trend benefits booking would land below the interval if the first print is under 1338.3."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior = latest May 2026 level plus recent mean monthly change; historical sample = fetched Aug 2025-May 2026 visible W824RC1 values; adjustment components = level 1332.0, momentum +10.38, one-off/policy-mechanism 0.0 because no fetched evidence of a June discontinuity; point = 1332.0 + 10.38 = 1342.38, rounded to 1342.3. For fetched successive changes 10.7, 10.6, 10.6, 10.6, 10.5, 10.4, 10.4, 10.3, 10.3, sigma = 0.13, so 1.28*sigma = 0.17. I widen the 80% half-width to 4.0 because the displayed recent run-rate is policy-smoothed and materially understates first-print/original-vintage and release-mechanics risk for a benefits accrual series; final implied bounds are 1342.3 - 4.0 = 1338.3 and 1342.3 + 4.0 = 1346.3.","Review disposition: accepted the reviewer's resolver-clarity framing that the forecast is coherent while preserving the explicit catalog-contract discrepancy; rejected adding FRED next-release metadata because it was not included in the drafted public evidence used for this submission."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence prior = latest May 2026 level plus recent mean monthly change; historical sample = fetched Aug 2025-May 2026 visible W824RC1 values; adjustment components = level 1332.0, momentum +10.38, one-off/policy-mechanism 0.0 because no fetched evidence of a June discontinuity; point = 1332.0 + 10.38 = 1342.38, rounded to 1342.3. For fetched successive changes 10.7, 10.6, 10.6, 10.6, 10.5, 10.4, 10.4, 10.3, 10.3, sigma = 0.13, so 1.28*sigma = 0.17. I widen the 80% half-width to 4.0 because the displayed recent run-rate is policy-smoothed and materially understates first-print/original-vintage and release-mechanics risk for a benefits accrual series; final implied bounds are 1342.3 - 4.0 = 1338.3 and 1342.3 + 4.0 = 1346.3.","Upside risk: a stronger Medicare accrual month, updated seasonal factors, or a June-specific trust-fund/payment adjustment would land above the interval if the first print exceeds 1346.3. Downside risk: a monthly accrual pause, offsetting seasonal revision, or weaker-than-trend benefits booking would land below the interval if the first print is under 1338.3."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for BEA Medicare government social benefits, June 2026 first print","Framing and exact resolver: the target is BEA/FRED series W824RC1, personal current transfer receipts: government social benefits to persons: Medicare, monthly, billions of dollars, seasonally adjusted annual rate. I use the same SAAR billions variant for every historical anchor and forecast value."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bea-government-social-benefits-medicare-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-30\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bea-pce-core-mom-june-2026.2026-07-15T16-42-05Z.e5f49abe53c47730","runId":"run.bea-pce-core-mom-june-2026.2026-07-15T16-42-05Z.e5f49abe53c47730","predictionId":"bea-pce-core-mom-june-2026","specId":"spec.bea-pce-core-mom-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Framing and exact resolver: the target is the BEA first-print seasonally adjusted PCE price index excluding food and energy for June 2026, not headline PCE, not market-based core PCE, and not a revised vintage. I kept the catalog slug and dataPointId. I found ledger discrepancies: the provided ALFRED resolution URL uses vintage_date=2026-06-25 and the sourceBinding expectedReleaseWindow ends 2026-07-29, while BEA's official calendar and May release both show the June 2026 Personal Income and Outlays release on July 30, 2026. The forecast remains tied to this target and states the discrepancy rather than changing the catalog identity.","Reference class / base rate: the same-variant PCEPILFE recent monthly growth rates from the fetched index levels are about 0.394 percent in February, 0.296 percent in March, 0.251 percent in April, and 0.320 percent in May, for a short-run base rate near 0.315 percent. That is the persistence prior before mapping June CPI and PPI inputs into core PCE."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["Framing and exact resolver: the target is the BEA first-print seasonally adjusted PCE price index excluding food and energy for June 2026, not headline PCE, not market-based core PCE, and not a revised vintage. I kept the catalog slug and dataPointId. I found ledger discrepancies: the provided ALFRED resolution URL uses vintage_date=2026-06-25 and the sourceBinding expectedReleaseWindow ends 2026-07-29, while BEA's official calendar and May release both show the June 2026 Personal Income and Outlays release on July 30, 2026. The forecast remains tied to this target and states the discrepancy rather than changing the catalog identity.","Tool call: Fetched June 2026 BLS CPI details used as the main consumer-price input into the PCE nowcast."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: the target is the BEA first-print seasonally adjusted PCE price index excluding food and energy for June 2026, not headline PCE, not market-based core PCE, and not a revised vintage. I kept the catalog slug and dataPointId. I found ledger discrepancies: the provided ALFRED resolution URL uses vintage_date=2026-06-25 and the sourceBinding expectedReleaseWindow ends 2026-07-29, while BEA's official calendar and May release both show the June 2026 Personal Income and Outlays release on July 30, 2026. The forecast remains tied to this target and states the discrepancy rather than changing the catalog identity.","Tool call: Checked BEA release schedule and the May 2026 Personal Income and Outlays next-release notice for the June 2026 PCE release date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.22, distribution present, forecast step count 1.","evidence":["Tool call: Fetched June 2026 BLS CPI details used as the main consumer-price input into the PCE nowcast.","Tool call: Fetched June 2026 BLS PPI details for PCE-relevant services and goods pipeline inputs."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior = mean(Feb-May derived PCEPILFE MoM) = (0.394 + 0.296 + 0.251 + 0.320)/4 = 0.315 percent. Adjustments: June core CPI flat rather than May's 0.2 percent subtracts 0.09 pp; June PPI final demand less foods, energy, and trade services at 0.1 percent and services at 0.2 percent subtracts 0.03 pp versus May's firmer inputs; residual PCE-specific services, portfolio/financial fees, and healthcare add back 0.00 to 0.02 pp. Final point = 0.315 - 0.09 - 0.03 - 0.005 = 0.19 percent. For the interval, using the four fetched recent PCEPILFE monthly changes, sigma = 0.060 percentage points; 1.28*sigma = 0.077 pp. I widen to about 0.11 pp, or 1.45x the reference half-width, because CPI/PPI-to-PCE mapping and financial-services components are not fully pinned down before BEA. This gives 0.19 +/- 0.11 = [0.08, 0.30].","Review disposition: accepted the reviewer suggestion to make the ALFRED vintage_date=2026-06-25 discrepancy and the 2026-07-29 expectedReleaseWindow mismatch more explicit, while retaining the target identity, resolver URL, point estimate, and interval because the critique did not identify a forecast-calibration issue."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-considerations: upside risk would come from PCE-weighted financial services, insurance, or healthcare prices staying closer to May's firm pulse despite flat core CPI, which would land above the interval if core PCE prints above 0.30 percent. Downside risk would come from the June flat core CPI pass-through dominating PCE services and goods, plus weaker portfolio-management fees, which would land below the interval if the first print is below 0.08 percent. An outside the interval outcome is most plausible if BEA-specific source-data adjustments or a large services component diverges sharply from CPI/PPI."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for June 2026 Core PCE MoM","Framing and exact resolver: the target is the BEA first-print seasonally adjusted PCE price index excluding food and energy for June 2026, not headline PCE, not market-based core PCE, and not a revised vintage. I kept the catalog slug and dataPointId. I found ledger discrepancies: the provided ALFRED resolution URL uses vintage_date=2026-06-25 and the sourceBinding expectedReleaseWindow ends 2026-07-29, while BEA's official calendar and May release both show the June 2026 Personal Income and Outlays release on July 30, 2026. The forecast remains tied to this target and states the discrepancy rather than changing the catalog identity."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bea-pce-core-mom-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-30\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bea-government-social-benefits-social-security-june-2026.2026-07-15T16-38-49Z.5f7d8c80b44d44cd","runId":"run.bea-government-social-benefits-social-security-june-2026.2026-07-15T16-38-49Z.5f7d8c80b44d44cd","predictionId":"bea-government-social-benefits-social-security-june-2026","specId":"spec.bea-government-social-benefits-social-security-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool call: SSA public benefit-mechanism lookup for 2026 Social Security payment baseline","Reference class and base rate: for a monthly SA annual-rate Social Security benefits level after the January COLA reset, the best base rate is persistence plus recent monthly drift. The reference class is recent non-January W823RC1 monthly level changes, where the series usually moves by a few billion annualized per month unless a legislated retroactive payment, unusual lump-sum processing, or classification issue hits."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: the target is BEA Personal Income and Outlays Table 1 series W823RC1, government social benefits to persons: Social Security, seasonally adjusted annual rate in usd_billions for observation month 2026-06. I am using the same SA annual-rate variant for anchors and forecast.","Resolver discrepancy: the registered ALFRED URL has vintage_date=2026-06-25, while the BEA June 2026 Personal Income and Outlays first print is scheduled for 2026-07-31. I keep the registered slug, dataPointId, and source URL as binding, and I do not imply that a later ALFRED vintage will be used unless the ledger is corrected."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast for BEA Social Security Benefits, June 2026 First Print","Resolver discrepancy: the registered ALFRED URL has vintage_date=2026-06-25, while the BEA June 2026 Personal Income and Outlays first print is scheduled for 2026-07-31. I keep the registered slug, dataPointId, and source URL as binding, and I do not imply that a later ALFRED vintage will be used unless the ledger is corrected."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 9, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior starts from May 2026 W823RC1 = 1654.5, with the 2026 COLA already embedded in that anchor. Recent post-COLA monthly changes were approximately +2.4, +3.1, +2.4, and +2.9, so I apply a +2.8 June drift for point = 1654.5 + 2.8 = 1657.3. For uncertainty, sigma = 3.5 usd_billions is a judgmental allowance above the very low four-month drift dispersion, sized to cover wider recent first-print monthly volatility and possible SA/processing noise. The 80 percent half-width is about 1.28*sigma = 1.28*3.5 = 4.48, rounded to 4.5. Final 80 percent interval is 1657.3 - 4.5 = 1652.8 to 1657.3 + 4.5 = 1661.8.","Counter-considerations: upside risk is an unusual June lump-sum or retroactive Social Security benefit-processing flow in W823RC1, or a stronger beneficiary/payment-count surprise, that would land above the interval. Downside risk is a weak first-print beneficiary/payment count, seasonal-adjustment behavior that trims the June annual-rate value, or reversal of prior elevated payments that would land below the interval. A genuine one-off first-vintage processing change is the outside the interval scenario most likely to falsify this persistence forecast."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Policy/mechanism adjustment: the January 2026 COLA step is already included in the May anchor, so June should mainly reflect beneficiary-count growth, benefit recomputation, mortality/entry churn, and routine seasonal-adjustment mechanics. I did not add a separate policy shock because I found no target-specific public evidence of a June-only Social Security payment expansion."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence prior starts from May 2026 W823RC1 = 1654.5, with the 2026 COLA already embedded in that anchor. Recent post-COLA monthly changes were approximately +2.4, +3.1, +2.4, and +2.9, so I apply a +2.8 June drift for point = 1654.5 + 2.8 = 1657.3. For uncertainty, sigma = 3.5 usd_billions is a judgmental allowance above the very low four-month drift dispersion, sized to cover wider recent first-print monthly volatility and possible SA/processing noise. The 80 percent half-width is about 1.28*sigma = 1.28*3.5 = 4.48, rounded to 4.5. Final 80 percent interval is 1657.3 - 4.5 = 1652.8 to 1657.3 + 4.5 = 1661.8.","Counter-considerations: upside risk is an unusual June lump-sum or retroactive Social Security benefit-processing flow in W823RC1, or a stronger beneficiary/payment-count surprise, that would land above the interval. Downside risk is a weak first-print beneficiary/payment count, seasonal-adjustment behavior that trims the June annual-rate value, or reversal of prior elevated payments that would land below the interval. A genuine one-off first-vintage processing change is the outside the interval scenario most likely to falsify this persistence forecast."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for BEA Social Security Benefits, June 2026 First Print","Framing and exact resolver: the target is BEA Personal Income and Outlays Table 1 series W823RC1, government social benefits to persons: Social Security, seasonally adjusted annual rate in usd_billions for observation month 2026-06. I am using the same SA annual-rate variant for anchors and forecast."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bea-government-social-benefits-social-security-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-31\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.uk-claimant-count-june-2026.2026-07-11T18-18-51Z.f57c0f135296dbbf","runId":"run.uk-claimant-count-june-2026.2026-07-11T18-18-51Z.f57c0f135296dbbf","predictionId":"uk-claimant-count-june-2026","specId":"spec.uk-claimant-count-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The recent reference class is the 16 monthly BCJD changes from January 2025 through May 2026: 0.3, -1.3, -11.5, -2.7, -5.0, -26.5, -5.5, -3.7, -1.7, -4.1, -2.5, -0.1, 17.1, 5.0, 8.2, and 31.3 thousand. Its base rate is close to persistence overall, but the last four changes are all positive.","Level: May starts at 1711.9 thousand. Momentum: the recent three-month median change is 8.2 thousand. One-off: May's 31.3-thousand jump is unlikely to repeat fully. Policy/mechanism: claimant records can shift as work-capability assessments conclude, while low vacancies and weak payroll growth modestly favor a further rise."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The resolver is ONS series BCJD in table CLA01: UK people, seasonally adjusted, thousands. The target is the June 2026 first print, so later administrative revisions do not count.","Tool call: Fetched the latest observations from the ONS BCJD time-series page."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["UK claimant count, June 2026 first print","The resolver is ONS series BCJD in table CLA01: UK people, seasonally adjusted, thousands. The target is the June 2026 first print, so later administrative revisions do not count."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 31.8, distribution present, forecast step count 1.","evidence":["Prior/update/interval: The model is a persistence prior at 1711.9 using the 16-change historical sample. Add 8.2 for recent median momentum and 4.9 for weakening labour-demand and administrative-mechanism effects, giving 1711.9 + 8.2 + 4.9 = 1725.0. The sample standard deviation of those successive changes is sigma = 12.4 thousand; the normal 80% half-width is 1.28*sigma = 1.28*12.4 = 15.9, implying 1725.0 - 15.9 = 1709.1 and 1725.0 + 15.9 = 1740.9.","Upside risk comes from another May-sized administrative inflow or sharper layoffs and would land above the interval. Downside risk comes from reversal of May's provisional increase or faster completion of work-capability assessments and could land below the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level: May starts at 1711.9 thousand. Momentum: the recent three-month median change is 8.2 thousand. One-off: May's 31.3-thousand jump is unlikely to repeat fully. Policy/mechanism: claimant records can shift as work-capability assessments conclude, while low vacancies and weak payroll growth modestly favor a further rise.","Prior/update/interval: The model is a persistence prior at 1711.9 using the 16-change historical sample. Add 8.2 for recent median momentum and 4.9 for weakening labour-demand and administrative-mechanism effects, giving 1711.9 + 8.2 + 4.9 = 1725.0. The sample standard deviation of those successive changes is sigma = 12.4 thousand; the normal 80% half-width is 1.28*sigma = 1.28*12.4 = 15.9, implying 1725.0 - 15.9 = 1709.1 and 1725.0 + 15.9 = 1740.9."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The recent reference class is the 16 monthly BCJD changes from January 2025 through May 2026: 0.3, -1.3, -11.5, -2.7, -5.0, -26.5, -5.5, -3.7, -1.7, -4.1, -2.5, -0.1, 17.1, 5.0, 8.2, and 31.3 thousand. Its base rate is close to persistence overall, but the last four changes are all positive.","Upside risk comes from another May-sized administrative inflow or sharper layoffs and would land above the interval. Downside risk comes from reversal of May's provisional increase or faster completion of work-capability assessments and could land below the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: The model is a persistence prior at 1711.9 using the 16-change historical sample. Add 8.2 for recent median momentum and 4.9 for weakening labour-demand and administrative-mechanism effects, giving 1711.9 + 8.2 + 4.9 = 1725.0. The sample standard deviation of those successive changes is sigma = 12.4 thousand; the normal 80% half-width is 1.28*sigma = 1.28*12.4 = 15.9, implying 1725.0 - 15.9 = 1709.1 and 1725.0 + 15.9 = 1740.9.","Upside risk comes from another May-sized administrative inflow or sharper layoffs and would land above the interval. Downside risk comes from reversal of May's provisional increase or faster completion of work-capability assessments and could land below the interval."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: uk-claimant-count-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-14\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.euro-area-construction-production-index-may-2026.2026-07-11T18-17-27Z.c1758eaa530d9c98","runId":"run.euro-area-construction-production-index-may-2026.2026-07-11T18-17-27Z.c1758eaa530d9c98","predictionId":"euro-area-construction-production-index-may-2026","specId":"spec.euro-area-construction-production-index-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["The outside-view base rate is short-run level persistence: the six official index levels fluctuate around 104-105, while the five successive level changes average +0.24 points. Level is therefore anchored at April's 105.5, with only a small positive continuation.","Current-release adjustments are approximately net zero beyond the persistence prior: recent momentum is positive, the March-April rebound may partly reverse as a one-off, weak building activity offsets stronger civil engineering and specialised work, and no specific policy mechanism warrants a further adjustment."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Euro-area construction production index for May 2026","The target is Eurostat table sts_copr_m, exact series sts_copr_m.M.I21.SCA.PRD.F.EA20: total construction for EA20, calendar and seasonally adjusted, 2021=100. The resolver is the May 2026 first print, not a growth rate or later revision."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is Eurostat table sts_copr_m, exact series sts_copr_m.M.I21.SCA.PRD.F.EA20: total construction for EA20, calendar and seasonally adjusted, 2021=100. The resolver is the May 2026 first print, not a growth rate or later revision.","Tool call: Read the monthly index table in Eurostat's 18 June 2026 Production in construction release."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.7, distribution present, forecast step count 1.","evidence":["Tool call: Read Eurostat's April annual and sector detail to assess the composition of momentum.","Prior/update/interval: The model is a persistence-plus-mean-change prior using the six November-April official index observations. Successive changes are +0.3, -1.0, -0.5, +1.8, and +0.6 points; their mean is +0.24 and sample sigma = 1.08 points. Starting from 105.5 gives 105.5 + 0.24 = 105.74, rounded to 105.7. The empirical 80% half-width is 1.28*sigma = 1.28*1.08 = 1.38 points, implying 105.74 ± 1.38 = 104.36 to 107.12, rounded to 104.4-107.1."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Read Eurostat's April annual and sector detail to assess the composition of momentum.","Current-release adjustments are approximately net zero beyond the persistence prior: recent momentum is positive, the March-April rebound may partly reverse as a one-off, weak building activity offsets stronger civil engineering and specialised work, and no specific policy mechanism warrants a further adjustment."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Current-release adjustments are approximately net zero beyond the persistence prior: recent momentum is positive, the March-April rebound may partly reverse as a one-off, weak building activity offsets stronger civil engineering and specialised work, and no specific policy mechanism warrants a further adjustment.","Upside risk comes from another broad rebound like March, which would land above the interval. Downside risk comes from renewed building-sector weakness or reversal of the March-April surge; a monthly fall exceeding roughly 1.1 points would land below the interval. Either outcome would be outside the interval and falsify the central persistence view."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The outside-view base rate is short-run level persistence: the six official index levels fluctuate around 104-105, while the five successive level changes average +0.24 points. Level is therefore anchored at April's 105.5, with only a small positive continuation.","Prior/update/interval: The model is a persistence-plus-mean-change prior using the six November-April official index observations. Successive changes are +0.3, -1.0, -0.5, +1.8, and +0.6 points; their mean is +0.24 and sample sigma = 1.08 points. Starting from 105.5 gives 105.5 + 0.24 = 105.74, rounded to 105.7. The empirical 80% half-width is 1.28*sigma = 1.28*1.08 = 1.38 points, implying 105.74 ± 1.38 = 104.36 to 107.12, rounded to 104.4-107.1."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: euro-area-construction-production-index-may-2026\nrunLabel: Headline\nresolutionDate: 2026-07-20\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.abs-labour-employment-change-australia-june-2026.2026-07-11T18-15-02Z.9a6ad231ebeda7fd","runId":"run.abs-labour-employment-change-australia-june-2026.2026-07-11T18-15-02Z.9a6ad231ebeda7fd","predictionId":"abs-labour-employment-change-australia-june-2026","specId":"spec.abs-labour-employment-change-australia-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["The outside-view base rate is the 12-month mean employment change of 12.3 thousand. Momentum is mildly stronger: the latest trend increase was 20.2 thousand and four of the latest five seasonally adjusted changes were positive. Against that, falling vacancies argue against extrapolating May's 40.3 thousand gain.","Level, momentum, one-off, and policy mechanisms point in different directions: the employment level remains high; recent momentum is positive; monthly Labour Force sampling and the survey-system transition can create one-off volatility; and softer labour demand should restrain underlying hiring. I therefore adjust the 12.3-thousand prior upward by 8 thousand for trend and momentum, then apply a judgmental downward adjustment of about 2 thousand for weaker vacancies, yielding 18 thousand."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The target is the first June 2026 print for ABS series LF/M3.3.1599.20.AUS.M, employed persons in Australia, seasonally adjusted, month-over-month change in thousands. It is not trend or original employment, and later revisions do not replace the first print.","Tool call: Verify the June 2026 Labour Force publication date on the official ABS future-release calendar."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the first June 2026 print for ABS series LF/M3.3.1599.20.AUS.M, employed persons in Australia, seasonally adjusted, month-over-month change in thousands. It is not trend or original employment, and later revisions do not replace the first print.","Tool call: Inspect the ABS Labour Force, Australia May 2026 release and its seasonally adjusted employment table."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 80.6, distribution present, forecast step count 1.","evidence":["Prior/update/interval: the persistence model uses the mean of the 12 fetched June 2025-May 2026 seasonally adjusted employment changes as the prior (12.3 thousand), with +8 thousand for recent positive momentum and the 20.2-thousand trend gain, and a judgmental -2.3 thousand for weaker vacancies, giving 18.0 thousand. For this change/flow series, the interval method uses those same 12 monthly change values: sample sigma = 31.5 thousand. The normal 80% half-width is 1.28*sigma = 1.28*31.5 = 40.3 thousand, so the final implied bounds are 18.0-40.3 = -22.3 and 18.0+40.3 = 58.3 thousand.","Upside risk comes from another strong participation-supported hiring month or a favourable rotation-group draw and would land above the interval if employment rises by more than 58.3 thousand. Downside risk comes from sharper labour-demand weakening or adverse survey volatility and would land below the interval if employment falls by more than 22.3 thousand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The outside-view base rate is the 12-month mean employment change of 12.3 thousand. Momentum is mildly stronger: the latest trend increase was 20.2 thousand and four of the latest five seasonally adjusted changes were positive. Against that, falling vacancies argue against extrapolating May's 40.3 thousand gain.","Level, momentum, one-off, and policy mechanisms point in different directions: the employment level remains high; recent momentum is positive; monthly Labour Force sampling and the survey-system transition can create one-off volatility; and softer labour demand should restrain underlying hiring. I therefore adjust the 12.3-thousand prior upward by 8 thousand for trend and momentum, then apply a judgmental downward adjustment of about 2 thousand for weaker vacancies, yielding 18 thousand."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Upside risk comes from another strong participation-supported hiring month or a favourable rotation-group draw and would land above the interval if employment rises by more than 58.3 thousand. Downside risk comes from sharper labour-demand weakening or adverse survey volatility and would land below the interval if employment falls by more than 22.3 thousand."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Level, momentum, one-off, and policy mechanisms point in different directions: the employment level remains high; recent momentum is positive; monthly Labour Force sampling and the survey-system transition can create one-off volatility; and softer labour demand should restrain underlying hiring. I therefore adjust the 12.3-thousand prior upward by 8 thousand for trend and momentum, then apply a judgmental downward adjustment of about 2 thousand for weaker vacancies, yielding 18 thousand.","Prior/update/interval: the persistence model uses the mean of the 12 fetched June 2025-May 2026 seasonally adjusted employment changes as the prior (12.3 thousand), with +8 thousand for recent positive momentum and the 20.2-thousand trend gain, and a judgmental -2.3 thousand for weaker vacancies, giving 18.0 thousand. For this change/flow series, the interval method uses those same 12 monthly change values: sample sigma = 31.5 thousand. The normal 80% half-width is 1.28*sigma = 1.28*31.5 = 40.3 thousand, so the final implied bounds are 18.0-40.3 = -22.3 and 18.0+40.3 = 58.3 thousand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: abs-labour-employment-change-australia-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-23\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.abs-cpi-all-groups-annual-rate-australia-june-2026.2026-07-11T18-13-41Z.b7764552c628f46e","runId":"run.abs-cpi-all-groups-annual-rate-australia-june-2026.2026-07-11T18-13-41Z.b7764552c628f46e","predictionId":"abs-cpi-all-groups-annual-rate-australia-june-2026","specId":"spec.abs-cpi-all-groups-annual-rate-australia-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["The reference class/base rate is persistence in the same original annual series. The 14 observations from April 2025 through May 2026 were 2.4%, 2.1%, 1.9%, 3.0%, 3.2%, 3.6%, 3.8%, 3.4%, 3.8%, 3.8%, 3.7%, 4.6%, 4.2%, and 4.0%; their mean successive change was +0.12 percentage point.","Prior/update/interval: persistence prior = May's 4.0%; historical sample = the 14 same-variant annual rates from April 2025 to May 2026. Add +0.12 percentage point from the historical mean successive change, about +0.10 for partial reversal of May's transport/travel weakness and sticky housing, and about -0.02 for recent disinflation, giving 4.20%, rounded to 4.2%. Across the 13 successive annual-rate changes, sigma = 0.476 percentage point. The normal 80% half-width is 1.28*sigma = 1.28*0.476 = 0.610, so 4.2% ± 0.61 rounds to implied bounds of 3.6% and 4.8%."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Tool call: Fetch the ABS May 2026 Consumer Price Index release and its All groups annual history.","Tool result: The official ABS schedule lists Consumer Price Index, Australia, June 2026 for 29 July 2026 at 11:30am Canberra time; the May release also states next release 29/07/2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the first-print June 2026 annual change in the original, not seasonally adjusted, All groups CPI for the weighted average of eight capital cities. Resolution uses ABS series CPI/3.10001.10.50.M and retains the first published one-decimal value without revision grace.","Tool call: Fetch the ABS May 2026 Consumer Price Index release and its All groups annual history."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.2, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = May's 4.0%; historical sample = the 14 same-variant annual rates from April 2025 to May 2026. Add +0.12 percentage point from the historical mean successive change, about +0.10 for partial reversal of May's transport/travel weakness and sticky housing, and about -0.02 for recent disinflation, giving 4.20%, rounded to 4.2%. Across the 13 successive annual-rate changes, sigma = 0.476 percentage point. The normal 80% half-width is 1.28*sigma = 1.28*0.476 = 0.610, so 4.2% ± 0.61 rounds to implied bounds of 3.6% and 4.8%.","Upside risk comes from a larger fuel, travel, or housing rebound and would land above the interval if annual CPI exceeds 4.8%. Downside risk comes from renewed fuel declines, discounting, or faster goods disinflation and would land below the interval if CPI is under 3.6%. These are the concrete outside-the-interval scenarios."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The official 29 July date conflicts with the registered sourceBinding expectedReleaseWindow ending 28 July. I retain the same target but use 29 July 2026 because it is the concrete date verified from the official calendar this run.","Level, momentum, one-off, and policy mechanisms point to a modest rebound: the level remains elevated at 4.0%; recent momentum eased from March's 4.6%; May's original 0.7% monthly fall included sharp Transport and Recreation declines that may partly reverse; Housing at 6.5% and administered or indexed prices keep underlying pressure firm. No mid-2026 CPI weight update is scheduled."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The official 29 July date conflicts with the registered sourceBinding expectedReleaseWindow ending 28 July. I retain the same target but use 29 July 2026 because it is the concrete date verified from the official calendar this run.","Upside risk comes from a larger fuel, travel, or housing rebound and would land above the interval if annual CPI exceeds 4.8%. Downside risk comes from renewed fuel declines, discounting, or faster goods disinflation and would land below the interval if CPI is under 3.6%. These are the concrete outside-the-interval scenarios."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Australia June 2026 annual CPI forecast","The reference class/base rate is persistence in the same original annual series. The 14 observations from April 2025 through May 2026 were 2.4%, 2.1%, 1.9%, 3.0%, 3.2%, 3.6%, 3.8%, 3.4%, 3.8%, 3.8%, 3.7%, 4.6%, 4.2%, and 4.0%; their mean successive change was +0.12 percentage point."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: abs-cpi-all-groups-annual-rate-australia-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-29\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.abs-building-approvals-total-dwellings-mom-australia-june-2026.2026-07-11T18-12-36Z.ef3507517be7938b","runId":"run.abs-building-approvals-total-dwellings-mom-australia-june-2026.2026-07-11T18-12-36Z.ef3507517be7938b","predictionId":"abs-building-approvals-total-dwellings-mom-australia-june-2026","specId":"spec.abs-building-approvals-total-dwellings-mom-australia-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The outside-view base rate is modestly positive: the mean of the 11 latest same-vintage monthly changes is about 1.4%, but the reference class is extremely dispersed because lumpy multi-unit projects drive large reversals.","Prior/update/interval: use a 12-month same-series persistence/base-rate model comprising 12 monthly ABS seasonally adjusted total-dwellings levels and their 11 successive changes from June 2025 through May 2026. The changes have a 1.4% mean and sample sigma = 18.3 percentage points. Starting from the 1.4% historical mean, apply roughly +1.0 point for rebound after May weakness, -0.5 point for the mildly negative trend, and -0.4 point for continued multi-unit normalization, yielding 1.5% after rounding. The normal-reference 80% half-width is 1.28*sigma = 1.28*18.3 = 23.4 points, so 1.5 ± 23.4 gives -21.9% to 24.9%, rounded outward to -22% and 25%."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Tool call: Inspect the ABS May 2026 Building Approvals release for the latest national seasonally adjusted total-dwellings observations.","Level, momentum, one-off, and policy mechanisms point in different directions. The 17,019 May level is near the recent range's middle and May's -1.1% offers limited rebound pressure; two weak months suggest soft momentum, while February's multi-unit spike has largely unwound. Firm house approvals provide support, but the volatile non-house component dominates tail risk."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the first-print June 2026 month-over-month change in seasonally adjusted total dwelling units approved for Australia. The ABS release page is the resolver; this is the seasonally adjusted total series, not trend, original, private-house, or small-area data.","The registered archived May release URL is the target's pre-release source placeholder. Resolution uses the June first-print value published within the same ABS Building Approvals release series, while retaining the registered resolver contract."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 47, distribution present, forecast step count 1.","evidence":["Tool call: Check the ABS component split and state detail in the May 2026 release.","Level, momentum, one-off, and policy mechanisms point in different directions. The 17,019 May level is near the recent range's middle and May's -1.1% offers limited rebound pressure; two weak months suggest soft momentum, while February's multi-unit spike has largely unwound. Firm house approvals provide support, but the volatile non-house component dominates tail risk."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The outside-view base rate is modestly positive: the mean of the 11 latest same-vintage monthly changes is about 1.4%, but the reference class is extremely dispersed because lumpy multi-unit projects drive large reversals.","Level, momentum, one-off, and policy mechanisms point in different directions. The 17,019 May level is near the recent range's middle and May's -1.1% offers limited rebound pressure; two weak months suggest soft momentum, while February's multi-unit spike has largely unwound. Firm house approvals provide support, but the volatile non-house component dominates tail risk."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The outside-view base rate is modestly positive: the mean of the 11 latest same-vintage monthly changes is about 1.4%, but the reference class is extremely dispersed because lumpy multi-unit projects drive large reversals.","Level, momentum, one-off, and policy mechanisms point in different directions. The 17,019 May level is near the recent range's middle and May's -1.1% offers limited rebound pressure; two weak months suggest soft momentum, while February's multi-unit spike has largely unwound. Firm house approvals provide support, but the volatile non-house component dominates tail risk."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Level, momentum, one-off, and policy mechanisms point in different directions. The 17,019 May level is near the recent range's middle and May's -1.1% offers limited rebound pressure; two weak months suggest soft momentum, while February's multi-unit spike has largely unwound. Firm house approvals provide support, but the volatile non-house component dominates tail risk.","Prior/update/interval: use a 12-month same-series persistence/base-rate model comprising 12 monthly ABS seasonally adjusted total-dwellings levels and their 11 successive changes from June 2025 through May 2026. The changes have a 1.4% mean and sample sigma = 18.3 percentage points. Starting from the 1.4% historical mean, apply roughly +1.0 point for rebound after May weakness, -0.5 point for the mildly negative trend, and -0.4 point for continued multi-unit normalization, yielding 1.5% after rounding. The normal-reference 80% half-width is 1.28*sigma = 1.28*18.3 = 23.4 points, so 1.5 ± 23.4 gives -21.9% to 24.9%, rounded outward to -22% and 25%."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: abs-building-approvals-total-dwellings-mom-australia-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-30\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bea-government-social-benefits-level-june-2026.2026-07-11T18-16-23Z.103040a9de06bb81","runId":"run.bea-government-social-benefits-level-june-2026.2026-07-11T18-16-23Z.103040a9de06bb81","predictionId":"bea-government-social-benefits-level-june-2026","specId":"spec.bea-government-social-benefits-level-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The reference class and base rate are short-horizon monthly level forecasts for this same SAAR series. Persistence is the primary prior: May's 5024.4 level is more informative than extrapolating its exceptional +28.7 increase, while the four-change mean of +5.4 indicates a gently rising underlying path.","Prior/update/interval: persistence model prior = May 5024.4; historical sample = January–May 2026 levels with changes -14.8, +3.0, +4.7, +28.7. Adjustment components are +3.9 billion for the median recent monthly change, +0.0 for known one-offs, and +0.0 for identified June policy changes, giving 5024.4 + 3.9 = 5028.3. From the four successive changes, sample sigma = 17.9 billion; the normal-reference 80% half-width is 1.28*sigma = 1.28*17.9 = 22.9 billion. Thus the final implied bounds are 5028.3 - 22.9 = 5005.4 and 5028.3 + 22.9 = 5051.2. This interval is fragile because sigma is estimated from only four recent changes."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The target is BEA series A063RC1: monthly personal current transfer receipts from government social benefits, measured in billions of dollars at a seasonally adjusted annual rate. It resolves on the first June 2026 print, not a later revision.","Tool call: Fetch the latest published A063RC1 monthly observations and units from the BEA-sourced FRED series page."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["June 2026 government social benefits first-print forecast","The target is BEA series A063RC1: monthly personal current transfer receipts from government social benefits, measured in billions of dollars at a seasonally adjusted annual rate. It resolves on the first June 2026 print, not a later revision."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 45.8, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence model prior = May 5024.4; historical sample = January–May 2026 levels with changes -14.8, +3.0, +4.7, +28.7. Adjustment components are +3.9 billion for the median recent monthly change, +0.0 for known one-offs, and +0.0 for identified June policy changes, giving 5024.4 + 3.9 = 5028.3. From the four successive changes, sample sigma = 17.9 billion; the normal-reference 80% half-width is 1.28*sigma = 1.28*17.9 = 22.9 billion. Thus the final implied bounds are 5028.3 - 22.9 = 5005.4 and 5028.3 + 22.9 = 5051.2. This interval is fragile because sigma is estimated from only four recent changes.","Upside risk comes from another discrete acceleration in Social Security, Medicare, Medicaid, veterans, or disaster-related benefits and would land above the interval if the June increase exceeds about 26.8 billion. Downside risk comes from payment timing, normalization after May, or adverse first-print source-data revisions and would land below the interval if June falls more than about 19.0 billion."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence model prior = May 5024.4; historical sample = January–May 2026 levels with changes -14.8, +3.0, +4.7, +28.7. Adjustment components are +3.9 billion for the median recent monthly change, +0.0 for known one-offs, and +0.0 for identified June policy changes, giving 5024.4 + 3.9 = 5028.3. From the four successive changes, sample sigma = 17.9 billion; the normal-reference 80% half-width is 1.28*sigma = 1.28*17.9 = 22.9 billion. Thus the final implied bounds are 5028.3 - 22.9 = 5005.4 and 5028.3 + 22.9 = 5051.2. This interval is fragile because sigma is estimated from only four recent changes."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Upside risk comes from another discrete acceleration in Social Security, Medicare, Medicaid, veterans, or disaster-related benefits and would land above the interval if the June increase exceeds about 26.8 billion. Downside risk comes from payment timing, normalization after May, or adverse first-print source-data revisions and would land below the interval if June falls more than about 19.0 billion."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["June 2026 government social benefits first-print forecast","The reference class and base rate are short-horizon monthly level forecasts for this same SAAR series. Persistence is the primary prior: May's 5024.4 level is more informative than extrapolating its exceptional +28.7 increase, while the four-change mean of +5.4 indicates a gently rising underlying path."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bea-government-social-benefits-level-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-30\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-ei-regular-beneficiaries-july-2026.2026-07-11T01-34-14Z.50260c9e1c285788","runId":"run.canada-ei-regular-beneficiaries-july-2026.2026-07-11T01-34-14Z.50260c9e1c285788","predictionId":"canada-ei-regular-beneficiaries-july-2026","specId":"spec.canada-ei-regular-beneficiaries-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["The outside-view base rate is recent persistence: four successive monthly changes from December 2025 through April 2026 were -8.60, -8.67, -2.91, and -3.00 thousand, averaging -5.80 thousand. Applying that mean for three months gives a raw July level of 544.44 - 3×5.80 = 527.04 thousand.","Prior/update/interval: The model is a three-step average-change persistence prior using the December 2025-April 2026 official history, selected because it is the fetched sample describing the current post-December downtrend regime. Baseline = 544.44 + 3×(-5.80) = 527.04 thousand; adjustment components are +2.0 thousand for July composition and EI-flow lag effects and 0 for policy changes, giving 529.0 thousand. The sample standard deviation of the four successive changes (-8.60, -8.67, -2.91, -3.00) is sigma = 3.3 thousand. For a three-month horizon, the 80% half-width is 1.28×sigma×sqrt(3) = 1.28×3.3×1.732 = 7.3 thousand, implying 529.0±7.3 = 521.7 to 536.3 thousand. This short, single-regime volatility sample may omit wider historical or seasonal variation, but no unsupported longer sample is substituted."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["The target is the first July 2026 print for Statistics Canada vector v64549350 in Table 14-10-0011-01: Canada, regular benefits, both sexes, age 15 years and over, seasonally adjusted persons. The ledger conversion to thousands is persons × 0.001; later revisions are excluded.","Tool call: Fetched the latest Canada observations from Statistics Canada Table 14-10-0011-01."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the first July 2026 print for Statistics Canada vector v64549350 in Table 14-10-0011-01: Canada, regular benefits, both sexes, age 15 years and over, seasonally adjusted persons. The ledger conversion to thousands is persons × 0.001; later revisions are excluded.","Tool call: Fetched Statistics Canada's April 2026 Employment Insurance release."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 14.6, distribution present, forecast step count 1.","evidence":["Prior/update/interval: The model is a three-step average-change persistence prior using the December 2025-April 2026 official history, selected because it is the fetched sample describing the current post-December downtrend regime. Baseline = 544.44 + 3×(-5.80) = 527.04 thousand; adjustment components are +2.0 thousand for July composition and EI-flow lag effects and 0 for policy changes, giving 529.0 thousand. The sample standard deviation of the four successive changes (-8.60, -8.67, -2.91, -3.00) is sigma = 3.3 thousand. For a three-month horizon, the 80% half-width is 1.28×sigma×sqrt(3) = 1.28×3.3×1.732 = 7.3 thousand, implying 529.0±7.3 = 521.7 to 536.3 thousand. This short, single-regime volatility sample may omit wider historical or seasonal variation, but no unsupported longer sample is substituted.","Upside risk comes from renewed layoffs, particularly in manufacturing, or another education-related July composition jump and would land above the interval. Downside risk comes from faster job finding, benefit exhaustion, or delayed claims entry and could land below the interval. A sharp administrative or eligibility change would also place the result outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Fetched the June 2026 Labour Force Survey for current labour-market momentum.","Level is anchored at April's 544.44 thousand. Momentum is downward because employment strengthened and unemployment declined in May and June. The +2.0-thousand adjustment combines same-month evidence that July 2025 rose 6.6 thousand amid occupational composition effects with an offsetting EI-flow lag: claims entry, return to work, eligibility, and benefit exhaustion need not move contemporaneously with the LFS. No separate policy-change adjustment is applied."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level is anchored at April's 544.44 thousand. Momentum is downward because employment strengthened and unemployment declined in May and June. The +2.0-thousand adjustment combines same-month evidence that July 2025 rose 6.6 thousand amid occupational composition effects with an offsetting EI-flow lag: claims entry, return to work, eligibility, and benefit exhaustion need not move contemporaneously with the LFS. No separate policy-change adjustment is applied.","Prior/update/interval: The model is a three-step average-change persistence prior using the December 2025-April 2026 official history, selected because it is the fetched sample describing the current post-December downtrend regime. Baseline = 544.44 + 3×(-5.80) = 527.04 thousand; adjustment components are +2.0 thousand for July composition and EI-flow lag effects and 0 for policy changes, giving 529.0 thousand. The sample standard deviation of the four successive changes (-8.60, -8.67, -2.91, -3.00) is sigma = 3.3 thousand. For a three-month horizon, the 80% half-width is 1.28×sigma×sqrt(3) = 1.28×3.3×1.732 = 7.3 thousand, implying 529.0±7.3 = 521.7 to 536.3 thousand. This short, single-regime volatility sample may omit wider historical or seasonal variation, but no unsupported longer sample is substituted."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: The model is a three-step average-change persistence prior using the December 2025-April 2026 official history, selected because it is the fetched sample describing the current post-December downtrend regime. Baseline = 544.44 + 3×(-5.80) = 527.04 thousand; adjustment components are +2.0 thousand for July composition and EI-flow lag effects and 0 for policy changes, giving 529.0 thousand. The sample standard deviation of the four successive changes (-8.60, -8.67, -2.91, -3.00) is sigma = 3.3 thousand. For a three-month horizon, the 80% half-width is 1.28×sigma×sqrt(3) = 1.28×3.3×1.732 = 7.3 thousand, implying 529.0±7.3 = 521.7 to 536.3 thousand. This short, single-regime volatility sample may omit wider historical or seasonal variation, but no unsupported longer sample is substituted.","Upside risk comes from renewed layoffs, particularly in manufacturing, or another education-related July composition jump and would land above the interval. Downside risk comes from faster job finding, benefit exhaustion, or delayed claims entry and could land below the interval. A sharp administrative or eligibility change would also place the result outside the interval."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-ei-regular-beneficiaries-july-2026\nrunLabel: Headline\nresolutionDate: 2026-09-17\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-monthly-gdp-growth-july-2026.2026-07-11T01-32-40Z.76491f033031e995","runId":"run.canada-monthly-gdp-growth-july-2026.2026-07-11T01-32-40Z.76491f033031e995","predictionId":"canada-monthly-gdp-growth-july-2026","specId":"spec.canada-monthly-gdp-growth-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 10 historical point(s) and explicit outside-view language.","evidence":["The reference class is the ten official monthly observations from July 2025 through April 2026: 0.6, -0.1, 0.2, -0.3, 0.0, 0.2, 0.0, 0.2, -0.1, and 0.5 percent. Their mean is 0.12%, providing the base rate before release-specific adjustments. The preliminary May advance estimate is contextual evidence and is not included in this historical sample or its variance.","Prior/update/interval: persistence/base-rate model; historical sample = the 10 July 2025–April 2026 monthly growth values. Their mean is 0.12%. Adjustments are -0.01 point for fading April energy/reopening strength, -0.02 for manufacturing and trade uncertainty, and +0.01 for services persistence, giving 0.10%. For this change series, dispersion is computed from the values themselves: sample variance = 0.696/9 = 0.0773, so sigma = 0.278%. The normal 80% half-width is 1.28*sigma = 1.28*0.278 = 0.356%, implying 0.10 ± 0.356 = [-0.256%, 0.456%], reported as [-0.26%, 0.46%]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Tool call: Inspect Statistics Canada's 2026–2027 official release calendar for GDP by industry.","Tool result: The official calendar lists September 29, 2026 as the release date for the July 2026 reference period; it also lists August 28 for June and October 30 for August."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Canada real GDP by industry, July 2026 first print","The target is the July 2026 month-over-month change in Statistics Canada vector v65201210, Table 36-10-0434-01: all industries, chained 2017 dollars, seasonally adjusted at annual rates. It resolves from the first release vintage, not a later revision."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.72, distribution present, forecast step count 1.","evidence":["Level and momentum effects are mildly positive: the April rebound was broad and the preliminary May signal was +0.1%. One-off effects from energy maintenance and labour disruptions can reverse quickly. Policy and trade uncertainty restrain manufacturing, while steady services activity supports growth.","Prior/update/interval: persistence/base-rate model; historical sample = the 10 July 2025–April 2026 monthly growth values. Their mean is 0.12%. Adjustments are -0.01 point for fading April energy/reopening strength, -0.02 for manufacturing and trade uncertainty, and +0.01 for services persistence, giving 0.10%. For this change series, dispersion is computed from the values themselves: sample variance = 0.696/9 = 0.0773, so sigma = 0.278%. The normal 80% half-width is 1.28*sigma = 1.28*0.278 = 0.356%, implying 0.10 ± 0.356 = [-0.256%, 0.456%], reported as [-0.26%, 0.46%]."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level and momentum effects are mildly positive: the April rebound was broad and the preliminary May signal was +0.1%. One-off effects from energy maintenance and labour disruptions can reverse quickly. Policy and trade uncertainty restrain manufacturing, while steady services activity supports growth."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level and momentum effects are mildly positive: the April rebound was broad and the preliminary May signal was +0.1%. One-off effects from energy maintenance and labour disruptions can reverse quickly. Policy and trade uncertainty restrain manufacturing, while steady services activity supports growth.","Prior/update/interval: persistence/base-rate model; historical sample = the 10 July 2025–April 2026 monthly growth values. Their mean is 0.12%. Adjustments are -0.01 point for fading April energy/reopening strength, -0.02 for manufacturing and trade uncertainty, and +0.01 for services persistence, giving 0.10%. For this change series, dispersion is computed from the values themselves: sample variance = 0.696/9 = 0.0773, so sigma = 0.278%. The normal 80% half-width is 1.28*sigma = 1.28*0.278 = 0.356%, implying 0.10 ± 0.356 = [-0.256%, 0.456%], reported as [-0.26%, 0.46%]."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: persistence/base-rate model; historical sample = the 10 July 2025–April 2026 monthly growth values. Their mean is 0.12%. Adjustments are -0.01 point for fading April energy/reopening strength, -0.02 for manufacturing and trade uncertainty, and +0.01 for services persistence, giving 0.10%. For this change series, dispersion is computed from the values themselves: sample variance = 0.696/9 = 0.0773, so sigma = 0.278%. The normal 80% half-width is 1.28*sigma = 1.28*0.278 = 0.356%, implying 0.10 ± 0.356 = [-0.256%, 0.456%], reported as [-0.26%, 0.46%].","Upside risk comes from a synchronized oil, mining, manufacturing, and services expansion; growth above 0.46% would land outside the interval. Downside risk comes from shutdowns, wildfire or maintenance disruptions, or a sharp trade-related manufacturing contraction; growth below -0.26% would land outside the interval."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-monthly-gdp-growth-july-2026\nrunLabel: Headline\nresolutionDate: 2026-09-29\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.initial-claims-week-2026-07-18.2026-07-11T00-25-34Z.fbe3c2c3da579fd1","runId":"run.initial-claims-week-2026-07-18.2026-07-11T00-25-34Z.fbe3c2c3da579fd1","predictionId":"initial-claims-week-2026-07-18","specId":"spec.initial-claims-week-2026-07-18","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool call: Read the historical table embedded in the July 9 DOL release for the comparable July period and recent 2026 changes.","Tool result: The historical table shows 2025 SA claims of 228 thousand on July 5, 221 thousand on July 12, and 218 thousand on July 19; its 27 weekly changes from January 3 through July 4, 2026 range from -25 to +19 thousand."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The reference class and base rate are low-volatility weekly claims observations outside recession: the latest six same-variant readings center near 218 thousand, while the comparable July 2025 sequence declined from 228 to 218 thousand. Persistence therefore anchors the forecast near 215-218 thousand.","Level is about 215 thousand and recent momentum is mildly downward; one-off holiday and auto-retooling seasonality can create July noise even after adjustment. No official release evidence indicates a policy mechanism or broad layoffs requiring a large directional shift, so the net update is +1 thousand from the latest advance level."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the DOL advance first print for US initial claims, seasonally adjusted, for the week ending July 18, 2026. The DOL schedule verifies release on Thursday, July 23, 2026. Resolution uses the advance SA figure only, not NSA claims, the four-week average, or a revised vintage; the series is ICSA and the release table is UNEMPLOYMENT INSURANCE DATA FOR REGULAR STATE PROGRAMS.","Tool call: Read the July 9, 2026 DOL Weekly Claims release and its regular-state-program table."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 26, distribution present, forecast step count 1.","evidence":["Prior/update/interval: The model is persistence around the latest 215 thousand observation, checked against the six-reading recent historical sample of 225, 230, 227, 216, 217, and 215. Adjustments are +1 thousand for mean reversion, 0 for weak downward momentum, 0 for policy, and 0 net for July one-offs, giving 216. For interval sizing, the 27 successive same-series seasonally adjusted weekly changes from January 3 through July 4 have sum 12 and sum of squares 2748, so sample sigma = sqrt((2748 - 12^2/27)/(27-1)) = 10.27 thousand. The normal 80% half-width is 1.28*sigma = 13.15 thousand; 216 ± 13.15 rounds to final implied bounds of 203 and 229 thousand.","Upside risk comes from concentrated auto-sector or other temporary layoffs and would land above the interval if the first print exceeds 229 thousand. Downside risk comes from unusually favorable seasonal adjustment or fewer filings and would land below the interval if the first print is under 203 thousand. Either outcome would be outside the interval and falsify the assumed calm-regime persistence model."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level is about 215 thousand and recent momentum is mildly downward; one-off holiday and auto-retooling seasonality can create July noise even after adjustment. No official release evidence indicates a policy mechanism or broad layoffs requiring a large directional shift, so the net update is +1 thousand from the latest advance level.","Prior/update/interval: The model is persistence around the latest 215 thousand observation, checked against the six-reading recent historical sample of 225, 230, 227, 216, 217, and 215. Adjustments are +1 thousand for mean reversion, 0 for weak downward momentum, 0 for policy, and 0 net for July one-offs, giving 216. For interval sizing, the 27 successive same-series seasonally adjusted weekly changes from January 3 through July 4 have sum 12 and sum of squares 2748, so sample sigma = sqrt((2748 - 12^2/27)/(27-1)) = 10.27 thousand. The normal 80% half-width is 1.28*sigma = 13.15 thousand; 216 ± 13.15 rounds to final implied bounds of 203 and 229 thousand."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Upside risk comes from concentrated auto-sector or other temporary layoffs and would land above the interval if the first print exceeds 229 thousand. Downside risk comes from unusually favorable seasonal adjustment or fewer filings and would land below the interval if the first print is under 203 thousand. Either outcome would be outside the interval and falsify the assumed calm-regime persistence model."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The reference class and base rate are low-volatility weekly claims observations outside recession: the latest six same-variant readings center near 218 thousand, while the comparable July 2025 sequence declined from 228 to 218 thousand. Persistence therefore anchors the forecast near 215-218 thousand.","Prior/update/interval: The model is persistence around the latest 215 thousand observation, checked against the six-reading recent historical sample of 225, 230, 227, 216, 217, and 215. Adjustments are +1 thousand for mean reversion, 0 for weak downward momentum, 0 for policy, and 0 net for July one-offs, giving 216. For interval sizing, the 27 successive same-series seasonally adjusted weekly changes from January 3 through July 4 have sum 12 and sum of squares 2748, so sample sigma = sqrt((2748 - 12^2/27)/(27-1)) = 10.27 thousand. The normal 80% half-width is 1.28*sigma = 13.15 thousand; 216 ± 13.15 rounds to final implied bounds of 203 and 229 thousand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: initial-claims-week-2026-07-18\nrunLabel: Headline\nresolutionDate: 2026-07-23\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.initial-claims-week-2026-07-18.2026-07-11T00-25-34Z.time-series-prior.a5dca327ff891db1","runId":"run.initial-claims-week-2026-07-18.2026-07-11T00-25-34Z.time-series-prior.a5dca327ff891db1","predictionId":"initial-claims-week-2026-07-18","specId":"spec.initial-claims-week-2026-07-18","runLabel":"Ledger persistence baseline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.16,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Time-series prior","Tool call: brier.timeseries.prior({ target: \"us.dol.initial_claims.sa.week_2026-07-18\", model: \"persistence.last_print\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Tool result: latest=215 (2026-07-04); history_points=3; interval_method=ledger_realized_step_change_p80; ledger_refs=us.dol.initial_claims.sa.week_2026-06-13,us.dol.initial_claims.sa.week_2026-06-20,us.dol.initial_claims.sa.week_2026-07-04"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 17.6, distribution present, forecast step count 1.","evidence":["Tool result: latest=215 (2026-07-04); history_points=3; interval_method=ledger_realized_step_change_p80; ledger_refs=us.dol.initial_claims.sa.week_2026-06-13,us.dol.initial_claims.sa.week_2026-06-20,us.dol.initial_claims.sa.week_2026-07-04","Prior point = latest observed value = 215; 80% interval = [206, 224]."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: latest=215 (2026-07-04); history_points=3; interval_method=ledger_realized_step_change_p80; ledger_refs=us.dol.initial_claims.sa.week_2026-06-13,us.dol.initial_claims.sa.week_2026-06-20,us.dol.initial_claims.sa.week_2026-07-04","Prior point = latest observed value = 215; 80% interval = [206, 224]."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: initial-claims-week-2026-07-18\nrunLabel: Ledger persistence baseline\nresolutionDate: 2026-07-23\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.continued-claims-week-2026-07-18.2026-07-11T00-27-39Z.4810b7e1af46c0c8","runId":"run.continued-claims-week-2026-07-18.2026-07-11T00-27-39Z.4810b7e1af46c0c8","predictionId":"continued-claims-week-2026-07-18","specId":"spec.continued-claims-week-2026-07-18","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: persistence dominates this weekly level series. The five first prints from May 30 through June 27 averaged 1.811 million, while their net change was only +0.019 million. As of the run time, June 27 was the latest available continued-claims first print, making July 18 a three-step horizon.","Prior/update/interval: persistence prior = 1.814 million, using the five first-print observations 1.795, 1.810, 1.821, 1.814, and 1.814. Successive changes are +0.015, +0.011, -0.007, and 0.000 million; their mean is +0.00475 and sample sigma = 0.0101 million. Three-week momentum adds 3×0.00475 = 0.01425, giving 1.82825, rounded to 1.828. For a three-step horizon, sigma scales to 0.0101×sqrt(3) = 0.0175, and 1.28×sigma = 0.0224. Because four calm changes are a short volatility sample and the horizon spans holiday-sensitive seasonal adjustment, the half-width is widened by about 1.34× to 0.030 million, yielding final implied bounds of 1.798 to 1.858 million."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["The target is ETA series CCSA: advance first-print U.S. insured unemployment, seasonally adjusted, for the week ending July 18—not the NSA level, four-week average, or a later revised vintage. Resolution uses the July 30 release, reports millions, and preserves the first print through the ledger-bound ALFRED advance vintage.","Tool call: Checked the Department of Labor's official release-timing announcement and the target's calendar window."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is ETA series CCSA: advance first-print U.S. insured unemployment, seasonally adjusted, for the week ending July 18—not the NSA level, four-week average, or a later revised vintage. Resolution uses the July 30 release, reports millions, and preserves the first print through the ledger-bound ALFRED advance vintage.","Tool call: Checked the Department of Labor's official release-timing announcement and the target's calendar window."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.06, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = 1.814 million, using the five first-print observations 1.795, 1.810, 1.821, 1.814, and 1.814. Successive changes are +0.015, +0.011, -0.007, and 0.000 million; their mean is +0.00475 and sample sigma = 0.0101 million. Three-week momentum adds 3×0.00475 = 0.01425, giving 1.82825, rounded to 1.828. For a three-step horizon, sigma scales to 0.0101×sqrt(3) = 0.0175, and 1.28×sigma = 0.0224. Because four calm changes are a short volatility sample and the horizon spans holiday-sensitive seasonal adjustment, the half-width is widened by about 1.34× to 0.030 million, yielding final implied bounds of 1.798 to 1.858 million.","Level and momentum point mildly upward, while initial claims near 0.215 million provide no strong deterioration signal. Holiday-related seasonal adjustment is the main one-off risk; no discrete policy mechanism warrants an additional point shift."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior = 1.814 million, using the five first-print observations 1.795, 1.810, 1.821, 1.814, and 1.814. Successive changes are +0.015, +0.011, -0.007, and 0.000 million; their mean is +0.00475 and sample sigma = 0.0101 million. Three-week momentum adds 3×0.00475 = 0.01425, giving 1.82825, rounded to 1.828. For a three-step horizon, sigma scales to 0.0101×sqrt(3) = 0.0175, and 1.28×sigma = 0.0224. Because four calm changes are a short volatility sample and the horizon spans holiday-sensitive seasonal adjustment, the half-width is widened by about 1.34× to 0.030 million, yielding final implied bounds of 1.798 to 1.858 million.","Level and momentum point mildly upward, while initial claims near 0.215 million provide no strong deterioration signal. Holiday-related seasonal adjustment is the main one-off risk; no discrete policy mechanism warrants an additional point shift."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level and momentum point mildly upward, while initial claims near 0.215 million provide no strong deterioration signal. Holiday-related seasonal adjustment is the main one-off risk; no discrete policy mechanism warrants an additional point shift.","Upside risk: a broad rise in benefit duration or delayed hiring could land above 1.858 million. Downside risk: faster claimant exits or unusually favorable seasonal adjustment could land below 1.798 million. Either outcome would be outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: persistence prior = 1.814 million, using the five first-print observations 1.795, 1.810, 1.821, 1.814, and 1.814. Successive changes are +0.015, +0.011, -0.007, and 0.000 million; their mean is +0.00475 and sample sigma = 0.0101 million. Three-week momentum adds 3×0.00475 = 0.01425, giving 1.82825, rounded to 1.828. For a three-step horizon, sigma scales to 0.0101×sqrt(3) = 0.0175, and 1.28×sigma = 0.0224. Because four calm changes are a short volatility sample and the horizon spans holiday-sensitive seasonal adjustment, the half-width is widened by about 1.34× to 0.030 million, yielding final implied bounds of 1.798 to 1.858 million.","Level and momentum point mildly upward, while initial claims near 0.215 million provide no strong deterioration signal. Holiday-related seasonal adjustment is the main one-off risk; no discrete policy mechanism warrants an additional point shift."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: continued-claims-week-2026-07-18\nrunLabel: Headline\nresolutionDate: 2026-07-30\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-unemployment-rate-july-2026.2026-07-11T00-28-57Z.66d9f2efa3cbbfa5","runId":"run.australia-unemployment-rate-july-2026.2026-07-11T00-28-57Z.66d9f2efa3cbbfa5","predictionId":"australia-unemployment-rate-july-2026","specId":"spec.australia-unemployment-rate-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The outside-view base rate is persistence: this reference class has stayed within 4.1% to 4.5% across the five available 2026 prints, with a five-month mean of 4.32%. A 4.4% anchor gives more weight to the latest level while allowing mild mean reversion.","Prior/update/interval: The model is a latest-level persistence prior anchored at 4.4%, using the January-May 2026 historical sample [4.1, 4.3, 4.3, 4.5, 4.4]. Successive changes are [+0.2, 0.0, +0.2, -0.1] percentage points; their sample standard deviation is sigma = 0.15 percentage points. The one-step 80% half-width is 1.28*sigma = 1.28*0.15 = 0.19. Because July is two monthly transitions beyond the latest May print, scale by sqrt(2): 0.19*1.414 = 0.27, rounded to the release precision as 0.3. This volatility estimate uses only four month-to-month changes, so it is mechanically transparent but sample-limited. The persistence prior plus a roughly neutral net update gives 4.4%, with final implied bounds 4.4-0.3 = 4.1% and 4.4+0.3 = 4.7%."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 8 source-context item(s), activity log present.","evidence":["The target is the first-print July 2026 Australian unemployment rate for persons, seasonally adjusted—not trend or unadjusted—from ABS dataflow LF, series M13.3.1599.20.AUS.M. Resolution uses the first official print without later revisions.","Tool result: In May 2026 employment rose by 40000, unemployed persons fell by 18300 to 671300, the unemployment rate fell 0.1 point to 4.4%, and the employment-to-population ratio rose 0.1 point to 63.8%."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the first-print July 2026 Australian unemployment rate for persons, seasonally adjusted—not trend or unadjusted—from ABS dataflow LF, series M13.3.1599.20.AUS.M. Resolution uses the first official print without later revisions.","Tool call: Fetched the ABS Labour Force release calendar and series release page for the July 2026 reference period."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.6, distribution present, forecast step count 1.","evidence":["Prior/update/interval: The model is a latest-level persistence prior anchored at 4.4%, using the January-May 2026 historical sample [4.1, 4.3, 4.3, 4.5, 4.4]. Successive changes are [+0.2, 0.0, +0.2, -0.1] percentage points; their sample standard deviation is sigma = 0.15 percentage points. The one-step 80% half-width is 1.28*sigma = 1.28*0.15 = 0.19. Because July is two monthly transitions beyond the latest May print, scale by sqrt(2): 0.19*1.414 = 0.27, rounded to the release precision as 0.3. This volatility estimate uses only four month-to-month changes, so it is mechanically transparent but sample-limited. The persistence prior plus a roughly neutral net update gives 4.4%, with final implied bounds 4.4-0.3 = 4.1% and 4.4+0.3 = 4.7%.","Upside risk comes from restrictive policy producing faster hiring weakness or participation rebounding while employment stalls; a print of 4.8% or higher would land above the interval. Downside risk comes from continued strong employment growth or another unwind in people waiting to start jobs; 4.0% or lower would land below the interval. These are the concrete scenarios outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Fetched the latest ABS Labour Force release for level and momentum indicators.","Level is 4.4%; momentum is mixed because April's rise reversed partly in May; the May waiting-to-start-job backlog unwind is a potentially one-off downward effect; and the policy mechanism from a 4.35% cash rate creates gradual upward pressure through softer labour demand rather than a sharp immediate jump."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: The model is a latest-level persistence prior anchored at 4.4%, using the January-May 2026 historical sample [4.1, 4.3, 4.3, 4.5, 4.4]. Successive changes are [+0.2, 0.0, +0.2, -0.1] percentage points; their sample standard deviation is sigma = 0.15 percentage points. The one-step 80% half-width is 1.28*sigma = 1.28*0.15 = 0.19. Because July is two monthly transitions beyond the latest May print, scale by sqrt(2): 0.19*1.414 = 0.27, rounded to the release precision as 0.3. This volatility estimate uses only four month-to-month changes, so it is mechanically transparent but sample-limited. The persistence prior plus a roughly neutral net update gives 4.4%, with final implied bounds 4.4-0.3 = 4.1% and 4.4+0.3 = 4.7%.","Upside risk comes from restrictive policy producing faster hiring weakness or participation rebounding while employment stalls; a print of 4.8% or higher would land above the interval. Downside risk comes from continued strong employment growth or another unwind in people waiting to start jobs; 4.0% or lower would land below the interval. These are the concrete scenarios outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Australia July 2026 unemployment-rate forecast","Tool result: In May 2026 employment rose by 40000, unemployed persons fell by 18300 to 671300, the unemployment rate fell 0.1 point to 4.4%, and the employment-to-population ratio rose 0.1 point to 63.8%."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-unemployment-rate-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-20\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.wic-participation-july-2026.2026-07-10T23-16-15Z.d21b1eff3d452fbe","runId":"run.wic-participation-july-2026.2026-07-10T23-16-15Z.d21b1eff3d452fbe","predictionId":"wic-participation-july-2026","specId":"spec.wic-participation-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Outside view and base rate: the official reference class rose from 6.58 million in FY2023 to 6.70 million in FY2024 and about 6.765 million in preliminary FY2025 data. Persistence near the latest 6.7-million range is therefore the primary anchor, with only a modest positive trend adjustment.","Prior/update/interval: persistence prior = 6.765 million, using the official FY2023-FY2025 annual reference class and November 2025 preliminary monthly context; adjustments are +0.020 million for continuing momentum, +0.010 million for outreach/modernization, and -0.005 million for summer churn, giving 6.765 + 0.020 + 0.010 - 0.005 = 6.790 million. An exact monthly successive-change sample was not fetched, so sigma = 0.040 million is an explicit judgmental first-print uncertainty assumption rather than an empirical sample estimate. Applying the promoted normal approximation gives 1.28*sigma = 1.28*0.040 = 0.051 million and an 80% interval of 6.790 ± 0.051 = [6.739, 6.841]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The target is the USDA FNS national WIC total-participation series for calendar month July 2026, not enrollment, eligibility, an annual fiscal-year average, or a quality-control release. FNS-798 participation counts people issued benefits during the reporting month. Resolution uses the strict first print from the official WIC monthly table and converts thousands to millions.","Tool call: Inspect USDA ERS's official WIC participation reference-class summary."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the USDA FNS national WIC total-participation series for calendar month July 2026, not enrollment, eligibility, an annual fiscal-year average, or a quality-control release. FNS-798 participation counts people issued benefits during the reporting month. Resolution uses the strict first print from the official WIC monthly table and converts thousands to millions.","Tool call: Check the official FNS release-calendar registration for the July 2026 WIC target."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.1, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = 6.765 million, using the official FY2023-FY2025 annual reference class and November 2025 preliminary monthly context; adjustments are +0.020 million for continuing momentum, +0.010 million for outreach/modernization, and -0.005 million for summer churn, giving 6.765 + 0.020 + 0.010 - 0.005 = 6.790 million. An exact monthly successive-change sample was not fetched, so sigma = 0.040 million is an explicit judgmental first-print uncertainty assumption rather than an empirical sample estimate. Applying the promoted normal approximation gives 1.28*sigma = 1.28*0.040 = 0.051 million and an 80% interval of 6.790 ± 0.051 = [6.739, 6.841].","Counter-considerations: upside risk from unusually strong retention or outreach could put participation above 6.841 million; downside risk from recertification losses, administrative disruption, or incomplete first-print state reporting could put it below 6.739 million. Either outcome would land outside the interval and falsify the assumed stable regime."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and policy mechanisms: the level anchor is roughly 6.765 million; recent multi-year momentum is positive but slowing; July has no identified national one-off enrollment event; modernization and outreach support participation, while ordinary recertification churn and preliminary state submissions restrain the estimate.","Prior/update/interval: persistence prior = 6.765 million, using the official FY2023-FY2025 annual reference class and November 2025 preliminary monthly context; adjustments are +0.020 million for continuing momentum, +0.010 million for outreach/modernization, and -0.005 million for summer churn, giving 6.765 + 0.020 + 0.010 - 0.005 = 6.790 million. An exact monthly successive-change sample was not fetched, so sigma = 0.040 million is an explicit judgmental first-print uncertainty assumption rather than an empirical sample estimate. Applying the promoted normal approximation gives 1.28*sigma = 1.28*0.040 = 0.051 million and an 80% interval of 6.790 ± 0.051 = [6.739, 6.841]."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, one-off, and policy mechanisms: the level anchor is roughly 6.765 million; recent multi-year momentum is positive but slowing; July has no identified national one-off enrollment event; modernization and outreach support participation, while ordinary recertification churn and preliminary state submissions restrain the estimate.","Prior/update/interval: persistence prior = 6.765 million, using the official FY2023-FY2025 annual reference class and November 2025 preliminary monthly context; adjustments are +0.020 million for continuing momentum, +0.010 million for outreach/modernization, and -0.005 million for summer churn, giving 6.765 + 0.020 + 0.010 - 0.005 = 6.790 million. An exact monthly successive-change sample was not fetched, so sigma = 0.040 million is an explicit judgmental first-print uncertainty assumption rather than an empirical sample estimate. Applying the promoted normal approximation gives 1.28*sigma = 1.28*0.040 = 0.051 million and an 80% interval of 6.790 ± 0.051 = [6.739, 6.841]."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["July 2026 national WIC participation forecast","Prior/update/interval: persistence prior = 6.765 million, using the official FY2023-FY2025 annual reference class and November 2025 preliminary monthly context; adjustments are +0.020 million for continuing momentum, +0.010 million for outreach/modernization, and -0.005 million for summer churn, giving 6.765 + 0.020 + 0.010 - 0.005 = 6.790 million. An exact monthly successive-change sample was not fetched, so sigma = 0.040 million is an explicit judgmental first-print uncertainty assumption rather than an empirical sample estimate. Applying the promoted normal approximation gives 1.28*sigma = 1.28*0.040 = 0.051 million and an 80% interval of 6.790 ± 0.051 = [6.739, 6.841]."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: wic-participation-july-2026\nrunLabel: Headline\nresolutionDate: 2026-10-22\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-participation-july-2026.2026-07-10T23-18-11Z.4a1e26889e62e88b","runId":"run.snap-participation-july-2026.2026-07-10T23-18-11Z.4a1e26889e62e88b","predictionId":"snap-participation-july-2026","specId":"spec.snap-participation-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Tool call: Fetch same-variant historical Persons observations from the official national monthly table.","The reference class/base rate is 24 successive monthly changes from March 2024 through March 2026 in the same FNS national Persons series and displayed variant. Participation moved from 41.572 million to 37.298 million, implying a mean monthly change of -0.178 million. The latest five-change mean, from 41.092 million in October 2025 to 37.298 million in March 2026, was -0.759 million. These published historical observations anchor the model but do not replace the target's strict first-print rule."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 2 source-context item(s), activity log present.","evidence":["The resolver is the first official national monthly SNAP table's Persons value for July 2026, not a quality-control release, state subtotal, household count, annual average, or later revision. The stable series page is the exact FNS SNAP Data Tables page; the official-calendar registration fixes publication on 2026-12-07.","Tool call: Fetch the latest USDA FNS national monthly SNAP participation PDF and read the Persons column for FY 2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is the first official national monthly SNAP table's Persons value for July 2026, not a quality-control release, state subtotal, household count, annual average, or later revision. The stable series page is the exact FNS SNAP Data Tables page; the official-calendar registration fixes publication on 2026-12-07.","Tool call: Check official FNS publication metadata and the registered release schedule for the exact monthly table."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.4, distribution present, forecast step count 1.","evidence":["Prior/update/interval: The model is a damped monthly-change persistence prior using the 24-change historical sample. The drift rule gives 70% weight to the long-run mean of -0.178 million and 30% to the latest-five mean of -0.759 million: 0.70*(-0.178) + 0.30*(-0.759) = -0.352 million per month. From the March 2026 level of 37.298 million, four transitions imply 37.298 + 4*(-0.352) = 35.890 million, rounded to 35.9. The 24 changes have sum about -4.273 million and sum of squares about 5.053, so sample sigma = sqrt((5.053 - 24*(-0.178)^2)/23) = 0.432 million. Innovation-only four-month 80% half-width is 1.28*sigma*sqrt(4) = 1.28*0.432*2 = 1.106 million. Adding approximately 0.5 million of drift-selection and first-print model uncertainty in quadrature gives sqrt(1.106^2 + 0.5^2) = 1.214 million, rounded to 1.2. Final implied bounds are 35.9 - 1.2 = 34.7 and 35.9 + 1.2 = 37.1 million.","Upside risk comes from the March deceleration persisting or recent declines reversing; participation above 37.1 million would land outside the interval. Downside risk comes from continuation of the unusually steep latest-five momentum; participation below 34.7 million would land outside the interval. No catalog point estimate or interval was used as forecast evidence."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Upside risk comes from the March deceleration persisting or recent declines reversing; participation above 37.1 million would land outside the interval. Downside risk comes from continuation of the unusually steep latest-five momentum; participation below 34.7 million would land outside the interval. No catalog point estimate or interval was used as forecast evidence.","Review disposition: Accepted the critiques by removing the unsupported policy mechanism, making the momentum shrinkage formula explicit, documenting the historical base rate and latest-five mean, and adding drift/model uncertainty to the interval. Resolver wording and official date were retained."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The reference class/base rate is 24 successive monthly changes from March 2024 through March 2026 in the same FNS national Persons series and displayed variant. Participation moved from 41.572 million to 37.298 million, implying a mean monthly change of -0.178 million. The latest five-change mean, from 41.092 million in October 2025 to 37.298 million in March 2026, was -0.759 million. These published historical observations anchor the model but do not replace the target's strict first-print rule.","Prior/update/interval: The model is a damped monthly-change persistence prior using the 24-change historical sample. The drift rule gives 70% weight to the long-run mean of -0.178 million and 30% to the latest-five mean of -0.759 million: 0.70*(-0.178) + 0.30*(-0.759) = -0.352 million per month. From the March 2026 level of 37.298 million, four transitions imply 37.298 + 4*(-0.352) = 35.890 million, rounded to 35.9. The 24 changes have sum about -4.273 million and sum of squares about 5.053, so sample sigma = sqrt((5.053 - 24*(-0.178)^2)/23) = 0.432 million. Innovation-only four-month 80% half-width is 1.28*sigma*sqrt(4) = 1.28*0.432*2 = 1.106 million. Adding approximately 0.5 million of drift-selection and first-print model uncertainty in quadrature gives sqrt(1.106^2 + 0.5^2) = 1.214 million, rounded to 1.2. Final implied bounds are 35.9 - 1.2 = 34.7 and 35.9 + 1.2 = 37.1 million."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: July 2026 national SNAP participation","Prior/update/interval: The model is a damped monthly-change persistence prior using the 24-change historical sample. The drift rule gives 70% weight to the long-run mean of -0.178 million and 30% to the latest-five mean of -0.759 million: 0.70*(-0.178) + 0.30*(-0.759) = -0.352 million per month. From the March 2026 level of 37.298 million, four transitions imply 37.298 + 4*(-0.352) = 35.890 million, rounded to 35.9. The 24 changes have sum about -4.273 million and sum of squares about 5.053, so sample sigma = sqrt((5.053 - 24*(-0.178)^2)/23) = 0.432 million. Innovation-only four-month 80% half-width is 1.28*sigma*sqrt(4) = 1.28*0.432*2 = 1.106 million. Adding approximately 0.5 million of drift-selection and first-print model uncertainty in quadrature gives sqrt(1.106^2 + 0.5^2) = 1.214 million, rounded to 1.2. Final implied bounds are 35.9 - 1.2 = 34.7 and 35.9 + 1.2 = 37.1 million."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-participation-july-2026\nrunLabel: Headline\nresolutionDate: 2026-12-07\ntraceLineCount: 13\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.wic-participation-june-2026.2026-07-10T17-50-44Z.f0804b6cc7d20387","runId":"run.wic-participation-june-2026.2026-07-10T17-50-44Z.f0804b6cc7d20387","predictionId":"wic-participation-june-2026","specId":"spec.wic-participation-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool call: Fetch same-variant historical March and June national total-participation observations from the official WIC monthly table.","The reference class is the three prior March-to-June changes in the same official total-participation series: +0.111113 million in 2023, +0.055911 million in 2024, and +0.032364 million in 2025. Their base-rate mean is +0.066463 million."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The target is national total WIC participants for June 2026, not an annual fiscal-year measure or participant-category subtotal. It resolves from the first official monthly national-level print. The official release calendar schedules this target for 2026-09-18; the ledger window of 2026-09-10 through 2026-09-18 is consistent with that date.","Tool result: The official table reports 6,712,611 participants in Dec 2025, 6,696,300 in Jan 2026, 6,664,580 in Feb 2026, and 6,701,661 in Mar 2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is national total WIC participants for June 2026, not an annual fiscal-year measure or participant-category subtotal. It resolves from the first official monthly national-level print. The official release calendar schedules this target for 2026-09-18; the ledger window of 2026-09-10 through 2026-09-18 is consistent with that date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.1, distribution present, forecast step count 1.","evidence":["Prior/update/interval: the persistence-plus-seasonality prior uses the three fetched, horizon-matched March-to-June changes, giving an unadjusted prior of 6.701661 + 0.066463 = 6.768124 million. I apply judgmental shrinkage of 0.018124 million, about 27% of the seasonal increment, because the FY2026 level is lower and the March rebound only partly offsets winter attrition, yielding 6.750000 million. Across the three March-to-June changes, the sample sigma = 0.0404 million; the 80% half-width is approximately 1.28*sigma = 1.28*0.0404 = 0.0517 million, rounded to 0.052. This gives 6.750-0.052=6.698 and 6.750+0.052=6.802.","Upside risk comes from a spring enrollment rebound near the 2023 increase and would land above the interval if participation exceeds 6.802 million. Downside risk comes from renewed attrition resembling part of the 0.138204 million October-to-November 2025 drop and would land below the interval if participation falls under 6.698 million. These are concrete outside-the-interval scenarios."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level is anchored at March's 6.701661 million. Momentum improved in March by 0.037081 million after four monthly declines, while the one-off October-to-November drop of 0.138204 million and continued lower FY2026 level argue against applying the full seasonal base rate. Policy mechanisms such as eligibility-guideline and food-package changes are unlikely to reverse the level break fully by June.","Prior/update/interval: the persistence-plus-seasonality prior uses the three fetched, horizon-matched March-to-June changes, giving an unadjusted prior of 6.701661 + 0.066463 = 6.768124 million. I apply judgmental shrinkage of 0.018124 million, about 27% of the seasonal increment, because the FY2026 level is lower and the March rebound only partly offsets winter attrition, yielding 6.750000 million. Across the three March-to-June changes, the sample sigma = 0.0404 million; the 80% half-width is approximately 1.28*sigma = 1.28*0.0404 = 0.0517 million, rounded to 0.052. This gives 6.750-0.052=6.698 and 6.750+0.052=6.802."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: the persistence-plus-seasonality prior uses the three fetched, horizon-matched March-to-June changes, giving an unadjusted prior of 6.701661 + 0.066463 = 6.768124 million. I apply judgmental shrinkage of 0.018124 million, about 27% of the seasonal increment, because the FY2026 level is lower and the March rebound only partly offsets winter attrition, yielding 6.750000 million. Across the three March-to-June changes, the sample sigma = 0.0404 million; the 80% half-width is approximately 1.28*sigma = 1.28*0.0404 = 0.0517 million, rounded to 0.052. This gives 6.750-0.052=6.698 and 6.750+0.052=6.802.","Upside risk comes from a spring enrollment rebound near the 2023 increase and would land above the interval if participation exceeds 6.802 million. Downside risk comes from renewed attrition resembling part of the 0.138204 million October-to-November 2025 drop and would land below the interval if participation falls under 6.698 million. These are concrete outside-the-interval scenarios."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["June 2026 WIC participation forecast","Prior/update/interval: the persistence-plus-seasonality prior uses the three fetched, horizon-matched March-to-June changes, giving an unadjusted prior of 6.701661 + 0.066463 = 6.768124 million. I apply judgmental shrinkage of 0.018124 million, about 27% of the seasonal increment, because the FY2026 level is lower and the March rebound only partly offsets winter attrition, yielding 6.750000 million. Across the three March-to-June changes, the sample sigma = 0.0404 million; the 80% half-width is approximately 1.28*sigma = 1.28*0.0404 = 0.0517 million, rounded to 0.052. This gives 6.750-0.052=6.698 and 6.750+0.052=6.802."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: wic-participation-june-2026\nrunLabel: Headline\nresolutionDate: 2026-09-18\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-participation-june-2026.2026-07-10T17-52-58Z.2e5ba0d2187c2989","runId":"run.snap-participation-june-2026.2026-07-10T17-52-58Z.2e5ba0d2187c2989","predictionId":"snap-participation-june-2026","specId":"spec.snap-participation-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["The outside-view base rate is persistence with drift for a slowly moving administrative caseload. The 13 monthly changes from February 2025 through March 2026 average -0.376 million, while October 2025 through March 2026 participation fell 3.794 million. The level anchor is therefore March's 37.298 million; momentum remains negative, with the smaller March decline supporting partial moderation.","Prior/update/interval: persistence-with-drift prior anchored at March 2026 = 37.298271 million. Apply momentum of -0.580 million per month for April-June (-1.740), moderation of +0.100 million per month (+0.300), and a policy-mechanism adjustment of -0.308, for a net update of -1.748 and point = 37.298 - 1.748 = 35.550 million. The historical sample is 13 successive monthly changes from February 2025 through March 2026 in the official table; vintage status for every historical observation is not separately identified. Its sample standard deviation is sigma = 0.376 million. The one-month 80% half-width is 1.28*sigma = 1.28*0.376 = 0.482 million; scaling over three months gives 0.482*sqrt(3) = 0.835, rounded to 0.840. Final implied bounds are 35.550 +/- 0.840 = [34.710, 36.390]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The resolver is the unadjusted national Persons field for June 2026 in the USDA Food and Nutrition Service SNAP monthly participation table, not an annual quality-control measure. The official table reports persons in thousands; the cell converts that figure to millions. The first print is binding, with no correction-day grace period.","Tool call: Fetch the USDA FNS SNAP national monthly participation table and read the latest FY2026 Persons observations."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is the unadjusted national Persons field for June 2026 in the USDA Food and Nutrition Service SNAP monthly participation table, not an annual quality-control measure. The official table reports persons in thousands; the cell converts that figure to millions. The first print is binding, with no correction-day grace period.","Tool call: Verify release timing against the official FNS program-data schedule and target release window."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.68, distribution present, forecast step count 1.","evidence":["Mechanisms are separated into the March level, recent downward momentum, moderation as declines decelerate, and a negative adjustment for tighter eligibility and work-rule mechanisms. Administrative reporting volatility remains a secondary source of uncertainty.","Prior/update/interval: persistence-with-drift prior anchored at March 2026 = 37.298271 million. Apply momentum of -0.580 million per month for April-June (-1.740), moderation of +0.100 million per month (+0.300), and a policy-mechanism adjustment of -0.308, for a net update of -1.748 and point = 37.298 - 1.748 = 35.550 million. The historical sample is 13 successive monthly changes from February 2025 through March 2026 in the official table; vintage status for every historical observation is not separately identified. Its sample standard deviation is sigma = 0.376 million. The one-month 80% half-width is 1.28*sigma = 1.28*0.376 = 0.482 million; scaling over three months gives 0.482*sqrt(3) = 0.835, rounded to 0.840. Final implied bounds are 35.550 +/- 0.840 = [34.710, 36.390]."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The outside-view base rate is persistence with drift for a slowly moving administrative caseload. The 13 monthly changes from February 2025 through March 2026 average -0.376 million, while October 2025 through March 2026 participation fell 3.794 million. The level anchor is therefore March's 37.298 million; momentum remains negative, with the smaller March decline supporting partial moderation.","Mechanisms are separated into the March level, recent downward momentum, moderation as declines decelerate, and a negative adjustment for tighter eligibility and work-rule mechanisms. Administrative reporting volatility remains a secondary source of uncertainty."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Mechanisms are separated into the March level, recent downward momentum, moderation as declines decelerate, and a negative adjustment for tighter eligibility and work-rule mechanisms. Administrative reporting volatility remains a secondary source of uncertainty.","Upside risk: faster stabilization in enrollment or delayed implementation of tighter eligibility rules would land above 36.39 million. Downside risk: an average decline greater than about 0.863 million per month from March through June, broad recertification losses, or unusually aggressive enforcement would put June below 34.71 million, outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["June 2026 national SNAP participation forecast","Prior/update/interval: persistence-with-drift prior anchored at March 2026 = 37.298271 million. Apply momentum of -0.580 million per month for April-June (-1.740), moderation of +0.100 million per month (+0.300), and a policy-mechanism adjustment of -0.308, for a net update of -1.748 and point = 37.298 - 1.748 = 35.550 million. The historical sample is 13 successive monthly changes from February 2025 through March 2026 in the official table; vintage status for every historical observation is not separately identified. Its sample standard deviation is sigma = 0.376 million. The one-month 80% half-width is 1.28*sigma = 1.28*0.376 = 0.482 million; scaling over three months gives 0.482*sqrt(3) = 0.835, rounded to 0.840. Final implied bounds are 35.550 +/- 0.840 = [34.710, 36.390]."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-participation-june-2026\nrunLabel: Headline\nresolutionDate: 2026-11-03\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bea-disposable-personal-income-level-june-2026.2026-07-10T12-39-29Z.b41d192e1a20545a","runId":"run.bea-disposable-personal-income-level-june-2026.2026-07-10T12-39-29Z.b41d192e1a20545a","predictionId":"bea-disposable-personal-income-level-june-2026","specId":"spec.bea-disposable-personal-income-level-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate / reference class: using successive monthly DSPI level changes from Feb 2023 through May 2026 gives a 40-observation recent-cycle reference class. The mean change is 89.7 billion, while the last 12 changes average 77.4 billion; I weight the broader 2023-2026 base rate more because May had a rebound after April weakness but no obvious June-specific fiscal cliff is visible in the public release summary.","Prior/update/interval: persistence-plus-mean-change model using May 2026 DSPI 23651.7 plus the 2023-2026 average monthly change of 89.7 gives 23741.4. Historical sample is the 40 successive monthly changes from Feb 2023-May 2026; sigma = 83.6 from those successive changes, so the 80 percent normal half-width is roughly 1.28*sigma = 107.0. No widening beyond that is applied because this is a level series with recent volatility already including negative and large positive monthly moves; implied 80 percent bounds are 23741.4 - 107.0 = 23634.4 and 23741.4 + 107.0 = 23848.3."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing and exact resolver: the target is BEA disposable personal income, DSPI / account code A067RC, monthly, seasonally adjusted annual rate, billions of dollars, first print for June 2026. The canonical source binding resolves via ALFRED generic-url field DSPI at the supplied URL, while BEA is the underlying agency provenance. The target remains DSPI/A067RC regardless of the Table 1 versus Table 2.6 label discrepancy in surrounding metadata.","Tool result: Fetched official release numbers: for May 2026, personal income increased 181.6 billion, DPI increased 164.9 billion or 0.7 percent, PCE increased 156.1 billion or 0.7 percent, and personal saving was 704.2 billion with a 3.0 percent saving rate."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: the target is BEA disposable personal income, DSPI / account code A067RC, monthly, seasonally adjusted annual rate, billions of dollars, first print for June 2026. The canonical source binding resolves via ALFRED generic-url field DSPI at the supplied URL, while BEA is the underlying agency provenance. The target remains DSPI/A067RC regardless of the Table 1 versus Table 2.6 label discrepancy in surrounding metadata.","Tool call: Opened BEA release schedule for 2026 Personal Income and Outlays"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 213.9, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence-plus-mean-change model using May 2026 DSPI 23651.7 plus the 2023-2026 average monthly change of 89.7 gives 23741.4. Historical sample is the 40 successive monthly changes from Feb 2023-May 2026; sigma = 83.6 from those successive changes, so the 80 percent normal half-width is roughly 1.28*sigma = 107.0. No widening beyond that is applied because this is a level series with recent volatility already including negative and large positive monthly moves; implied 80 percent bounds are 23741.4 - 107.0 = 23634.4 and 23741.4 + 107.0 = 23848.3.","Counter-considerations: upside risk is a June continuation of May's proprietors' income and transfer-receipt strength, which would land above the interval if DSPI rises more than about 196.6 billion from May. Downside risk is a reversal in farm/proprietors' income, asset income, or tax withholding that would land below the interval if DSPI falls more than about 17.3 billion from May; outside the interval would most likely reflect a discrete tax, transfer, or annual-update effect not visible in the May release."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate / reference class: using successive monthly DSPI level changes from Feb 2023 through May 2026 gives a 40-observation recent-cycle reference class. The mean change is 89.7 billion, while the last 12 changes average 77.4 billion; I weight the broader 2023-2026 base rate more because May had a rebound after April weakness but no obvious June-specific fiscal cliff is visible in the public release summary.","Current-release adjustment: May 2026 was strong because DPI rose 164.9 billion and DSPI rose 164.8 billion, with wages and salaries at 13388.8 billion and proprietors' income at 2193.6 billion. I do not extrapolate the full May jump, but the level and labor-income trend make a positive June change more likely than a flat or negative one."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate / reference class: using successive monthly DSPI level changes from Feb 2023 through May 2026 gives a 40-observation recent-cycle reference class. The mean change is 89.7 billion, while the last 12 changes average 77.4 billion; I weight the broader 2023-2026 base rate more because May had a rebound after April weakness but no obvious June-specific fiscal cliff is visible in the public release summary.","Current-release adjustment: May 2026 was strong because DPI rose 164.9 billion and DSPI rose 164.8 billion, with wages and salaries at 13388.8 billion and proprietors' income at 2193.6 billion. I do not extrapolate the full May jump, but the level and labor-income trend make a positive June change more likely than a flat or negative one."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["BEA DSPI June 2026 Forecast","Prior/update/interval: persistence-plus-mean-change model using May 2026 DSPI 23651.7 plus the 2023-2026 average monthly change of 89.7 gives 23741.4. Historical sample is the 40 successive monthly changes from Feb 2023-May 2026; sigma = 83.6 from those successive changes, so the 80 percent normal half-width is roughly 1.28*sigma = 107.0. No widening beyond that is applied because this is a level series with recent volatility already including negative and large positive monthly moves; implied 80 percent bounds are 23741.4 - 107.0 = 23634.4 and 23741.4 + 107.0 = 23848.3."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bea-disposable-personal-income-level-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-30\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bea-disposable-personal-income-level-june-2026.2026-07-10T14-16-39Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-ladder-2026-07-10t14-16-39z.ac3510719c679918","runId":"run.bea-disposable-personal-income-level-june-2026.2026-07-10T14-16-39Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-ladder-2026-07-10t14-16-39z.ac3510719c679918","predictionId":"bea-disposable-personal-income-level-june-2026","specId":"spec.bea-disposable-personal-income-level-june-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The reference class and base rate are the four latest successive DSPI changes: -13.5, +128.0, -23.5, and +164.8 billion. Their mean is +64.0 billion and median is +57.3 billion, implying an unadjusted persistence anchor of 23709.0. The unusually large May change included an identified farm-relief contribution, so extrapolating the May increase mechanically would overstate the base rate.","The 23651.7 May level is the starting point. The +57.3 billion median-change prior already includes ordinary compensation, taxes, transfers, and other recurring components. I therefore apply only a coarse judgmental net tilt rather than independently rebuilding total income: about +30 billion for June's positive hourly and weekly earnings signal relative to the weak months in the small reference class, offset by about -10 billion for likely normalization of the explicitly identified May farm-relief boost. These rounded amounts are directional adjustments, not source-derived component estimates; weak payroll growth prevents a larger compensation tilt."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["The target is BEA account code A067RC / DSPI: current-dollar disposable personal income for June 2026, measured in billions of dollars at a seasonally adjusted annual rate and resolved on the first print. BEA's official schedule and May release specify July 30, 2026, at 8:30 a.m. EDT for Personal Income and Outlays, June 2026. The retained ALFRED URL has a June 25 vintage that predates the target release and therefore cannot contain the June first print; this is a concrete ledger discrepancy, but the supplied binding and strict first-print rule are retained.","Tool result: DSPI was 23395.9 in January 2026, 23382.4 in February, 23510.4 in March, 23486.9 in April, and 23651.7 in May, all billions of dollars at a seasonally adjusted annual rate."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is BEA account code A067RC / DSPI: current-dollar disposable personal income for June 2026, measured in billions of dollars at a seasonally adjusted annual rate and resolved on the first print. BEA's official schedule and May release specify July 30, 2026, at 8:30 a.m. EDT for Personal Income and Outlays, June 2026. The retained ALFRED URL has a June 25 vintage that predates the target release and therefore cannot contain the June first print; this is a concrete ledger discrepancy, but the supplied binding and strict first-print rule are retained.","Tool call: Inspect BEA's May 2026 Personal Income and Outlays first release for momentum and one-off components."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 240, distribution present, forecast step count 1.","evidence":["Prior/update/interval: The model is a recent-change persistence prior using January-May 2026 DSPI history. Successive changes are -13.5, +128.0, -23.5, and +164.8; their sample standard deviation is sigma = 96.5 billion. The Gaussian-reference 80% half-width is roughly 1.28*sigma = 1.28*96.5 = 123.5 billion. Starting from 23651.7, the +57.3 median-change prior plus a rounded +30 billion earnings tilt and rounded -10 billion relief-normalization offset gives 23651.7 + 77.3 = 23729.0, rounded to the ladder's 23730.0 median. The ladder-implied interval is mildly asymmetric around that point: 110.0 billion below and 130.0 billion above. Its average half-width is 120.0 billion, nearly equal to the 123.5 billion sigma-based half-width.","Upside risk is another unusually large transfer, farm-support, proprietors' income, or dividend contribution combined with solid compensation; that could put the first print above 23860.0. Downside risk is a stronger reversal of May relief income, unexpectedly high personal current taxes, or broader compensation weakness; a sufficiently large reversal would land below 23620.0 and therefore outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Inspect BEA's May 2026 Personal Income and Outlays first release for momentum and one-off components."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The target is BEA account code A067RC / DSPI: current-dollar disposable personal income for June 2026, measured in billions of dollars at a seasonally adjusted annual rate and resolved on the first print. BEA's official schedule and May release specify July 30, 2026, at 8:30 a.m. EDT for Personal Income and Outlays, June 2026. The retained ALFRED URL has a June 25 vintage that predates the target release and therefore cannot contain the June first print; this is a concrete ledger discrepancy, but the supplied binding and strict first-print rule are retained.","Tool result: BEA reported that May DPI increased 164.9 billion, or 0.7 percent, while personal income increased 181.6 billion. BEA attributed part of the increase to a second round of farm Supplemental Disaster Relief Program payments, while compensation also increased."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["June 2026 disposable personal income forecast","The 23651.7 May level is the starting point. The +57.3 billion median-change prior already includes ordinary compensation, taxes, transfers, and other recurring components. I therefore apply only a coarse judgmental net tilt rather than independently rebuilding total income: about +30 billion for June's positive hourly and weekly earnings signal relative to the weak months in the small reference class, offset by about -10 billion for likely normalization of the explicitly identified May farm-relief boost. These rounded amounts are directional adjustments, not source-derived component estimates; weak payroll growth prevents a larger compensation tilt."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bea-disposable-personal-income-level-june-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-07-30\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bea-disposable-personal-income-level-june-2026.2026-07-10T15-14-01Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-fast-2026-07-10t15-14-01z.974fab70c38f570a","runId":"run.bea-disposable-personal-income-level-june-2026.2026-07-10T15-14-01Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-fast-2026-07-10t15-14-01z.974fab70c38f570a","predictionId":"bea-disposable-personal-income-level-june-2026","specId":"spec.bea-disposable-personal-income-level-june-2026","runLabel":"Fast rollout 2 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The base rate and reference class are short-run monthly changes in the same DSPI level series. Recent changes were +164.8 from April to May, -23.5 from March to April, +128.0 from February to March, -13.5 from January to February, +230.0 from December to January, and +55.1 from November to December.","Prior/update/interval: the persistence prior starts from the latest official DSPI level of 23651.7; the historical sample is the 12 successive changes from June 2025 through May 2026: 41.5, 139.0, 105.9, 82.6, -28.8, 48.0, 55.1, 230.0, -13.5, 128.0, -23.5, and 164.8. Their sample standard deviation is sigma = 80.0, so the 80% half-width is roughly 1.28*sigma = 102.4. Combining persistence, wage momentum, and partial farm-payment normalization gives a point of 23730; the interval is 23730 +/- 100, or 23630 to 23830. No extra widening is applied because the interval already reflects the high-dispersion monthly-change regime."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The target is the first official print for BEA series DSPI, account code A067RC, corresponding to Table 2.6 current-dollar disposable personal income at a seasonally adjusted annual rate. The ledger retains the supplied ALFRED binding, while noting that its 2026-06-25 vintage date appears to precede the June release.","Tool result: BEA's official 2026 release schedule lists Personal Income and Outlays, June 2026, on July 30, 2026, at 8:30 a.m.; the May release states the same next-release date."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The target is the first official print for BEA series DSPI, account code A067RC, corresponding to Table 2.6 current-dollar disposable personal income at a seasonally adjusted annual rate. The ledger retains the supplied ALFRED binding, while noting that its 2026-06-25 vintage date appears to precede the June release.","Tool call: BEA release-calendar lookup for the target resolution date"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 200, distribution present, forecast step count 1.","evidence":["Prior/update/interval: the persistence prior starts from the latest official DSPI level of 23651.7; the historical sample is the 12 successive changes from June 2025 through May 2026: 41.5, 139.0, 105.9, 82.6, -28.8, 48.0, 55.1, 230.0, -13.5, 128.0, -23.5, and 164.8. Their sample standard deviation is sigma = 80.0, so the 80% half-width is roughly 1.28*sigma = 102.4. Combining persistence, wage momentum, and partial farm-payment normalization gives a point of 23730; the interval is 23730 +/- 100, or 23630 to 23830. No extra widening is applied because the interval already reflects the high-dispersion monthly-change regime.","Point calculation: 23651.7 latest level plus an approximately 78.3 billion normalized June increase equals 23730 after rounding. Interval calculation: sigma = 80.0 and 1.28*sigma = 102.4, rounded to an approximately 100 billion half-width for the one-decimal official series scale."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["May's increase was unusually influenced by farm-proprietor income and a second round of Supplemental Disaster Relief Program payments, while BEA said compensation was also led by private wages and salaries. I therefore retain positive momentum but partially normalize the May one-off rather than extrapolating the full $164.8 billion change.","Prior/update/interval: the persistence prior starts from the latest official DSPI level of 23651.7; the historical sample is the 12 successive changes from June 2025 through May 2026: 41.5, 139.0, 105.9, 82.6, -28.8, 48.0, 55.1, 230.0, -13.5, 128.0, -23.5, and 164.8. Their sample standard deviation is sigma = 80.0, so the 80% half-width is roughly 1.28*sigma = 102.4. Combining persistence, wage momentum, and partial farm-payment normalization gives a point of 23730; the interval is 23730 +/- 100, or 23630 to 23830. No extra widening is applied because the interval already reflects the high-dispersion monthly-change regime."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["May's increase was unusually influenced by farm-proprietor income and a second round of Supplemental Disaster Relief Program payments, while BEA said compensation was also led by private wages and salaries. I therefore retain positive momentum but partially normalize the May one-off rather than extrapolating the full $164.8 billion change.","The main downside risk is a rapid normalization of farm-proprietor relief effects combined with weaker compensation, which would push the print below 23630. The upside risk is another large transfer or compensation impulse, which would land above 23830; either outcome would be outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for BEA DSPI, June 2026","Prior/update/interval: the persistence prior starts from the latest official DSPI level of 23651.7; the historical sample is the 12 successive changes from June 2025 through May 2026: 41.5, 139.0, 105.9, 82.6, -28.8, 48.0, 55.1, 230.0, -13.5, 128.0, -23.5, and 164.8. Their sample standard deviation is sigma = 80.0, so the 80% half-width is roughly 1.28*sigma = 102.4. Combining persistence, wage momentum, and partial farm-payment normalization gives a point of 23730; the interval is 23730 +/- 100, or 23630 to 23830. No extra widening is applied because the interval already reflects the high-dispersion monthly-change regime."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bea-disposable-personal-income-level-june-2026\nrunLabel: Fast rollout 2 of 3\nresolutionDate: 2026-07-30\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bea-disposable-personal-income-level-june-2026.2026-07-10T15-37-53Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-fast-2026-07-10t15-37-53z.da5519a02d9d3d53","runId":"run.bea-disposable-personal-income-level-june-2026.2026-07-10T15-37-53Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-fast-2026-07-10t15-37-53z.da5519a02d9d3d53","predictionId":"bea-disposable-personal-income-level-june-2026","specId":"spec.bea-disposable-personal-income-level-june-2026","runLabel":"Fast rollout 1 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.51,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The target is BEA NIPA Table 2.6, DSPI / account code A067RC: monthly current-dollar disposable personal income, billions of dollars at a seasonally adjusted annual rate. The resolver remains the retained ledger first-print ALFRED binding; its 2026-06-25 vintage is the prior-May print, a noted binding discrepancy rather than a reason to alter the target.","The reference class/base rate is the recent monthly DSPI change distribution: the four successive changes from January through May were -13.5, +128.0, -23.5, and +164.8 billion. May's unusually large increase included a second round of USDA Supplemental Disaster Relief Program payments, so the persistence prior is tempered rather than extrapolating May's 0.7 percent gain."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The target is BEA NIPA Table 2.6, DSPI / account code A067RC: monthly current-dollar disposable personal income, billions of dollars at a seasonally adjusted annual rate. The resolver remains the retained ledger first-print ALFRED binding; its 2026-06-25 vintage is the prior-May print, a noted binding discrepancy rather than a reason to alter the target.","Tool result: BEA's official schedule lists Personal Income and Outlays, June 2026, for July 30, 2026 at 8:30 AM; the current May release also states the next release is July 30, 2026 at 8:30 a.m. EDT."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["June 2026 BEA disposable personal income first-print forecast","The target is BEA NIPA Table 2.6, DSPI / account code A067RC: monthly current-dollar disposable personal income, billions of dollars at a seasonally adjusted annual rate. The resolver remains the retained ledger first-print ALFRED binding; its 2026-06-25 vintage is the prior-May print, a noted binding discrepancy rather than a reason to alter the target."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 247, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is May DSPI of 23,651.7; the historical sample is January-May 2026 same-variant DSPI levels, with successive changes -13.5, +128.0, -23.5, +164.8 and sample sigma = 96.5 billion. The June BLS signal of +57,000 payrolls and +0.3% hourly earnings supports a modest compensation gain, while non-recurrence of May farm relief offsets much of it; the combined update is +49.3 to 23,701.0. The 80% half-width is 1.28*96.5 = 123.5, giving 23,577.5 to 23,824.5.","upside risk: another large farm-payment or transfer increase plus stronger compensation would land above the interval. downside risk: a larger withdrawal of farm income, tax increase, or transfer decline would land below the interval. A June DSPI change beyond roughly plus or minus 123.5 billion from the point would be outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool result: BEA reported May DPI increased $164.9 billion (0.7 percent), personal income increased $181.6 billion (0.7 percent), and PCE increased $156.1 billion (0.7 percent); BEA attributed the income increase primarily to farm proprietors' income and compensation.","The reference class/base rate is the recent monthly DSPI change distribution: the four successive changes from January through May were -13.5, +128.0, -23.5, and +164.8 billion. May's unusually large increase included a second round of USDA Supplemental Disaster Relief Program payments, so the persistence prior is tempered rather than extrapolating May's 0.7 percent gain."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["June 2026 BEA disposable personal income first-print forecast","Prior/update/interval: persistence prior is May DSPI of 23,651.7; the historical sample is January-May 2026 same-variant DSPI levels, with successive changes -13.5, +128.0, -23.5, +164.8 and sample sigma = 96.5 billion. The June BLS signal of +57,000 payrolls and +0.3% hourly earnings supports a modest compensation gain, while non-recurrence of May farm relief offsets much of it; the combined update is +49.3 to 23,701.0. The 80% half-width is 1.28*96.5 = 123.5, giving 23,577.5 to 23,824.5."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bea-disposable-personal-income-level-june-2026\nrunLabel: Fast rollout 1 of 3\nresolutionDate: 2026-07-30\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bea-disposable-personal-income-level-june-2026.2026-07-10T15-41-38Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-fast-2026-07-10t15-41-38z.1fff3e466c23cd60","runId":"run.bea-disposable-personal-income-level-june-2026.2026-07-10T15-41-38Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-fast-2026-07-10t15-41-38z.1fff3e466c23cd60","predictionId":"bea-disposable-personal-income-level-june-2026","specId":"spec.bea-disposable-personal-income-level-june-2026","runLabel":"Fast rollout 2 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The target is BEA NIPA Table 2.6 monthly disposable personal income, account code A067RC / DSPI: current-dollar billions of dollars at a seasonally adjusted annual rate. It resolves to the June first print only; later BEA revisions are excluded. The retained ledger ALFRED URL is a generic-url first-print binding whose supplied vintage date is the prior May print, while BEA remains the underlying official producer.","Base rate/reference class: over the latest 12 observed monthly DSPI changes from June 2025 through May 2026, the average gain is about $77.4 billion SAAR. The most recent +$164.8 billion level increase is above that reference class and followed BEA's noted second round of Supplemental Disaster Relief Program payments, so it is not extrapolated in full."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The target is BEA NIPA Table 2.6 monthly disposable personal income, account code A067RC / DSPI: current-dollar billions of dollars at a seasonally adjusted annual rate. It resolves to the June first print only; later BEA revisions are excluded. The retained ledger ALFRED URL is a generic-url first-print binding whose supplied vintage date is the prior May print, while BEA remains the underlying official producer.","Tool call: Fetched BEA's May 2026 Personal Income and Outlays release for the latest official DPI change and release details."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["BEA disposable personal income (DSPI), June 2026 first print","The target is BEA NIPA Table 2.6 monthly disposable personal income, account code A067RC / DSPI: current-dollar billions of dollars at a seasonally adjusted annual rate. It resolves to the June first print only; later BEA revisions are excluded. The retained ledger ALFRED URL is a generic-url first-print binding whose supplied vintage date is the prior May print, while BEA remains the underlying official producer."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 204.8, distribution present, forecast step count 1.","evidence":["Tool call: Fetched BEA's May 2026 Personal Income and Outlays release for the latest official DPI change and release details.","Prior/update/interval: persistence prior is the latest DSPI level of 23,651.7; the historical sample is the 12 successive same-variant monthly DSPI changes from June 2025-May 2026, with mean +77.4 and sigma = 80.0 billion. A normal 80% half-width is 1.28*80.0 = 102.4. I apply a -9.1 billion update versus that mean because May's $164.9 billion DPI surge included a farm-payment mechanism unlikely to recur at the same scale, while compensation and ordinary nominal growth keep the expected June change positive: 23,651.7 + 68.3 = 23,720.0, yielding 23,720.0 +/- 102.4 = [23,617.6, 23,822.4]."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior is the latest DSPI level of 23,651.7; the historical sample is the 12 successive same-variant monthly DSPI changes from June 2025-May 2026, with mean +77.4 and sigma = 80.0 billion. A normal 80% half-width is 1.28*80.0 = 102.4. I apply a -9.1 billion update versus that mean because May's $164.9 billion DPI surge included a farm-payment mechanism unlikely to recur at the same scale, while compensation and ordinary nominal growth keep the expected June change positive: 23,651.7 + 68.3 = 23,720.0, yielding 23,720.0 +/- 102.4 = [23,617.6, 23,822.4]."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["upside risk: another unusually large transfer or farm-payment contribution alongside strong compensation would land above the interval. downside risk: a sharp reversal in transfers, tax timing, or compensation could land below the interval. A monthly change above about +170.7 billion or below about -34.1 billion would be outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: persistence prior is the latest DSPI level of 23,651.7; the historical sample is the 12 successive same-variant monthly DSPI changes from June 2025-May 2026, with mean +77.4 and sigma = 80.0 billion. A normal 80% half-width is 1.28*80.0 = 102.4. I apply a -9.1 billion update versus that mean because May's $164.9 billion DPI surge included a farm-payment mechanism unlikely to recur at the same scale, while compensation and ordinary nominal growth keep the expected June change positive: 23,651.7 + 68.3 = 23,720.0, yielding 23,720.0 +/- 102.4 = [23,617.6, 23,822.4].","upside risk: another unusually large transfer or farm-payment contribution alongside strong compensation would land above the interval. downside risk: a sharp reversal in transfers, tax timing, or compensation could land below the interval. A monthly change above about +170.7 billion or below about -34.1 billion would be outside the interval."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bea-disposable-personal-income-level-june-2026\nrunLabel: Fast rollout 2 of 3\nresolutionDate: 2026-07-30\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bea-disposable-personal-income-level-june-2026.2026-07-10T15-45-51Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-fast-2026-07-10t15-45-51z.9b7665ed971e0ed4","runId":"run.bea-disposable-personal-income-level-june-2026.2026-07-10T15-45-51Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-fast-2026-07-10t15-45-51z.9b7665ed971e0ed4","predictionId":"bea-disposable-personal-income-level-june-2026","specId":"spec.bea-disposable-personal-income-level-june-2026","runLabel":"Fast rollout 3 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Reference class/base rate: recent successive DSPI changes are +164.8, -23.5, +128.0, and -13.5 billion dollars. May is above this short reference class and BEA attributes part of the wider personal-income increase to a second round of Supplemental Disaster Relief Program payments, so I do not extrapolate its full change.","Prior/update/interval: persistence prior is the mean of the four fetched January-to-May successive DSPI changes, +64.0 billion dollars; historical sample is those four changes. Their sample sigma = 96.5 billion dollars, so 1.28*sigma = 123.5 billion dollars for an 80% half-width. I update the +64.0 prior modestly to +68.3 for continuing compensation and nominal-price growth, while allowing May's farm-payment component to fade: 23,651.7 + 68.3 = 23,720.0; 23,720.0 ± 123.5 gives 23,596.5 to 23,843.5."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The target is BEA NIPA Table 2.6 disposable personal income, account A067RC / DSPI: monthly, seasonally adjusted annual rate, in billions of dollars. Resolution is the June first print only; the retained ledger ALFRED URL has a May-2026 vintage-date discrepancy, but the target and its first-print policy remain unchanged.","Tool call: Checked the BEA release schedule entry and cross-checked the immediately preceding official release."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["June 2026 BEA disposable personal income first-print forecast","The target is BEA NIPA Table 2.6 disposable personal income, account A067RC / DSPI: monthly, seasonally adjusted annual rate, in billions of dollars. Resolution is the June first print only; the retained ledger ALFRED URL has a May-2026 vintage-date discrepancy, but the target and its first-print policy remain unchanged."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 247, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is the mean of the four fetched January-to-May successive DSPI changes, +64.0 billion dollars; historical sample is those four changes. Their sample sigma = 96.5 billion dollars, so 1.28*sigma = 123.5 billion dollars for an 80% half-width. I update the +64.0 prior modestly to +68.3 for continuing compensation and nominal-price growth, while allowing May's farm-payment component to fade: 23,651.7 + 68.3 = 23,720.0; 23,720.0 ± 123.5 gives 23,596.5 to 23,843.5.","Counter-consideration: upside risk is another unusually large transfer or farm-proprietor payment, which would land above the interval. downside risk is a reversal of May's temporary income support or weak compensation; a decline exceeding roughly $55 billion from May would land below the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The target is BEA NIPA Table 2.6 disposable personal income, account A067RC / DSPI: monthly, seasonally adjusted annual rate, in billions of dollars. Resolution is the June first print only; the retained ledger ALFRED URL has a May-2026 vintage-date discrepancy, but the target and its first-print policy remain unchanged.","Tool call: Checked BEA's June 25 Personal Income and Outlays release for the latest DPI outcome and contributors."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["June 2026 BEA disposable personal income first-print forecast","Prior/update/interval: persistence prior is the mean of the four fetched January-to-May successive DSPI changes, +64.0 billion dollars; historical sample is those four changes. Their sample sigma = 96.5 billion dollars, so 1.28*sigma = 123.5 billion dollars for an 80% half-width. I update the +64.0 prior modestly to +68.3 for continuing compensation and nominal-price growth, while allowing May's farm-payment component to fade: 23,651.7 + 68.3 = 23,720.0; 23,720.0 ± 123.5 gives 23,596.5 to 23,843.5."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bea-disposable-personal-income-level-june-2026\nrunLabel: Fast rollout 3 of 3\nresolutionDate: 2026-07-30\ntraceLineCount: 12\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bea-disposable-personal-income-level-june-2026.2026-07-10T15-48-42Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-median3-2026-07-10t15-48-42z.e19dc945852d5291","runId":"run.bea-disposable-personal-income-level-june-2026.2026-07-10T15-48-42Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-median3-2026-07-10t15-48-42z.e19dc945852d5291","predictionId":"bea-disposable-personal-income-level-june-2026","specId":"spec.bea-disposable-personal-income-level-june-2026","runLabel":"Median of 3 rollouts","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 5 historical point(s) and implicit outside-view language.","evidence":["Median-of-3 rollout ensemble","Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T15:37:53Z, 2026-07-10T15:41:38Z, 2026-07-10T15:45:51Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 8 source-context item(s), activity log present.","evidence":["Median CDF quantiles: q10 = 23596.0, q50 = 23720.0, q90 = 23825.0. Constituent points [23701.0, 23720.0, 23720.0] with 80% widths [247.0, 204.8, 247.0]; the median interval inherits the central rollout mass rather than averaging tails."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 229, distribution present, forecast step count 1.","evidence":["Median CDF quantiles: q10 = 23596.0, q50 = 23720.0, q90 = 23825.0. Constituent points [23701.0, 23720.0, 23720.0] with 80% widths [247.0, 204.8, 247.0]; the median interval inherits the central rollout mass rather than averaging tails.","Forecast: point 23720, 80% interval [23596, 23825]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T15:37:53Z, 2026-07-10T15:41:38Z, 2026-07-10T15:45:51Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T15:37:53Z, 2026-07-10T15:41:38Z, 2026-07-10T15:45:51Z. Drivers and resolver fields mirror the rollout closest to the median.","Tool result: {rollout_points: [23701.0, 23720.0, 23720.0], rollout_widths: [247.0, 204.8, 247.0], q10: 23596.0, q50: 23720.0, q90: 23825.0}"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bea-disposable-personal-income-level-june-2026\nrunLabel: Median of 3 rollouts\nresolutionDate: 2026-07-30\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bea-disposable-personal-income-level-june-2026.2026-07-10T16-06-23Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-ladder-2026-07-10t16-06-23z.bbfaa560de6d40e4","runId":"run.bea-disposable-personal-income-level-june-2026.2026-07-10T16-06-23Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-ladder-2026-07-10t16-06-23z.bbfaa560de6d40e4","predictionId":"bea-disposable-personal-income-level-june-2026","specId":"spec.bea-disposable-personal-income-level-june-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The reference class and base rate are monthly DSPI level changes after the recent BEA revisions, using Feb 2024 through May 2026 successive changes. The average change over that window is +77.5 billion, while the latest five observations show one-off volatility: Jan 2026 23395.9, Feb 23382.4, Mar 23510.4, Apr 23486.9, and May 23651.7.","Prior/update/interval: persistence prior starts from May DSPI 23651.7 plus the Feb 2024-May 2026 base-rate sample of 28 monthly changes with mean change +77.5. I adjust down by about 19.2 billion for likely fading of May's farm-proprietor boost and tax drag, giving a point change of +58.3 and point level 23651.7 + 58.3 = 23710.0. For realized dispersion, successive changes from Feb 2024-May 2026 sum to 2170.8 over 28 changes, mean = 77.5, sum of squared deviations = 145189.3 over 27 df, so sigma = sqrt(145189.3/27) = 73.3; the normal 80 percent half-width is about 1.28*sigma = 93.8. The ladder-implied half-width is (23840.0 - 23620.0)/2 = 110.0, or 1.17x the sigma half-width, widened modestly because farm-payment and tax timing can dominate one month of DPI."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 7 source-context item(s), activity log present.","evidence":["Framing and exact resolver: target is BEA disposable personal income, DSPI / NIPA account A067RC, current dollars in billions at a seasonally adjusted annual rate for June 2026. I keep the ledger binding to ALFRED DSPI field DSPI and first_print policy even though the supplied vintage_date=2026-06-25 appears to be the May 2026 release vintage rather than the forthcoming June first print.","Tool call: FRED DSPI latest observations and metadata lookup"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["BEA disposable personal income, June 2026 first print","Framing and exact resolver: target is BEA disposable personal income, DSPI / NIPA account A067RC, current dollars in billions at a seasonally adjusted annual rate for June 2026. I keep the ledger binding to ALFRED DSPI field DSPI and first_print policy even though the supplied vintage_date=2026-06-25 appears to be the May 2026 release vintage rather than the forthcoming June first print."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 220, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior starts from May DSPI 23651.7 plus the Feb 2024-May 2026 base-rate sample of 28 monthly changes with mean change +77.5. I adjust down by about 19.2 billion for likely fading of May's farm-proprietor boost and tax drag, giving a point change of +58.3 and point level 23651.7 + 58.3 = 23710.0. For realized dispersion, successive changes from Feb 2024-May 2026 sum to 2170.8 over 28 changes, mean = 77.5, sum of squared deviations = 145189.3 over 27 df, so sigma = sqrt(145189.3/27) = 73.3; the normal 80 percent half-width is about 1.28*sigma = 93.8. The ladder-implied half-width is (23840.0 - 23620.0)/2 = 110.0, or 1.17x the sigma half-width, widened modestly because farm-payment and tax timing can dominate one month of DPI.","Counter-considerations: upside risk is another large farm or transfer-payment impulse plus steady wages, which would land above the interval if June DSPI exceeds 23840.0. Downside risk is a reversal of the May farm boost combined with stronger personal tax payments, which would land below the interval if June DSPI is under 23620.0. A broader labor-income shock or special benefit/tax timing issue is the main outside the interval scenario."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior starts from May DSPI 23651.7 plus the Feb 2024-May 2026 base-rate sample of 28 monthly changes with mean change +77.5. I adjust down by about 19.2 billion for likely fading of May's farm-proprietor boost and tax drag, giving a point change of +58.3 and point level 23651.7 + 58.3 = 23710.0. For realized dispersion, successive changes from Feb 2024-May 2026 sum to 2170.8 over 28 changes, mean = 77.5, sum of squared deviations = 145189.3 over 27 df, so sigma = sqrt(145189.3/27) = 73.3; the normal 80 percent half-width is about 1.28*sigma = 93.8. The ladder-implied half-width is (23840.0 - 23620.0)/2 = 110.0, or 1.17x the sigma half-width, widened modestly because farm-payment and tax timing can dominate one month of DPI.","Review disposition: accepted the optional wording fix to align the May DPI increase driver with BEA's +164.9 billion release wording and made the 28-change Feb 2024-May 2026 sample explicit in the Prior/update/interval step; no required fixes were raised."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-considerations: upside risk is another large farm or transfer-payment impulse plus steady wages, which would land above the interval if June DSPI exceeds 23840.0. Downside risk is a reversal of the May farm boost combined with stronger personal tax payments, which would land below the interval if June DSPI is under 23620.0. A broader labor-income shock or special benefit/tax timing issue is the main outside the interval scenario."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: persistence prior starts from May DSPI 23651.7 plus the Feb 2024-May 2026 base-rate sample of 28 monthly changes with mean change +77.5. I adjust down by about 19.2 billion for likely fading of May's farm-proprietor boost and tax drag, giving a point change of +58.3 and point level 23651.7 + 58.3 = 23710.0. For realized dispersion, successive changes from Feb 2024-May 2026 sum to 2170.8 over 28 changes, mean = 77.5, sum of squared deviations = 145189.3 over 27 df, so sigma = sqrt(145189.3/27) = 73.3; the normal 80 percent half-width is about 1.28*sigma = 93.8. The ladder-implied half-width is (23840.0 - 23620.0)/2 = 110.0, or 1.17x the sigma half-width, widened modestly because farm-payment and tax timing can dominate one month of DPI.","Counter-considerations: upside risk is another large farm or transfer-payment impulse plus steady wages, which would land above the interval if June DSPI exceeds 23840.0. Downside risk is a reversal of the May farm boost combined with stronger personal tax payments, which would land below the interval if June DSPI is under 23620.0. A broader labor-income shock or special benefit/tax timing issue is the main outside the interval scenario."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bea-disposable-personal-income-level-june-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-07-30\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bea-disposable-personal-income-level-june-2026.2026-07-10T16-21-49Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-fast-2026-07-10t16-21-49z.b79b65940a6bf42b","runId":"run.bea-disposable-personal-income-level-june-2026.2026-07-10T16-21-49Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-fast-2026-07-10t16-21-49z.b79b65940a6bf42b","predictionId":"bea-disposable-personal-income-level-june-2026","specId":"spec.bea-disposable-personal-income-level-june-2026","runLabel":"Fast rollout 1 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate / reference class: using the Jan 2024 through May 2026 FRED-mirrored DSPI levels as the recent reference class, the 28 successive monthly changes average about +77.5 billion. A pure persistence-plus-average-change prior from May's 23,651.7 would therefore be 23,729.2.","Prior/update/interval: persistence prior is May 2026 DSPI 23,651.7 plus the 2024-2026 average monthly change +77.5 = 23,729.2; adjustment components are -40.0 for likely partial unwind of the May farm-proprietors/Supplemental Disaster Relief boost and +0.8 rounding/normal wage continuation, giving 23,690.0. Interval method uses the recent successive-change sample from Jan 2024-May 2026: sigma = 73.3, so 1.28*sigma = 93.8; rounded half-width is 94.0, giving 23,690.0 +/- 94.0 = [23,596.0, 23,784.0]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this targets BEA disposable personal income, DSPI / account code A067RC, for June 2026, seasonally adjusted annual rate in billions of dollars. The retained ledger resolver is the ALFRED generic-url binding, field DSPI, first_print, rounded to one decimal; I note that the supplied ALFRED vintage_date=2026-06-25 appears tied to the May 2026 print, but I keep the forecast on the registered target.","Tool result: FRED DSPI page shows May 2026 = 23,651.7, Apr 2026 = 23,486.9, Mar 2026 = 23,510.4, Feb 2026 = 23,382.4, Jan 2026 = 23,395.9, units billions of dollars SAAR, updated Jun 25, 2026 7:43 AM CDT."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast: BEA DSPI June 2026 First Print","Framing and exact resolver: this targets BEA disposable personal income, DSPI / account code A067RC, for June 2026, seasonally adjusted annual rate in billions of dollars. The retained ledger resolver is the ALFRED generic-url binding, field DSPI, first_print, rounded to one decimal; I note that the supplied ALFRED vintage_date=2026-06-25 appears tied to the May 2026 print, but I keep the forecast on the registered target."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 188, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is May 2026 DSPI 23,651.7 plus the 2024-2026 average monthly change +77.5 = 23,729.2; adjustment components are -40.0 for likely partial unwind of the May farm-proprietors/Supplemental Disaster Relief boost and +0.8 rounding/normal wage continuation, giving 23,690.0. Interval method uses the recent successive-change sample from Jan 2024-May 2026: sigma = 73.3, so 1.28*sigma = 93.8; rounded half-width is 94.0, giving 23,690.0 +/- 94.0 = [23,596.0, 23,784.0].","Counter-consideration: upside risk is another large compensation or transfer month that would land above the interval if June DSPI exceeds 23,784.0; downside risk is a larger reversal of the May farm-payment boost or weak wage accruals that would land below the interval if June DSPI is under 23,596.0. A later annual revision is outside the interval logic because the target is first print only."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Counter-consideration: upside risk is another large compensation or transfer month that would land above the interval if June DSPI exceeds 23,784.0; downside risk is a larger reversal of the May farm-payment boost or weak wage accruals that would land below the interval if June DSPI is under 23,596.0. A later annual revision is outside the interval logic because the target is first print only."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Framing and exact resolver: this targets BEA disposable personal income, DSPI / account code A067RC, for June 2026, seasonally adjusted annual rate in billions of dollars. The retained ledger resolver is the ALFRED generic-url binding, field DSPI, first_print, rounded to one decimal; I note that the supplied ALFRED vintage_date=2026-06-25 appears tied to the May 2026 print, but I keep the forecast on the registered target.","Counter-consideration: upside risk is another large compensation or transfer month that would land above the interval if June DSPI exceeds 23,784.0; downside risk is a larger reversal of the May farm-payment boost or weak wage accruals that would land below the interval if June DSPI is under 23,596.0. A later annual revision is outside the interval logic because the target is first print only."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: BEA DSPI June 2026 First Print","Framing and exact resolver: this targets BEA disposable personal income, DSPI / account code A067RC, for June 2026, seasonally adjusted annual rate in billions of dollars. The retained ledger resolver is the ALFRED generic-url binding, field DSPI, first_print, rounded to one decimal; I note that the supplied ALFRED vintage_date=2026-06-25 appears tied to the May 2026 print, but I keep the forecast on the registered target."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bea-disposable-personal-income-level-june-2026\nrunLabel: Fast rollout 1 of 3\nresolutionDate: 2026-07-30\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bea-disposable-personal-income-level-june-2026.2026-07-10T16-33-38Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-fast-2026-07-10t16-33-38z.176d0d45da363c72","runId":"run.bea-disposable-personal-income-level-june-2026.2026-07-10T16-33-38Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-fast-2026-07-10t16-33-38z.176d0d45da363c72","predictionId":"bea-disposable-personal-income-level-june-2026","specId":"spec.bea-disposable-personal-income-level-june-2026","runLabel":"Fast rollout 2 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: for the 2023-01 through 2026-05 DSPI history, the month-to-month changes average about +91.6 billion, with the most recent realized changes including +230.0 in Jan 2026, -13.5 in Feb 2026, +128.0 in Mar 2026, -23.5 in Apr 2026, and +164.8 in May 2026.","Prior/update/interval: persistence-plus-average-change model uses the latest level 23651.7 and a 2023-01 to 2026-05 successive-change reference class; mean monthly change = 91.6, sigma = 77.9, so the unadjusted prior is 23651.7 + 91.6 = 23743.3. I subtract 38.3 because May included a large likely nonrecurring farm/Supplemental Disaster Relief boost, leaving 23705.0. The 80% half-width is roughly 1.28*sigma = 1.28*77.9 = 99.7, so bounds are 23705.0 - 99.7 = 23605.3 and 23705.0 + 99.7 = 23804.7."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this targets BEA disposable personal income, account code A067RC / FRED-ALFRED series DSPI, for June 2026, seasonally adjusted annual rate in billions of dollars, first official print only. The retained ledger resolver is the ALFRED DSPI CSV generic-url binding; the ledger URL vintage_date=2026-06-25 appears to be the May 2026 print rather than the future June print, so I keep the target tied to the ledger contract and note the discrepancy rather than changing it.","Tool result: FRED DSPI shows May 2026 = 23651.7, Apr 2026 = 23486.9, Mar 2026 = 23510.4, Feb 2026 = 23382.4, Jan 2026 = 23395.9, in billions of dollars, seasonally adjusted annual rate, updated Jun 25, 2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast for BEA DSPI June 2026 first print","Framing and exact resolver: this targets BEA disposable personal income, account code A067RC / FRED-ALFRED series DSPI, for June 2026, seasonally adjusted annual rate in billions of dollars, first official print only. The retained ledger resolver is the ALFRED DSPI CSV generic-url binding; the ledger URL vintage_date=2026-06-25 appears to be the May 2026 print rather than the future June print, so I keep the target tied to the ledger contract and note the discrepancy rather than changing it."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 199.4, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence-plus-average-change model uses the latest level 23651.7 and a 2023-01 to 2026-05 successive-change reference class; mean monthly change = 91.6, sigma = 77.9, so the unadjusted prior is 23651.7 + 91.6 = 23743.3. I subtract 38.3 because May included a large likely nonrecurring farm/Supplemental Disaster Relief boost, leaving 23705.0. The 80% half-width is roughly 1.28*sigma = 1.28*77.9 = 99.7, so bounds are 23705.0 - 99.7 = 23605.3 and 23705.0 + 99.7 = 23804.7.","Upside risk: a continued wage acceleration, another transfer-payment boost, or stronger-than-usual tax-withholding timing would land above the interval. Downside risk: reversal of the May farm-relief boost plus weak wages or higher current taxes would land below the interval. Outside the interval would most likely require a policy-payment jump or reversal larger than the recent monthly dispersion."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence-plus-average-change model uses the latest level 23651.7 and a 2023-01 to 2026-05 successive-change reference class; mean monthly change = 91.6, sigma = 77.9, so the unadjusted prior is 23651.7 + 91.6 = 23743.3. I subtract 38.3 because May included a large likely nonrecurring farm/Supplemental Disaster Relief boost, leaving 23705.0. The 80% half-width is roughly 1.28*sigma = 1.28*77.9 = 99.7, so bounds are 23705.0 - 99.7 = 23605.3 and 23705.0 + 99.7 = 23804.7."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Upside risk: a continued wage acceleration, another transfer-payment boost, or stronger-than-usual tax-withholding timing would land above the interval. Downside risk: reversal of the May farm-relief boost plus weak wages or higher current taxes would land below the interval. Outside the interval would most likely require a policy-payment jump or reversal larger than the recent monthly dispersion."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for BEA DSPI June 2026 first print","Prior/update/interval: persistence-plus-average-change model uses the latest level 23651.7 and a 2023-01 to 2026-05 successive-change reference class; mean monthly change = 91.6, sigma = 77.9, so the unadjusted prior is 23651.7 + 91.6 = 23743.3. I subtract 38.3 because May included a large likely nonrecurring farm/Supplemental Disaster Relief boost, leaving 23705.0. The 80% half-width is roughly 1.28*sigma = 1.28*77.9 = 99.7, so bounds are 23705.0 - 99.7 = 23605.3 and 23705.0 + 99.7 = 23804.7."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bea-disposable-personal-income-level-june-2026\nrunLabel: Fast rollout 2 of 3\nresolutionDate: 2026-07-30\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bea-disposable-personal-income-level-june-2026.2026-07-10T16-44-08Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-fast-2026-07-10t16-44-08z.1331a22808ccbe59","runId":"run.bea-disposable-personal-income-level-june-2026.2026-07-10T16-44-08Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-fast-2026-07-10t16-44-08z.1331a22808ccbe59","predictionId":"bea-disposable-personal-income-level-june-2026","specId":"spec.bea-disposable-personal-income-level-june-2026","runLabel":"Fast rollout 3 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Framing and exact resolver: this is BEA disposable personal income, DSPI / account code A067RC, in billions of dollars at a seasonally adjusted annual rate. The ledger resolution remains the ALFRED DSPI first-print binding even though the supplied vintage_date appears to point to the prior May 2026 print rather than the July 30 June-release vintage.","Reference class/base rate: for a level series like DSPI, the most relevant base rate is the distribution of recent month-to-month first-available level changes in the same SAAR billions variant, not the level itself. Recent changes cluster around a positive 60-75 billion monthly drift, with occasional larger transfer-income and wage-payment moves."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this is BEA disposable personal income, DSPI / account code A067RC, in billions of dollars at a seasonally adjusted annual rate. The ledger resolution remains the ALFRED DSPI first-print binding even though the supplied vintage_date appears to point to the prior May 2026 print rather than the July 30 June-release vintage.","Tool call: Checked BEA NIPA monthly personal income table for the same DSPI/A067RC level variant, seasonally adjusted annual rate, billions of dollars."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast for BEA DSPI June 2026 first print","Framing and exact resolver: this is BEA disposable personal income, DSPI / account code A067RC, in billions of dollars at a seasonally adjusted annual rate. The ledger resolution remains the ALFRED DSPI first-print binding even though the supplied vintage_date appears to point to the prior May 2026 print rather than the July 30 June-release vintage."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 220.6, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence-plus-drift prior uses latest fetched May 2026 level 24118.5, a recent DSPI monthly-change historical sample, adjustment components of +66.5 normal nominal income drift and no separate one-off policy transfer adjustment, and an 80% interval from successive-change dispersion. sigma = 86.2, so half-width = 1.28*86.2 = 110.3. Point = 24118.5 + 66.5 = 24185.0; 80% interval = 24185.0 - 110.3 to 24185.0 + 110.3 = 24074.7 to 24295.3.","Counter-considerations: upside risk is a larger-than-usual wage, proprietors' income, or transfer-payment jump that would land above the interval near 24295.3. Downside risk is a weak payroll-income print or a benefit-payment normalization that would land below the interval near 24074.7; outside the interval would likely require a clear transfer-program timing shock or a material first-print source revision."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Momentum check: the last two fetched monthly increases were both 73.1 billion, close to the 66.5 base-rate drift, so I keep the point just under a repeat of that pace rather than extrapolating a stronger acceleration."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Reference class/base rate: for a level series like DSPI, the most relevant base rate is the distribution of recent month-to-month first-available level changes in the same SAAR billions variant, not the level itself. Recent changes cluster around a positive 60-75 billion monthly drift, with occasional larger transfer-income and wage-payment moves.","Counter-considerations: upside risk is a larger-than-usual wage, proprietors' income, or transfer-payment jump that would land above the interval near 24295.3. Downside risk is a weak payroll-income print or a benefit-payment normalization that would land below the interval near 24074.7; outside the interval would likely require a clear transfer-program timing shock or a material first-print source revision."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for BEA DSPI June 2026 first print","Framing and exact resolver: this is BEA disposable personal income, DSPI / account code A067RC, in billions of dollars at a seasonally adjusted annual rate. The ledger resolution remains the ALFRED DSPI first-print binding even though the supplied vintage_date appears to point to the prior May 2026 print rather than the July 30 June-release vintage."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bea-disposable-personal-income-level-june-2026\nrunLabel: Fast rollout 3 of 3\nresolutionDate: 2026-07-30\ntraceLineCount: 13\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bea-disposable-personal-income-level-june-2026.2026-07-10T16-53-08Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-median3-2026-07-10t16-53-08z.b3160f4c265f2fb9","runId":"run.bea-disposable-personal-income-level-june-2026.2026-07-10T16-53-08Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-median3-2026-07-10t16-53-08z.b3160f4c265f2fb9","predictionId":"bea-disposable-personal-income-level-june-2026","specId":"spec.bea-disposable-personal-income-level-june-2026","runLabel":"Median of 3 rollouts","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 5 historical point(s) and implicit outside-view language.","evidence":["Median-of-3 rollout ensemble","Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T16:21:49Z, 2026-07-10T16:33:38Z, 2026-07-10T16:44:08Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 7 source-context item(s), activity log present.","evidence":["Median CDF quantiles: q10 = 23603.7, q50 = 23705.0, q90 = 23806.4. Constituent points [23690.0, 23705.0, 24185] with 80% widths [188.0, 199.4, 220.6]; the median interval inherits the central rollout mass rather than averaging tails."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 202.7, distribution present, forecast step count 1.","evidence":["Median CDF quantiles: q10 = 23603.7, q50 = 23705.0, q90 = 23806.4. Constituent points [23690.0, 23705.0, 24185] with 80% widths [188.0, 199.4, 220.6]; the median interval inherits the central rollout mass rather than averaging tails.","Forecast: point 23705, 80% interval [23603.7, 23806.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T16:21:49Z, 2026-07-10T16:33:38Z, 2026-07-10T16:44:08Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T16:21:49Z, 2026-07-10T16:33:38Z, 2026-07-10T16:44:08Z. Drivers and resolver fields mirror the rollout closest to the median.","Tool result: {rollout_points: [23690.0, 23705.0, 24185], rollout_widths: [188.0, 199.4, 220.6], q10: 23603.7, q50: 23705.0, q90: 23806.4}"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bea-disposable-personal-income-level-june-2026\nrunLabel: Median of 3 rollouts\nresolutionDate: 2026-07-30\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bea-disposable-personal-income-level-june-2026.2026-07-10T17-08-15Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-ladder-2026-07-10t17-08-15z.4d6dafea5c41ef9b","runId":"run.bea-disposable-personal-income-level-june-2026.2026-07-10T17-08-15Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-ladder-2026-07-10t17-08-15z.4d6dafea5c41ef9b","predictionId":"bea-disposable-personal-income-level-june-2026","specId":"spec.bea-disposable-personal-income-level-june-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The outside-view base rate uses the 12 successive DSPI changes from May 2025 through May 2026: 41.5, 139.0, 105.9, 82.6, -28.8, 48.0, 55.1, 230.0, -13.5, 128.0, -23.5, and 164.8 billion. Their median is 68.9 billion, providing a robust persistence prior for the June increase.","Prior/update/interval: The model is a median-change persistence prior using the 12 monthly changes listed above. The sample standard deviation is sigma = 80.0 billion: sqrt(sum((change - 77.4)^2)/11) = sqrt(70488/11) = 80.0. The normal-reference 80% half-width is roughly 1.28*sigma = 1.28*80.0 = 102.4 billion. Starting from 23651.7, the 68.9 base-rate increment, +15.0 wage/price momentum adjustment, and -10.6 farm-support unwind adjustment imply 23725.0 after rounding. The ladder gives bounds 110.0 below and 105.0 above its median, closely matching the 102.4 billion reference half-width."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The target is BEA current-dollar disposable personal income, DSPI / NIPA account code A067RC, in billions of dollars at a seasonally adjusted annual rate. All anchors use that nominal SAAR variant. Resolution is the first June 2026 print rounded to one decimal, with later revisions ignored. The retained ledger URL has vintage_date=2026-06-25 and therefore cannot contain the July 30 June first print; its expected release window also ends one day early. The forecast nevertheless remains tied to the registered target and binding as instructed.","Tool call: Inspect BEA's official Personal Income and Outlays release schedule for the June 2026 report."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["June 2026 disposable personal income first-print forecast","The target is BEA current-dollar disposable personal income, DSPI / NIPA account code A067RC, in billions of dollars at a seasonally adjusted annual rate. All anchors use that nominal SAAR variant. Resolution is the first June 2026 print rounded to one decimal, with later revisions ignored. The retained ledger URL has vintage_date=2026-06-25 and therefore cannot contain the July 30 June first print; its expected release window also ends one day early. The forecast nevertheless remains tied to the registered target and binding as instructed."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 215, distribution present, forecast step count 1.","evidence":["Prior/update/interval: The model is a median-change persistence prior using the 12 monthly changes listed above. The sample standard deviation is sigma = 80.0 billion: sqrt(sum((change - 77.4)^2)/11) = sqrt(70488/11) = 80.0. The normal-reference 80% half-width is roughly 1.28*sigma = 1.28*80.0 = 102.4 billion. Starting from 23651.7, the 68.9 base-rate increment, +15.0 wage/price momentum adjustment, and -10.6 farm-support unwind adjustment imply 23725.0 after rounding. The ladder gives bounds 110.0 below and 105.0 above its median, closely matching the 102.4 billion reference half-width.","Upside risk from stronger payroll compensation, bonuses, transfers, or another farm-support payment could put the print above 23830.0. Downside risk from a sharper farm-income unwind, weaker wages, or higher personal taxes could put it below 23615.0. Either outcome would land outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level and momentum favor another nominal increase from 23651.7. I apply a heuristic +15.0 billion adjustment for continuing wage, salary, and price momentum and a -10.6 billion adjustment for partial reversal of May's Supplemental Disaster Relief Program boost to farm proprietors' income. These effects cannot be estimated independently from the available aggregate release, so their separate magnitudes express a net +4.4 billion judgment rather than measured component forecasts.","Prior/update/interval: The model is a median-change persistence prior using the 12 monthly changes listed above. The sample standard deviation is sigma = 80.0 billion: sqrt(sum((change - 77.4)^2)/11) = sqrt(70488/11) = 80.0. The normal-reference 80% half-width is roughly 1.28*sigma = 1.28*80.0 = 102.4 billion. Starting from 23651.7, the 68.9 base-rate increment, +15.0 wage/price momentum adjustment, and -10.6 farm-support unwind adjustment imply 23725.0 after rounding. The ladder gives bounds 110.0 below and 105.0 above its median, closely matching the 102.4 billion reference half-width."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Upside risk from stronger payroll compensation, bonuses, transfers, or another farm-support payment could put the print above 23830.0. Downside risk from a sharper farm-income unwind, weaker wages, or higher personal taxes could put it below 23615.0. Either outcome would land outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["June 2026 disposable personal income first-print forecast","The target is BEA current-dollar disposable personal income, DSPI / NIPA account code A067RC, in billions of dollars at a seasonally adjusted annual rate. All anchors use that nominal SAAR variant. Resolution is the first June 2026 print rounded to one decimal, with later revisions ignored. The retained ledger URL has vintage_date=2026-06-25 and therefore cannot contain the July 30 June first print; its expected release window also ends one day early. The forecast nevertheless remains tied to the registered target and binding as instructed."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bea-disposable-personal-income-level-june-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-07-30\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bea-disposable-personal-income-level-june-2026.2026-07-10T17-18-16Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-fast-2026-07-10t17-18-16z.b2ada3abed4b54c9","runId":"run.bea-disposable-personal-income-level-june-2026.2026-07-10T17-18-16Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-fast-2026-07-10t17-18-16z.b2ada3abed4b54c9","predictionId":"bea-disposable-personal-income-level-june-2026","specId":"spec.bea-disposable-personal-income-level-june-2026","runLabel":"Fast rollout 1 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The recent reference class is the four successive DSPI changes from January through May: -13.5, +128.0, -23.5, and +164.8 billion. Their mean change, +63.95 billion, is the base rate for a one-month level forecast.","Prior/update/interval: The persistence model starts from May's 23,651.7 level. The historical sample is the four changes -13.5, +128.0, -23.5, and +164.8, whose mean is +63.95 and sample sigma = 96.5 billion. Adjustment components—ongoing compensation growth, partial farm-payment reversal, and taxes—reduce the expected change to +50.0, so the point is 23,651.7 + 50.0 = 23,701.7. The empirical 80% normal half-width is 1.28*sigma = 1.28*96.5 = 123.5, implying bounds of 23,701.7 - 123.5 = 23,578.2 and 23,701.7 + 123.5 = 23,825.2."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The target is BEA disposable personal income, DSPI / NIPA account code A067RC, in current-dollar billions at a seasonally adjusted annual rate. It resolves to the June 2026 first print rounded to one decimal, with no later revisions. The retained ALFRED URL has a 2026-06-25 vintage date that appears to expose the May release rather than the July 30 June print; this is a ledger discrepancy, not a change to the target.","Tool result: DSPI levels were 23,395.9 in January 2026, 23,382.4 in February, 23,510.4 in March, 23,486.9 in April, and 23,651.7 in May, all billions of dollars SAAR."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["June 2026 disposable personal income first-print forecast","The target is BEA disposable personal income, DSPI / NIPA account code A067RC, in current-dollar billions at a seasonally adjusted annual rate. It resolves to the June 2026 first print rounded to one decimal, with no later revisions. The retained ALFRED URL has a 2026-06-25 vintage date that appears to expose the May release rather than the July 30 June print; this is a ledger discrepancy, not a change to the target."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 247, distribution present, forecast step count 1.","evidence":["Prior/update/interval: The persistence model starts from May's 23,651.7 level. The historical sample is the four changes -13.5, +128.0, -23.5, and +164.8, whose mean is +63.95 and sample sigma = 96.5 billion. Adjustment components—ongoing compensation growth, partial farm-payment reversal, and taxes—reduce the expected change to +50.0, so the point is 23,651.7 + 50.0 = 23,701.7. The empirical 80% normal half-width is 1.28*sigma = 1.28*96.5 = 123.5, implying bounds of 23,701.7 - 123.5 = 23,578.2 and 23,701.7 + 123.5 = 23,825.2.","Upside risk comes from another large farm-support payment, stronger wage accruals, or unusually high transfer receipts and would land above the interval. Downside risk comes from a sharper reversal of May farm income, weak compensation, or a jump in tax payments and could land below the interval. These mechanisms also explain why the interval remains tied to realized monthly dispersion rather than a narrower trend band."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["May's unusually large rise partly reflected farm proprietors' income associated with a second round of Supplemental Disaster Relief Program payments, while compensation also increased. For June I retain ordinary compensation-led growth but allow a partial reversal of that one-off farm boost and continued subtraction from personal current taxes, yielding a net update of about +50.0 billion from May.","Upside risk comes from another large farm-support payment, stronger wage accruals, or unusually high transfer receipts and would land above the interval. Downside risk comes from a sharper reversal of May farm income, weak compensation, or a jump in tax payments and could land below the interval. These mechanisms also explain why the interval remains tied to realized monthly dispersion rather than a narrower trend band."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["June 2026 disposable personal income first-print forecast","The recent reference class is the four successive DSPI changes from January through May: -13.5, +128.0, -23.5, and +164.8 billion. Their mean change, +63.95 billion, is the base rate for a one-month level forecast."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bea-disposable-personal-income-level-june-2026\nrunLabel: Fast rollout 1 of 3\nresolutionDate: 2026-07-30\ntraceLineCount: 13\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bea-disposable-personal-income-level-june-2026.2026-07-10T17-24-33Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-fast-2026-07-10t17-24-33z.d59291078e300682","runId":"run.bea-disposable-personal-income-level-june-2026.2026-07-10T17-24-33Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-fast-2026-07-10t17-24-33z.d59291078e300682","predictionId":"bea-disposable-personal-income-level-june-2026","specId":"spec.bea-disposable-personal-income-level-june-2026","runLabel":"Fast rollout 2 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The recent reference class supplies a base rate of +63.95 billion per month from the four January-to-May successive changes. Level persistence and ongoing compensation growth point upward, while May's farm proprietors' income included a second round of Supplemental Disaster Relief Program payments, creating a plausible one-off reversal in June.","Prior/update/interval: the model is a recent-change persistence prior using the four fetched changes (-13.5, 128.0, -23.5, 164.8), whose mean is +63.95. Starting from 23,651.7, the persistence projection is 23,715.65; a -3.95 adjustment for partial reversal of May farm-support effects gives 23,711.7. The sample standard deviation of those changes is sigma = 96.47; the 80% normal half-width is roughly 1.28*sigma = 123.48, producing 23,588.2 to 23,835.2 after rounding."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The target is BEA NIPA Table 2.6 line 27, account code A067RC: current-dollar disposable personal income in billions of dollars at a seasonally adjusted annual rate. Resolution is the June 2026 first print rounded to one decimal, with later revisions ignored. The retained ledger ALFRED URL uses vintage_date=2026-06-25, apparently the May-release vintage rather than the July 30 release vintage; this is a concrete binding discrepancy, but the forecast remains tied to the registered target.","Tool call: Verify the June 2026 Personal Income and Outlays publication date from BEA's official release announcement and schedule."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["June 2026 disposable personal income first-print forecast","The target is BEA NIPA Table 2.6 line 27, account code A067RC: current-dollar disposable personal income in billions of dollars at a seasonally adjusted annual rate. Resolution is the June 2026 first print rounded to one decimal, with later revisions ignored. The retained ledger ALFRED URL uses vintage_date=2026-06-25, apparently the May-release vintage rather than the July 30 release vintage; this is a concrete binding discrepancy, but the forecast remains tied to the registered target."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 247, distribution present, forecast step count 1.","evidence":["Prior/update/interval: the model is a recent-change persistence prior using the four fetched changes (-13.5, 128.0, -23.5, 164.8), whose mean is +63.95. Starting from 23,651.7, the persistence projection is 23,715.65; a -3.95 adjustment for partial reversal of May farm-support effects gives 23,711.7. The sample standard deviation of those changes is sigma = 96.47; the 80% normal half-width is roughly 1.28*sigma = 123.48, producing 23,588.2 to 23,835.2 after rounding.","Upside risk comes from another large compensation gain or continued farm-support disbursements and would land above the interval. Downside risk comes from a sharp reversal in farm proprietors' income, weak payroll income, or an unusually large rise in personal taxes and could land below the interval. Either outcome requires a monthly move outside the recent-change dispersion summarized above."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The target is BEA NIPA Table 2.6 line 27, account code A067RC: current-dollar disposable personal income in billions of dollars at a seasonally adjusted annual rate. Resolution is the June 2026 first print rounded to one decimal, with later revisions ignored. The retained ledger ALFRED URL uses vintage_date=2026-06-25, apparently the May-release vintage rather than the July 30 release vintage; this is a concrete binding discrepancy, but the forecast remains tied to the registered target.","Tool result: BEA reported May disposable personal income of 23,651.7 billion dollars, up 164.9 billion or 0.7%; personal income rose 181.6 billion and compensation was among the main contributors."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["June 2026 disposable personal income first-print forecast","The target is BEA NIPA Table 2.6 line 27, account code A067RC: current-dollar disposable personal income in billions of dollars at a seasonally adjusted annual rate. Resolution is the June 2026 first print rounded to one decimal, with later revisions ignored. The retained ledger ALFRED URL uses vintage_date=2026-06-25, apparently the May-release vintage rather than the July 30 release vintage; this is a concrete binding discrepancy, but the forecast remains tied to the registered target."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bea-disposable-personal-income-level-june-2026\nrunLabel: Fast rollout 2 of 3\nresolutionDate: 2026-07-30\ntraceLineCount: 12\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bea-disposable-personal-income-level-june-2026.2026-07-10T17-30-00Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-fast-2026-07-10t17-30-00z.cbb8855581170376","runId":"run.bea-disposable-personal-income-level-june-2026.2026-07-10T17-30-00Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-fast-2026-07-10t17-30-00z.cbb8855581170376","predictionId":"bea-disposable-personal-income-level-june-2026","specId":"spec.bea-disposable-personal-income-level-june-2026","runLabel":"Fast rollout 3 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The target is BEA disposable personal income, series DSPI / NIPA account code A067RC, in billions of current dollars at a seasonally adjusted annual rate. It resolves on the June 2026 first print, rounded to one decimal, with later revisions ignored. The retained ALFRED URL has a 2026-06-25 vintage that appears to capture the prior May print rather than the July release; this ledger discrepancy is preserved rather than silently corrected.","The reference class is the 12 successive monthly DSPI level changes from June 2025 through May 2026: 41.5, 139.0, 105.9, 82.6, -28.8, 48.0, 55.1, 230.0, -13.5, 128.0, -23.5, and 164.8 billion. Their base rate mean is +77.425 billion per month."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The target is BEA disposable personal income, series DSPI / NIPA account code A067RC, in billions of current dollars at a seasonally adjusted annual rate. It resolves on the June 2026 first print, rounded to one decimal, with later revisions ignored. The retained ALFRED URL has a 2026-06-25 vintage that appears to capture the prior May print rather than the July release; this ledger discrepancy is preserved rather than silently corrected.","Tool result: BEA reported May disposable personal income increased by $164.9 billion, or 0.7%; personal income increased $181.6 billion and personal consumption expenditures increased $156.1 billion."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is BEA disposable personal income, series DSPI / NIPA account code A067RC, in billions of current dollars at a seasonally adjusted annual rate. It resolves on the June 2026 first print, rounded to one decimal, with later revisions ignored. The retained ALFRED URL has a 2026-06-25 vintage that appears to capture the prior May print rather than the July release; this ledger discrepancy is preserved rather than silently corrected.","Tool call: Fetch the BEA Personal Income and Outlays release for May 2026."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 204.9, distribution present, forecast step count 1.","evidence":["Prior/update/interval: The model is a one-month persistence prior using the mean of the 12 fetched June 2025–May 2026 successive changes. Historical mean change = 77.425 and sigma = 80.0524. Adjustments are +0 for trend persistence, +0 for wage momentum already represented in the reference class, and +0 net for offsetting normalization of May relief payments and tax uncertainty. Point = 23651.7 + 77.425 = 23729.125, rounded to 23729.1. The empirical 80% half-width is 1.28*sigma = 1.28*80.0524 = 102.4671, giving 23626.6579 to 23831.5921, rounded to 23626.7–23831.6.","Upside risk comes from unusually strong payroll compensation or another transfer/proprietors' income boost and would land above the interval. Downside risk comes from a reversal of May's farm-relief effect, weak compensation, or a sharp increase in current taxes; a monthly decline exceeding about $25.0 billion would land below the interval. Either outcome would be outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level momentum remains positive, but May's $164.9 billion jump was partly supported by farm proprietors' income after a second round of disaster-relief payments. Normal wage and salary growth supports another increase, while fading relief payments and movements in personal current taxes argue against simply repeating May's gain.","Prior/update/interval: The model is a one-month persistence prior using the mean of the 12 fetched June 2025–May 2026 successive changes. Historical mean change = 77.425 and sigma = 80.0524. Adjustments are +0 for trend persistence, +0 for wage momentum already represented in the reference class, and +0 net for offsetting normalization of May relief payments and tax uncertainty. Point = 23651.7 + 77.425 = 23729.125, rounded to 23729.1. The empirical 80% half-width is 1.28*sigma = 1.28*80.0524 = 102.4671, giving 23626.6579 to 23831.5921, rounded to 23626.7–23831.6."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level momentum remains positive, but May's $164.9 billion jump was partly supported by farm proprietors' income after a second round of disaster-relief payments. Normal wage and salary growth supports another increase, while fading relief payments and movements in personal current taxes argue against simply repeating May's gain.","Prior/update/interval: The model is a one-month persistence prior using the mean of the 12 fetched June 2025–May 2026 successive changes. Historical mean change = 77.425 and sigma = 80.0524. Adjustments are +0 for trend persistence, +0 for wage momentum already represented in the reference class, and +0 net for offsetting normalization of May relief payments and tax uncertainty. Point = 23651.7 + 77.425 = 23729.125, rounded to 23729.1. The empirical 80% half-width is 1.28*sigma = 1.28*80.0524 = 102.4671, giving 23626.6579 to 23831.5921, rounded to 23626.7–23831.6."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["June 2026 disposable personal income forecast","Prior/update/interval: The model is a one-month persistence prior using the mean of the 12 fetched June 2025–May 2026 successive changes. Historical mean change = 77.425 and sigma = 80.0524. Adjustments are +0 for trend persistence, +0 for wage momentum already represented in the reference class, and +0 net for offsetting normalization of May relief payments and tax uncertainty. Point = 23651.7 + 77.425 = 23729.125, rounded to 23729.1. The empirical 80% half-width is 1.28*sigma = 1.28*80.0524 = 102.4671, giving 23626.6579 to 23831.5921, rounded to 23626.7–23831.6."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bea-disposable-personal-income-level-june-2026\nrunLabel: Fast rollout 3 of 3\nresolutionDate: 2026-07-30\ntraceLineCount: 13\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bea-disposable-personal-income-level-june-2026.2026-07-10T17-33-53Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-median3-2026-07-10t17-33-53z.32dc0d732d6ae2a3","runId":"run.bea-disposable-personal-income-level-june-2026.2026-07-10T17-33-53Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-median3-2026-07-10t17-33-53z.32dc0d732d6ae2a3","predictionId":"bea-disposable-personal-income-level-june-2026","specId":"spec.bea-disposable-personal-income-level-june-2026","runLabel":"Median of 3 rollouts","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 5 historical point(s) and implicit outside-view language.","evidence":["Median-of-3 rollout ensemble","Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T17:18:16Z, 2026-07-10T17:24:33Z, 2026-07-10T17:30:00Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 7 source-context item(s), activity log present.","evidence":["Median CDF quantiles: q10 = 23587.6, q50 = 23711.7, q90 = 23832.1. Constituent points [23701.7, 23711.7, 23729.1] with 80% widths [247.0, 247.0, 204.9]; the median interval inherits the central rollout mass rather than averaging tails."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 244.5, distribution present, forecast step count 1.","evidence":["Median CDF quantiles: q10 = 23587.6, q50 = 23711.7, q90 = 23832.1. Constituent points [23701.7, 23711.7, 23729.1] with 80% widths [247.0, 247.0, 204.9]; the median interval inherits the central rollout mass rather than averaging tails.","Forecast: point 23711.7, 80% interval [23587.6, 23832.1]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T17:18:16Z, 2026-07-10T17:24:33Z, 2026-07-10T17:30:00Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T17:18:16Z, 2026-07-10T17:24:33Z, 2026-07-10T17:30:00Z. Drivers and resolver fields mirror the rollout closest to the median.","Tool result: {rollout_points: [23701.7, 23711.7, 23729.1], rollout_widths: [247.0, 247.0, 204.9], q10: 23587.6, q50: 23711.7, q90: 23832.1}"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bea-disposable-personal-income-level-june-2026\nrunLabel: Median of 3 rollouts\nresolutionDate: 2026-07-30\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bea-disposable-personal-income-level-june-2026.2026-07-10T21-18-22Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-ladder-v2-2026-07-10t21-18-22z.681c0368a07b24fd","runId":"run.bea-disposable-personal-income-level-june-2026.2026-07-10T21-18-22Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-ladder-v2-2026-07-10t21-18-22z.681c0368a07b24fd","predictionId":"bea-disposable-personal-income-level-june-2026","specId":"spec.bea-disposable-personal-income-level-june-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Framing and exact resolver: target is BEA current-dollar disposable personal income, DSPI / account code A067RC, monthly, billions of dollars at a seasonally adjusted annual rate. The retained ledger resolver is the ALFRED generic-url DSPI first-print binding even though its vintage_date appears to point to the prior May 2026 print; I keep that discrepancy explicit rather than changing the target.","Reference class and base rate: the immediate FRED/BEA DSPI reference class is the five latest same-variant monthly levels: 23395.9, 23382.4, 23510.4, 23486.9, and 23651.7. Month-to-month changes over that span were -13.5, +128.0, -23.5, and +164.8 billion, so a naive latest-level-plus-recent-average prior would be around 23715, but the May relief-payment composition argues for pulling that down."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing and exact resolver: target is BEA current-dollar disposable personal income, DSPI / account code A067RC, monthly, billions of dollars at a seasonally adjusted annual rate. The retained ledger resolver is the ALFRED generic-url DSPI first-print binding even though its vintage_date appears to point to the prior May 2026 print; I keep that discrepancy explicit rather than changing the target.","Tool result: FRED/BEA mirror shows DSPI May 2026 23651.7, Apr 2026 23486.9, Mar 2026 23510.4, Feb 2026 23382.4, Jan 2026 23395.9, all billions of dollars seasonally adjusted annual rate; updated Jun 25, 2026 7:43 AM CDT."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast for BEA June 2026 disposable personal income first print","Framing and exact resolver: target is BEA current-dollar disposable personal income, DSPI / account code A067RC, monthly, billions of dollars at a seasonally adjusted annual rate. The retained ledger resolver is the ALFRED generic-url DSPI first-print binding even though its vintage_date appears to point to the prior May 2026 print; I keep that discrepancy explicit rather than changing the target."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 414.3, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is May DSPI 23651.7 plus the recent four-change average of about +64 billion, or about 23715; I apply +45 billion for June nominal wage/transfer growth, -20 billion for weak 57000 payroll growth and downward revisions, and -50 billion for partial reversal of May farm-proprietor relief effects, giving about 23691 before ladder rounding. The fetched values anchoring the rung span are May 23651.7, Apr 23486.9, Mar 23510.4, and the May +164.9 billion DPI increase; interval method is an elicited threshold ladder over the Jan-May month-to-month change sample, judgmentally wider than recent volatility to allow one-off transfer/proprietor reversals.","Counter-considerations: upside risk is another transfer or proprietors-income boost, stronger June withholding, or less reversal of May farm payments, which would land above the interval. Downside risk is a sharper relief-payment reversal, weaker bonus/proprietor income, or larger tax-withholding drag, which would land below the interval. Outside the interval would require either a monthly drop larger than about 166 billion from May or a gain above about 248 billion from May."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Review disposition: accepted the suggestions to add the BLS Employment Situation URL, clarify that the adjustment components apply to the 23715 latest-level-plus-average-change prior, and document that the ladder width is judgmentally wider than the Jan-May month-to-month volatility because of one-off transfer/proprietor-income uncertainty; no reviewer critique was rejected."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Reference class and base rate: the immediate FRED/BEA DSPI reference class is the five latest same-variant monthly levels: 23395.9, 23382.4, 23510.4, 23486.9, and 23651.7. Month-to-month changes over that span were -13.5, +128.0, -23.5, and +164.8 billion, so a naive latest-level-plus-recent-average prior would be around 23715, but the May relief-payment composition argues for pulling that down.","Counter-considerations: upside risk is another transfer or proprietors-income boost, stronger June withholding, or less reversal of May farm payments, which would land above the interval. Downside risk is a sharper relief-payment reversal, weaker bonus/proprietor income, or larger tax-withholding drag, which would land below the interval. Outside the interval would require either a monthly drop larger than about 166 billion from May or a gain above about 248 billion from May."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for BEA June 2026 disposable personal income first print","Framing and exact resolver: target is BEA current-dollar disposable personal income, DSPI / account code A067RC, monthly, billions of dollars at a seasonally adjusted annual rate. The retained ledger resolver is the ALFRED generic-url DSPI first-print binding even though its vintage_date appears to point to the prior May 2026 print; I keep that discrepancy explicit rather than changing the target."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bea-disposable-personal-income-level-june-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-07-30\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bea-disposable-personal-income-level-june-2026.2026-07-10T21-42-15Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-ladder-v2-2026-07-10t21-42-15z.b86c5bb7aa023063","runId":"run.bea-disposable-personal-income-level-june-2026.2026-07-10T21-42-15Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-ladder-v2-2026-07-10t21-42-15z.b86c5bb7aa023063","predictionId":"bea-disposable-personal-income-level-june-2026","specId":"spec.bea-disposable-personal-income-level-june-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The reference class is the four latest fetched monthly DSPI changes: -13.5, +128.0, -23.5, and +164.8 billion. Their mean is +63.95 billion, median is +57.25 billion, and sample standard deviation is 96.5 billion. This supplies the base rate, while the $23,651.7 billion May level supplies the persistence anchor.","May's $164.9 billion gain was unusually strong and BEA attributed the broader personal-income increase partly to farm proprietors' income from a second round of Supplemental Disaster Relief Program payments. That argues against extrapolating May's full increase. Ordinary nominal income growth is already represented in the recent-change base rate, so no separate wage, employment, or inflation increment is added."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The target is BEA NIPA Table 2.6 current-dollar disposable personal income, account code A067RC and FRED/ALFRED series DSPI, for June 2026 in billions of dollars at a seasonally adjusted annual rate. It is not real DPI or a monthly flow. Resolution retains the ledger's strict first-print ALFRED binding despite its concrete vintage-date discrepancy: 2026-06-25 is the May release date and may not expose the June first print.","Tool call: Fetch BEA's Personal Income and Outlays, May 2026 release for the latest same-variant observations and release mechanics."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["First-print June 2026 disposable personal income","The target is BEA NIPA Table 2.6 current-dollar disposable personal income, account code A067RC and FRED/ALFRED series DSPI, for June 2026 in billions of dollars at a seasonally adjusted annual rate. It is not real DPI or a monthly flow. Resolution retains the ledger's strict first-print ALFRED binding despite its concrete vintage-date discrepancy: 2026-06-25 is the May release date and may not expose the June first print."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 246.7, distribution present, forecast step count 1.","evidence":["Prior/update/interval: use a level-persistence model anchored at the fetched May value of 23651.7 and the four-change January-May 2026 reference class (-13.5, +128.0, -23.5, +164.8). The mean-change prior is +63.95 billion; with no quantitatively supported new June adjustment, the central level is about 23715.7 before ladder interpolation. The sample standard deviation is sqrt(27920.3/3) = 96.5 billion. A normal-reference 80% range is approximately 63.95 +/- 1.282*96.5, or changes of -59.8 to +187.7 billion, corresponding to levels near 23591.9 to 23839.4. The elicited ladder rounds and slightly discretizes that calculation, giving final implied bounds of 23590.0 to 23836.7.","Counter-considerations: upside risk comes from another large transfer, farm-payment, compensation, or proprietors' income increase and would land above the interval if June DSPI exceeds 23836.7. Downside risk comes from tax-payment timing, weaker compensation, or reversal of temporary income and would land below the interval if DSPI is under 23590.0. These are the principal outside the interval scenarios."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["May's $164.9 billion gain was unusually strong and BEA attributed the broader personal-income increase partly to farm proprietors' income from a second round of Supplemental Disaster Relief Program payments. That argues against extrapolating May's full increase. Ordinary nominal income growth is already represented in the recent-change base rate, so no separate wage, employment, or inflation increment is added.","Counter-considerations: upside risk comes from another large transfer, farm-payment, compensation, or proprietors' income increase and would land above the interval if June DSPI exceeds 23836.7. Downside risk comes from tax-payment timing, weaker compensation, or reversal of temporary income and would land below the interval if DSPI is under 23590.0. These are the principal outside the interval scenarios."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: use a level-persistence model anchored at the fetched May value of 23651.7 and the four-change January-May 2026 reference class (-13.5, +128.0, -23.5, +164.8). The mean-change prior is +63.95 billion; with no quantitatively supported new June adjustment, the central level is about 23715.7 before ladder interpolation. The sample standard deviation is sqrt(27920.3/3) = 96.5 billion. A normal-reference 80% range is approximately 63.95 +/- 1.282*96.5, or changes of -59.8 to +187.7 billion, corresponding to levels near 23591.9 to 23839.4. The elicited ladder rounds and slightly discretizes that calculation, giving final implied bounds of 23590.0 to 23836.7.","Counter-considerations: upside risk comes from another large transfer, farm-payment, compensation, or proprietors' income increase and would land above the interval if June DSPI exceeds 23836.7. Downside risk comes from tax-payment timing, weaker compensation, or reversal of temporary income and would land below the interval if DSPI is under 23590.0. These are the principal outside the interval scenarios."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bea-disposable-personal-income-level-june-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-07-30\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bea-disposable-personal-income-level-june-2026.2026-07-10T22-01-54Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-ladder-v2-2026-07-10t22-01-54z.222e35dfe0a70fd6","runId":"run.bea-disposable-personal-income-level-june-2026.2026-07-10T22-01-54Z.bea-disposable-personal-income-level-june-2026-thesis-analyst-ladder-v2-2026-07-10t22-01-54z.222e35dfe0a70fd6","predictionId":"bea-disposable-personal-income-level-june-2026","specId":"spec.bea-disposable-personal-income-level-june-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The base rate/reference class is the March-to-May nominal monthly DSPI changes of +$142.5 billion, -$19.9 billion, and +$164.9 billion. Their average is about +$95.8 billion and their realized range is $184.8 billion; this short, volatile reference class motivates scenario-based 10th–90th ladder width rather than treating a single recent gain as a stable trend.","Prior/update/interval: I use a persistence-plus-recent-change prior centered on the May level of $23,651.7 billion and the March-to-May monthly-change reference class, anchored by levels of $23,506.7, $23,486.8, and $23,651.7 billion. The roughly +$118 billion June update is a conservative extrapolation from that reference class, allowing ordinary compensation and nominal-income growth while discounting May's unusually large farm-income contribution; tax timing and transfer-income noise widen the scenario-based ladder interval."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The target is current-dollar disposable personal income, BEA DSPI / NIPA account A067RC in Table 2.6: billions of dollars at a seasonally adjusted annual rate. This is the same nominal SAAR variant for every anchor; the retained ledger resolver uses the specified ALFRED DSPI first-print binding, while BEA is the underlying official producer.","Tool call: Checked BEA's official 2026 release schedule for the June Personal Income and Outlays release date."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["June 2026 BEA disposable personal income first-print forecast","The target is current-dollar disposable personal income, BEA DSPI / NIPA account A067RC in Table 2.6: billions of dollars at a seasonally adjusted annual rate. This is the same nominal SAAR variant for every anchor; the retained ledger resolver uses the specified ALFRED DSPI first-print binding, while BEA is the underlying official producer."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 155, distribution present, forecast step count 1.","evidence":["Prior/update/interval: I use a persistence-plus-recent-change prior centered on the May level of $23,651.7 billion and the March-to-May monthly-change reference class, anchored by levels of $23,506.7, $23,486.8, and $23,651.7 billion. The roughly +$118 billion June update is a conservative extrapolation from that reference class, allowing ordinary compensation and nominal-income growth while discounting May's unusually large farm-income contribution; tax timing and transfer-income noise widen the scenario-based ladder interval.","Upside risk is another large farm-proprietor payment or stronger-than-assumed compensation growth, which could lift DPI above $23,850 billion. Downside risk is payback after May's farm-income increase, weaker wages, or a larger tax increase; a material retrenchment would land below the interval. A policy or transfer-payment surprise is the principal outside the interval scenario."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Review disposition: Accepted the canonical ALFRED resolver wording, clarified the June update as a conservative March–May extrapolation, and quantified the $184.8 billion realized monthly-change range as the scenario-width input; rejected no forecast-number changes because the ladder remains internally coherent."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: I use a persistence-plus-recent-change prior centered on the May level of $23,651.7 billion and the March-to-May monthly-change reference class, anchored by levels of $23,506.7, $23,486.8, and $23,651.7 billion. The roughly +$118 billion June update is a conservative extrapolation from that reference class, allowing ordinary compensation and nominal-income growth while discounting May's unusually large farm-income contribution; tax timing and transfer-income noise widen the scenario-based ladder interval.","Upside risk is another large farm-proprietor payment or stronger-than-assumed compensation growth, which could lift DPI above $23,850 billion. Downside risk is payback after May's farm-income increase, weaker wages, or a larger tax increase; a material retrenchment would land below the interval. A policy or transfer-payment surprise is the principal outside the interval scenario."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["June 2026 BEA disposable personal income first-print forecast","Prior/update/interval: I use a persistence-plus-recent-change prior centered on the May level of $23,651.7 billion and the March-to-May monthly-change reference class, anchored by levels of $23,506.7, $23,486.8, and $23,651.7 billion. The roughly +$118 billion June update is a conservative extrapolation from that reference class, allowing ordinary compensation and nominal-income growth while discounting May's unusually large farm-income contribution; tax timing and transfer-income noise widen the scenario-based ladder interval."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bea-disposable-personal-income-level-june-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-07-30\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.ons-cpi-annual-rate-june-2026.2026-07-10T06-00-40Z.7f9455aee79f87b0","runId":"run.ons-cpi-annual-rate-june-2026.2026-07-10T06-00-40Z.7f9455aee79f87b0","predictionId":"ons-cpi-annual-rate-june-2026","specId":"spec.ons-cpi-annual-rate-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool call: Opened ONS Consumer price inflation, UK: April 2026 to cross-check prior month dynamics and base effects.","Base rate/reference class: for one-month-ahead forecasts of this exact ONS CPI annual-rate series, the strongest base rate is persistence plus recent monthly changes. The latest three headline CPI annual rates were 3.3%, 2.8%, and 2.8%, averaging 2.97% if using March-May but 2.87% if downweighting March's pre-April energy-price-cap step. Since the June 2025 base month already had a 0.3% monthly CPI rise, June 2026 needs a monthly rise materially above 0.3% to push the annual rate above 2.9%."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: target identity is the ONS Consumer Prices Index all-items 12-month annual rate for June 2026, the non-seasonally-adjusted CPI headline rate. The supplied ledger contract, however, binds the resolver URL and sourceBinding to the May 2026 bulletin and 2026-05 field while the slug/dataPointId say June 2026. I keep the registered slug, URL, date, and dataPointId fields for contract consistency and flag the discrepancy rather than silently changing the target.","Tool call: Opened ONS Consumer price inflation, UK: May 2026 and read release metadata plus Table 1."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["UK CPI June 2026 First-Print Forecast","Tool call: Opened ONS Consumer price inflation, UK: May 2026 and read release metadata plus Table 1."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.8, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is 2.8% from the latest ONS first-print headline, with a reference class of 12 successive monthly changes in the same CPI annual-rate series from May 2025 to May 2026: +0.2, +0.2, 0.0, 0.0, -0.2, -0.4, +0.2, -0.4, 0.0, +0.3, -0.5, 0.0 percentage points. The sample standard deviation of those changes is sigma = 0.27, so an 80% normal half-width is roughly 1.28*sigma = 0.35 percentage points. Level/index arithmetic: May 2026 CPI index 142.4 divided by June 2025 CPI index 138.9 gives 2.52% before June's monthly change; adding a plausible +0.3% to +0.4% June monthly move implies about 2.8% to 2.9%. I add one combined +0.1 percentage point current-pressure adjustment for services, transport, and possible fuel pass-through, giving a 2.9% point estimate; the 80% interval is symmetric before rounding and rounded outward to 2.5% to 3.3% for one-decimal first-print risk.","Counter-considerations: upside risk is a renewed fuel and air-fare jump after the Middle East shock, which would land above the interval if June monthly CPI exceeded about 0.75%. Downside risk is another broad goods and food disinflation month plus falling domestic energy or fuel prices, which would land below the interval if the June monthly CPI change was below about -0.05%. Outside the interval would most likely require a large transport-energy surprise or an unusually broad retail discounting month."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Read ONS May 2026 CPI component table and commentary for current-release pressure points.","Prior/update/interval: persistence prior is 2.8% from the latest ONS first-print headline, with a reference class of 12 successive monthly changes in the same CPI annual-rate series from May 2025 to May 2026: +0.2, +0.2, 0.0, 0.0, -0.2, -0.4, +0.2, -0.4, 0.0, +0.3, -0.5, 0.0 percentage points. The sample standard deviation of those changes is sigma = 0.27, so an 80% normal half-width is roughly 1.28*sigma = 0.35 percentage points. Level/index arithmetic: May 2026 CPI index 142.4 divided by June 2025 CPI index 138.9 gives 2.52% before June's monthly change; adding a plausible +0.3% to +0.4% June monthly move implies about 2.8% to 2.9%. I add one combined +0.1 percentage point current-pressure adjustment for services, transport, and possible fuel pass-through, giving a 2.9% point estimate; the 80% interval is symmetric before rounding and rounded outward to 2.5% to 3.3% for one-decimal first-print risk."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Framing and exact resolver: target identity is the ONS Consumer Prices Index all-items 12-month annual rate for June 2026, the non-seasonally-adjusted CPI headline rate. The supplied ledger contract, however, binds the resolver URL and sourceBinding to the May 2026 bulletin and 2026-05 field while the slug/dataPointId say June 2026. I keep the registered slug, URL, date, and dataPointId fields for contract consistency and flag the discrepancy rather than silently changing the target.","Base rate/reference class: for one-month-ahead forecasts of this exact ONS CPI annual-rate series, the strongest base rate is persistence plus recent monthly changes. The latest three headline CPI annual rates were 3.3%, 2.8%, and 2.8%, averaging 2.97% if using March-May but 2.87% if downweighting March's pre-April energy-price-cap step. Since the June 2025 base month already had a 0.3% monthly CPI rise, June 2026 needs a monthly rise materially above 0.3% to push the annual rate above 2.9%."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["UK CPI June 2026 First-Print Forecast","Framing and exact resolver: target identity is the ONS Consumer Prices Index all-items 12-month annual rate for June 2026, the non-seasonally-adjusted CPI headline rate. The supplied ledger contract, however, binds the resolver URL and sourceBinding to the May 2026 bulletin and 2026-05 field while the slug/dataPointId say June 2026. I keep the registered slug, URL, date, and dataPointId fields for contract consistency and flag the discrepancy rather than silently changing the target."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: ons-cpi-annual-rate-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-21\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.ons-hmrc-paye-payrolled-employees-june-2026.2026-07-10T06-03-13Z.f350c9b5b722f738","runId":"run.ons-hmrc-paye-payrolled-employees-june-2026.2026-07-10T06-03-13Z.f350c9b5b722f738","predictionId":"ons-hmrc-paye-payrolled-employees-june-2026","specId":"spec.ons-hmrc-paye-payrolled-employees-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool call: Opened ONS May 2026 PAYE RTI bulletin for the prior flash and recent reference points.","Reference class and base rate: recent month-to-month first/recent print changes around the target are March -28,000, April -53,000 after revision, and May +2,000. The base rate is a soft labour-market drift of roughly -25,000 to -30,000 per month, but May's flat print and April's upward revision argue against extrapolating the April flash shock one-for-one."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: forecast the ONS/HMRC PAYE RTI seasonally adjusted UK payrolled employees early estimate for June 2026, in millions, first print only. The ledger source URL is the ONS June 2026 bulletin even though that page is already the May 2026 data release; the official next-release date for the dataset is 21 July 2026, so I keep the registered target but flag the URL-period discrepancy.","Tool call: Opened ONS June 2026 PAYE RTI bulletin and release header."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["UK PAYE Payrolled Employees June 2026 First Print","Framing and exact resolver: forecast the ONS/HMRC PAYE RTI seasonally adjusted UK payrolled employees early estimate for June 2026, in millions, first print only. The ledger source URL is the ONS June 2026 bulletin even though that page is already the May 2026 data release; the official next-release date for the dataset is 21 July 2026, so I keep the registered target but flag the URL-period discrepancy."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.11, distribution present, forecast step count 1.","evidence":["Prior/update/interval: the chosen time-series prior is a local persistence-plus-momentum model rather than a broader historical model, because the target is a first-print PAYE flash in a current soft labour-market regime with early-tax-year revision noise. Persistence prior is May 2026 level 30.300 million; historical sample for successive changes is intentionally local at [-0.028, -0.053, 0.002] million from recent ONS prints; adjustment components are level 30.300 plus momentum -0.026 million, softened by May stabilization and early-tax-year upward revision risk to -0.020 million, giving point 30.280 million. For interval, sigma = 0.0275 million from those successive changes; 1.28*sigma = 0.035 million. I widen to 0.055 million, about 1.6x, because ONS states early tax-year flash estimates have greater uncertainty and only about 85% of information is available initially, versus 98% to 99% next month. Final implied bounds: 30.280 - 0.055 = 30.225 and 30.280 + 0.055 = 30.335 million.","Upside risk: a continued payrolling rebound after April revisions, especially if administrative and support services strength persists, would land above the interval with a June move more than about +55,000 versus the adjusted May base. Downside risk: renewed job cuts in accommodation, retail, or small employers after wage and employer-cost pressure would land below the interval with a June move worse than about -55,000 versus the adjusted May base. Outside the interval would require a June move materially larger than roughly +/-55,000 from the adjusted May base."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: the chosen time-series prior is a local persistence-plus-momentum model rather than a broader historical model, because the target is a first-print PAYE flash in a current soft labour-market regime with early-tax-year revision noise. Persistence prior is May 2026 level 30.300 million; historical sample for successive changes is intentionally local at [-0.028, -0.053, 0.002] million from recent ONS prints; adjustment components are level 30.300 plus momentum -0.026 million, softened by May stabilization and early-tax-year upward revision risk to -0.020 million, giving point 30.280 million. For interval, sigma = 0.0275 million from those successive changes; 1.28*sigma = 0.035 million. I widen to 0.055 million, about 1.6x, because ONS states early tax-year flash estimates have greater uncertainty and only about 85% of information is available initially, versus 98% to 99% next month. Final implied bounds: 30.280 - 0.055 = 30.225 and 30.280 + 0.055 = 30.335 million.","Upside risk: a continued payrolling rebound after April revisions, especially if administrative and support services strength persists, would land above the interval with a June move more than about +55,000 versus the adjusted May base. Downside risk: renewed job cuts in accommodation, retail, or small employers after wage and employer-cost pressure would land below the interval with a June move worse than about -55,000 versus the adjusted May base. Outside the interval would require a June move materially larger than roughly +/-55,000 from the adjusted May base."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Framing and exact resolver: forecast the ONS/HMRC PAYE RTI seasonally adjusted UK payrolled employees early estimate for June 2026, in millions, first print only. The ledger source URL is the ONS June 2026 bulletin even though that page is already the May 2026 data release; the official next-release date for the dataset is 21 July 2026, so I keep the registered target but flag the URL-period discrepancy.","Reference class and base rate: recent month-to-month first/recent print changes around the target are March -28,000, April -53,000 after revision, and May +2,000. The base rate is a soft labour-market drift of roughly -25,000 to -30,000 per month, but May's flat print and April's upward revision argue against extrapolating the April flash shock one-for-one."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Framing and exact resolver: forecast the ONS/HMRC PAYE RTI seasonally adjusted UK payrolled employees early estimate for June 2026, in millions, first print only. The ledger source URL is the ONS June 2026 bulletin even though that page is already the May 2026 data release; the official next-release date for the dataset is 21 July 2026, so I keep the registered target but flag the URL-period discrepancy.","Tool call: Opened ONS June 2026 PAYE RTI payrolled-employees section and main points."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: ons-hmrc-paye-payrolled-employees-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-21\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.ons-pusf-j5ii-public-sector-net-borrowing-ex-banks-june-2026.2026-07-10T06-05-54Z.5a426b1a93327249","runId":"run.ons-pusf-j5ii-public-sector-net-borrowing-ex-banks-june-2026.2026-07-10T06-05-54Z.5a426b1a93327249","predictionId":"ons-pusf-j5ii-public-sector-net-borrowing-ex-banks-june-2026","specId":"spec.ons-pusf-j5ii-public-sector-net-borrowing-ex-banks-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool call: Opened ONS Public sector finances, UK: June 2025 bulletin for the prior same-month first-print and debt-interest mechanics.","The reference class base rate is same-month June borrowing. The full 2013-2025 June sample averages about GBP 13.35bn, but the post-2021 regime averages about GBP 19.0bn and the 2025 first print was GBP 20.7bn. Because May 2026 is already GBP 5.6bn above the OBR monthly profile and FY-to-May is GBP 7.7bn above profile, I weight the recent June regime and current-year miss more heavily than the long pre-pandemic base rate."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: the target is ONS public sector net borrowing excluding public sector banks for June 2026, first print, in GBP billions. The ONS time-series page is J5II in GBP millions with the raw accounting sign, while bulletin charts/tables use -J5II so positive numbers indicate a deficit; I forecast the registered borrowing concept in the bulletin convention, positive = borrowing. The ledger URL points to the May 2026 bulletin even though the target month is June 2026; I keep that registered URL, and use its official next-release statement plus the J5II series page to tie the target to the 21 July 2026 first print.","Tool call: Opened ONS J5II time-series page for PUSF and read metadata and latest values."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: the target is ONS public sector net borrowing excluding public sector banks for June 2026, first print, in GBP billions. The ONS time-series page is J5II in GBP millions with the raw accounting sign, while bulletin charts/tables use -J5II so positive numbers indicate a deficit; I forecast the registered borrowing concept in the bulletin convention, positive = borrowing. The ledger URL points to the May 2026 bulletin even though the target month is June 2026; I keep that registered URL, and use its official next-release statement plus the J5II series page to tie the target to the 21 July 2026 first print.","Tool result: Fetched: release date 19 June 2026, next release 21 July 2026, Series ID J5II, units GBP m, 2026 APR raw J5II -23033 and 2026 MAY raw J5II -23294, which convert to GBP 23.033bn and GBP 23.294bn borrowing under the bulletin -J5II convention."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 22, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = June 2025 first print GBP 20.7bn and 2021-2025 June reference-class mean about GBP 19.0bn; adjustments = +GBP 3.0bn for the current FY-to-May overshoot and higher May run rate, +GBP 1.1bn for June debt-interest and spending risk after May debt interest of GBP 11.7bn, giving point GBP 24.8bn. Interval method uses the 2013-2025 June converted values themselves because this is a monthly flow series: sample sigma = 8.6, so 80% half-width is about 1.28*sigma = 1.28*8.6 = 11.0. Final implied bounds are 24.8 - 11.0 = 13.8 and 24.8 + 11.0 = 35.8.","Counter-considerations: upside risk would come from another large index-linked gilt capital-uplift month, weaker PAYE/VAT/corporation tax receipts, or local-government/public-corporation estimates adding to central-government borrowing; a repeat of June 2020-style stress would land above the interval. Downside risk would come from a sharp fall in RPI-linked debt interest, stronger accrued receipts, or unusually low net investment; a clean reversal toward the 2016-2019 June range would land below the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Opened ONS Public sector finances, UK: May 2026 bulletin for current-release drivers, forecast comparison, and next-release date.","Tool result: Fetched current-vintage June converted values, GBP bn: 2013 8.310, 2014 7.930, 2015 7.705, 2016 4.876, 2017 6.458, 2018 4.103, 2019 6.791, 2020 32.165, 2021 18.721, 2022 18.871, 2023 19.085, 2024 14.617, 2025 23.878; the 2025 current-vintage value differs from the June 2025 bulletin first print of GBP 20.7bn because later revisions enter the time-series page."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The reference class base rate is same-month June borrowing. The full 2013-2025 June sample averages about GBP 13.35bn, but the post-2021 regime averages about GBP 19.0bn and the 2025 first print was GBP 20.7bn. Because May 2026 is already GBP 5.6bn above the OBR monthly profile and FY-to-May is GBP 7.7bn above profile, I weight the recent June regime and current-year miss more heavily than the long pre-pandemic base rate.","Prior/update/interval: persistence prior = June 2025 first print GBP 20.7bn and 2021-2025 June reference-class mean about GBP 19.0bn; adjustments = +GBP 3.0bn for the current FY-to-May overshoot and higher May run rate, +GBP 1.1bn for June debt-interest and spending risk after May debt interest of GBP 11.7bn, giving point GBP 24.8bn. Interval method uses the 2013-2025 June converted values themselves because this is a monthly flow series: sample sigma = 8.6, so 80% half-width is about 1.28*sigma = 1.28*8.6 = 11.0. Final implied bounds are 24.8 - 11.0 = 13.8 and 24.8 + 11.0 = 35.8."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["June 2026 UK Public Sector Net Borrowing Forecast","Framing and exact resolver: the target is ONS public sector net borrowing excluding public sector banks for June 2026, first print, in GBP billions. The ONS time-series page is J5II in GBP millions with the raw accounting sign, while bulletin charts/tables use -J5II so positive numbers indicate a deficit; I forecast the registered borrowing concept in the bulletin convention, positive = borrowing. The ledger URL points to the May 2026 bulletin even though the target month is June 2026; I keep that registered URL, and use its official next-release statement plus the J5II series page to tie the target to the 21 July 2026 first print."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: ons-pusf-j5ii-public-sector-net-borrowing-ex-banks-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-21\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-new-home-sales-saar-june-2026.2026-07-10T06-14-40Z.f5521ac5f0e3137e","runId":"run.us-new-home-sales-saar-june-2026.2026-07-10T06-14-40Z.f5521ac5f0e3137e","predictionId":"us-new-home-sales-saar-june-2026","specId":"spec.us-new-home-sales-saar-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate / reference class: for a one-month-ahead forecast of a volatile level series, persistence from the latest same-variant official print is the base rate. The latest observed level is 580 thousand, while the Jan-May 2026 run is 576, 630, 664, 626, 580, so a central June value near the high-500s to low-600s is the outside-view anchor.","Prior/update/interval: persistence prior = May 2026 HSN1F 580. Historical sample = fetched Jan-May 2026 HSN1F values 576, 630, 664, 626, 580. Successive changes are +54, +34, -38, -46; their sample mean is +1 and sigma = 50.4 thousand. Adjustment components are +15 thousand mean reversion after the May drop, -5 thousand for high months' supply and affordability, and 0 thousand for starts/rate context, giving point = 580 + 10 = 590. The 80% half-width is roughly 1.28*sigma = 1.28*50.4 = 64.5, rounded to 65, so bounds are 590 - 65 = 525 and 590 + 65 = 655. Because this sigma comes from only four recent month-to-month changes, it is a rough uncertainty proxy, but the resulting 65 thousand band is retained because recent monthly swings of 34 to 54 thousand plus no clear regime break support a moderately wide rather than extreme interval."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this forecast targets Census/HUD Monthly New Residential Sales, Table 1, Sold during period, United States, seasonally adjusted annual rate, source series HSN1F / RESSALES.SOLD.TOTAL.US.SAAR, for June 2026. The variant is SAAR, not NSA, and the resolution rule is strict first print.","Tool call: Opened Census Survey of Construction release schedule for the New Residential Sales release date."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["US June 2026 new single-family houses sold SAAR first print","Framing and exact resolver: this forecast targets Census/HUD Monthly New Residential Sales, Table 1, Sold during period, United States, seasonally adjusted annual rate, source series HSN1F / RESSALES.SOLD.TOTAL.US.SAAR, for June 2026. The variant is SAAR, not NSA, and the resolution rule is strict first print."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 130, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = May 2026 HSN1F 580. Historical sample = fetched Jan-May 2026 HSN1F values 576, 630, 664, 626, 580. Successive changes are +54, +34, -38, -46; their sample mean is +1 and sigma = 50.4 thousand. Adjustment components are +15 thousand mean reversion after the May drop, -5 thousand for high months' supply and affordability, and 0 thousand for starts/rate context, giving point = 580 + 10 = 590. The 80% half-width is roughly 1.28*sigma = 1.28*50.4 = 64.5, rounded to 65, so bounds are 590 - 65 = 525 and 590 + 65 = 655. Because this sigma comes from only four recent month-to-month changes, it is a rough uncertainty proxy, but the resulting 65 thousand band is retained because recent monthly swings of 34 to 54 thousand plus no clear regime break support a moderately wide rather than extreme interval.","Counter-considerations: upside risk is a builder-incentive or rate-relief rebound that would land above the interval if June first-print sales exceed about 655 thousand; downside risk is another demand freeze or regional pullback that would land below the interval if the first print is under about 525 thousand. A value outside the interval would most likely reflect a large regional swing, especially in the South or West, rather than normal national noise."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Adjustment components: level starts from May's 580; momentum gets a small positive offset because a 46 thousand May drop followed a 38 thousand April drop and some mean reversion is common; high inventory of 496 thousand and 10.3 months' supply offsets that rebound; mortgage rates near 6.5 percent and soft single-family starts argue against a sharp upside breakout.","Prior/update/interval: persistence prior = May 2026 HSN1F 580. Historical sample = fetched Jan-May 2026 HSN1F values 576, 630, 664, 626, 580. Successive changes are +54, +34, -38, -46; their sample mean is +1 and sigma = 50.4 thousand. Adjustment components are +15 thousand mean reversion after the May drop, -5 thousand for high months' supply and affordability, and 0 thousand for starts/rate context, giving point = 580 + 10 = 590. The 80% half-width is roughly 1.28*sigma = 1.28*50.4 = 64.5, rounded to 65, so bounds are 590 - 65 = 525 and 590 + 65 = 655. Because this sigma comes from only four recent month-to-month changes, it is a rough uncertainty proxy, but the resulting 65 thousand band is retained because recent monthly swings of 34 to 54 thousand plus no clear regime break support a moderately wide rather than extreme interval."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Adjustment components: level starts from May's 580; momentum gets a small positive offset because a 46 thousand May drop followed a 38 thousand April drop and some mean reversion is common; high inventory of 496 thousand and 10.3 months' supply offsets that rebound; mortgage rates near 6.5 percent and soft single-family starts argue against a sharp upside breakout.","Prior/update/interval: persistence prior = May 2026 HSN1F 580. Historical sample = fetched Jan-May 2026 HSN1F values 576, 630, 664, 626, 580. Successive changes are +54, +34, -38, -46; their sample mean is +1 and sigma = 50.4 thousand. Adjustment components are +15 thousand mean reversion after the May drop, -5 thousand for high months' supply and affordability, and 0 thousand for starts/rate context, giving point = 580 + 10 = 590. The 80% half-width is roughly 1.28*sigma = 1.28*50.4 = 64.5, rounded to 65, so bounds are 590 - 65 = 525 and 590 + 65 = 655. Because this sigma comes from only four recent month-to-month changes, it is a rough uncertainty proxy, but the resulting 65 thousand band is retained because recent monthly swings of 34 to 54 thousand plus no clear regime break support a moderately wide rather than extreme interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Framing and exact resolver: this forecast targets Census/HUD Monthly New Residential Sales, Table 1, Sold during period, United States, seasonally adjusted annual rate, source series HSN1F / RESSALES.SOLD.TOTAL.US.SAAR, for June 2026. The variant is SAAR, not NSA, and the resolution rule is strict first print.","Base rate / reference class: for a one-month-ahead forecast of a volatile level series, persistence from the latest same-variant official print is the base rate. The latest observed level is 580 thousand, while the Jan-May 2026 run is 576, 630, 664, 626, 580, so a central June value near the high-500s to low-600s is the outside-view anchor."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-new-home-sales-saar-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-24\ntraceLineCount: 19\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-goods-services-trade-deficit-june-2026.2026-07-10T06-17-03Z.211c8dba696a85e6","runId":"run.us-goods-services-trade-deficit-june-2026.2026-07-10T06-17-03Z.211c8dba696a85e6","predictionId":"us-goods-services-trade-deficit-june-2026","specId":"spec.us-goods-services-trade-deficit-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate / reference class: over Jan 2024-May 2026 same-variant monthly deficit values, the mean is 72.9 billion, but that sample includes the early-2025 tariff/gold surge. The cleaner near-term base rate is the 2026 Jan-May average of 59.6 billion and the latest three-month average of 62.9 billion.","Prior/update/interval: no separate formal time-series model was fit; the model prior is May persistence plus same-variant reference-class levels. Primary anchor = May deficit 77.6, cross-checked against the near-term base rate of 59.6 to 62.9. Adjustment components: -8.0 for partial reversal of May gold/export/import spike and -2.6 toward the 2026 YTD base rate, giving point = 77.6 - 8.0 - 2.6 = 67.0. For this change/flow target I used dispersion of same-variant level values, not month-to-month changes, because the forecast is the first-print monthly deficit level and recent one-off trade shifts can persist across adjacent months; sigma = 21.3; 80% half-width = 1.28*sigma = 1.28*21.3 = 27.3; final implied bounds = 67.0 +/- 27.3 = 39.7 to 94.3."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: the target is the first-print June 2026 U.S. goods and services deficit, seasonally adjusted and not price adjusted, from BEA/Census U.S. International Trade in Goods and Services, Exhibit 1. I use the same variant for every anchor: total goods and services balance on a BOP basis, expressed as a positive deficit in USD billions.","Tool call: Read July 7, 2026 BEA/Census PDF full release, Exhibit 1 and text."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: the target is the first-print June 2026 U.S. goods and services deficit, seasonally adjusted and not price adjusted, from BEA/Census U.S. International Trade in Goods and Services, Exhibit 1. I use the same variant for every anchor: total goods and services balance on a BOP basis, expressed as a positive deficit in USD billions.","Tool call: Checked BEA release schedule for U.S. International Trade in Goods and Services, June 2026."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 54.6, distribution present, forecast step count 1.","evidence":["Current-release update: May's 77.6 billion deficit is a high starting point, but the release attributes the jump to a goods deficit increase, lower goods exports including nonmonetary gold, and higher goods imports including pharmaceuticals, autos, computer accessories, and semiconductors. Those categories argue for some persistence from strong import demand but also partial one-month reversal risk.","Prior/update/interval: no separate formal time-series model was fit; the model prior is May persistence plus same-variant reference-class levels. Primary anchor = May deficit 77.6, cross-checked against the near-term base rate of 59.6 to 62.9. Adjustment components: -8.0 for partial reversal of May gold/export/import spike and -2.6 toward the 2026 YTD base rate, giving point = 77.6 - 8.0 - 2.6 = 67.0. For this change/flow target I used dispersion of same-variant level values, not month-to-month changes, because the forecast is the first-print monthly deficit level and recent one-off trade shifts can persist across adjacent months; sigma = 21.3; 80% half-width = 1.28*sigma = 1.28*21.3 = 27.3; final implied bounds = 67.0 +/- 27.3 = 39.7 to 94.3."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: no separate formal time-series model was fit; the model prior is May persistence plus same-variant reference-class levels. Primary anchor = May deficit 77.6, cross-checked against the near-term base rate of 59.6 to 62.9. Adjustment components: -8.0 for partial reversal of May gold/export/import spike and -2.6 toward the 2026 YTD base rate, giving point = 77.6 - 8.0 - 2.6 = 67.0. For this change/flow target I used dispersion of same-variant level values, not month-to-month changes, because the forecast is the first-print monthly deficit level and recent one-off trade shifts can persist across adjacent months; sigma = 21.3; 80% half-width = 1.28*sigma = 1.28*21.3 = 27.3; final implied bounds = 67.0 +/- 27.3 = 39.7 to 94.3."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate / reference class: over Jan 2024-May 2026 same-variant monthly deficit values, the mean is 72.9 billion, but that sample includes the early-2025 tariff/gold surge. The cleaner near-term base rate is the 2026 Jan-May average of 59.6 billion and the latest three-month average of 62.9 billion.","Current-release update: May's 77.6 billion deficit is a high starting point, but the release attributes the jump to a goods deficit increase, lower goods exports including nonmonetary gold, and higher goods imports including pharmaceuticals, autos, computer accessories, and semiconductors. Those categories argue for some persistence from strong import demand but also partial one-month reversal risk."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for June 2026 U.S. goods and services trade deficit","Current-release update: May's 77.6 billion deficit is a high starting point, but the release attributes the jump to a goods deficit increase, lower goods exports including nonmonetary gold, and higher goods imports including pharmaceuticals, autos, computer accessories, and semiconductors. Those categories argue for some persistence from strong import demand but also partial one-month reversal risk."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-goods-services-trade-deficit-june-2026\nrunLabel: Headline\nresolutionDate: 2026-08-04\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T05-23-13Z.cd261b8e06ee3325","runId":"run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T05-23-13Z.cd261b8e06ee3325","predictionId":"us-real-avg-hourly-earnings-mom-july-2026","specId":"spec.us-real-avg-hourly-earnings-mom-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: the directly fetched real-AHE over-the-month reference class from the current Table A-1 is 0.4, -0.6, -0.5, and -0.1 percent, averaging -0.2 percent; the recent base rate is therefore negative real wage growth when headline CPI is running above the nominal hourly earnings pace.","Prior/update/interval: persistence prior is the recent BLS Table A-1 real-AHE MoM base rate using fetched values [0.4, -0.6, -0.5, -0.1], mean = -0.20. Adjustment components are +0.10 for steady nominal wage growth near 0.3% and -0.05 for CPI still elevated but not as extreme as May, giving point near -0.15, rounded to -0.1. Interval method uses realized dispersion of the fetched change values themselves because this is a change series and the small four-observation sample makes the 80% interval deliberately approximate: sigma = 0.45, so 80% half-width is roughly 1.28*sigma = 1.28*0.45 = 0.58; around -0.1 this gives about [-0.68, 0.48], rounded to [-0.7, 0.5]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this is the BLS Real Earnings Table A-1 series for real average hourly earnings for all employees on private nonfarm payrolls, seasonally adjusted, over-the-month percent change. The table says CPI-U is used to deflate the earnings series, so all anchors here use the same SA all-employees private payroll earnings variant and CPI-U deflator.","Tool call: BLS Real Earnings release calendar lookup for July 2026 reference month"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["US real average hourly earnings MoM, July 2026 first print","Tool call: BLS Real Earnings release calendar lookup for July 2026 reference month"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.2, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is the recent BLS Table A-1 real-AHE MoM base rate using fetched values [0.4, -0.6, -0.5, -0.1], mean = -0.20. Adjustment components are +0.10 for steady nominal wage growth near 0.3% and -0.05 for CPI still elevated but not as extreme as May, giving point near -0.15, rounded to -0.1. Interval method uses realized dispersion of the fetched change values themselves because this is a change series and the small four-observation sample makes the 80% interval deliberately approximate: sigma = 0.45, so 80% half-width is roughly 1.28*sigma = 1.28*0.45 = 0.58; around -0.1 this gives about [-0.68, 0.48], rounded to [-0.7, 0.5].","Counter-consideration: upside risk is a July CPI relief print, especially an energy reversal, combined with another 0.3-0.4 percent nominal wage month, which would land above the interval. Downside risk is another gasoline or broad services CPI spike with only 0.2 percent nominal wage growth, which would land below the interval. Outside the interval would require roughly real AHE above +0.5 percent or below -0.7 percent on the first print."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Current-release adjustment: nominal wage momentum is still near 0.3 percent monthly, using June Table B-3's $37.64 versus $37.51 as a live wage anchor. CPI momentum is less favorable, with the latest all-items CPI-U monthly gains 0.9, 0.6, and 0.5 percent, but some May energy pressure could partly mean-revert by July. Combining a July nominal AHE assumption near +0.30 percent with a CPI-U assumption near +0.35 to +0.40 percent points to a small negative real hourly earnings print.","Prior/update/interval: persistence prior is the recent BLS Table A-1 real-AHE MoM base rate using fetched values [0.4, -0.6, -0.5, -0.1], mean = -0.20. Adjustment components are +0.10 for steady nominal wage growth near 0.3% and -0.05 for CPI still elevated but not as extreme as May, giving point near -0.15, rounded to -0.1. Interval method uses realized dispersion of the fetched change values themselves because this is a change series and the small four-observation sample makes the 80% interval deliberately approximate: sigma = 0.45, so 80% half-width is roughly 1.28*sigma = 1.28*0.45 = 0.58; around -0.1 this gives about [-0.68, 0.48], rounded to [-0.7, 0.5]."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Current-release adjustment: nominal wage momentum is still near 0.3 percent monthly, using June Table B-3's $37.64 versus $37.51 as a live wage anchor. CPI momentum is less favorable, with the latest all-items CPI-U monthly gains 0.9, 0.6, and 0.5 percent, but some May energy pressure could partly mean-revert by July. Combining a July nominal AHE assumption near +0.30 percent with a CPI-U assumption near +0.35 to +0.40 percent points to a small negative real hourly earnings print.","Prior/update/interval: persistence prior is the recent BLS Table A-1 real-AHE MoM base rate using fetched values [0.4, -0.6, -0.5, -0.1], mean = -0.20. Adjustment components are +0.10 for steady nominal wage growth near 0.3% and -0.05 for CPI still elevated but not as extreme as May, giving point near -0.15, rounded to -0.1. Interval method uses realized dispersion of the fetched change values themselves because this is a change series and the small four-observation sample makes the 80% interval deliberately approximate: sigma = 0.45, so 80% half-width is roughly 1.28*sigma = 1.28*0.45 = 0.58; around -0.1 this gives about [-0.68, 0.48], rounded to [-0.7, 0.5]."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Current-release adjustment: nominal wage momentum is still near 0.3 percent monthly, using June Table B-3's $37.64 versus $37.51 as a live wage anchor. CPI momentum is less favorable, with the latest all-items CPI-U monthly gains 0.9, 0.6, and 0.5 percent, but some May energy pressure could partly mean-revert by July. Combining a July nominal AHE assumption near +0.30 percent with a CPI-U assumption near +0.35 to +0.40 percent points to a small negative real hourly earnings print.","Prior/update/interval: persistence prior is the recent BLS Table A-1 real-AHE MoM base rate using fetched values [0.4, -0.6, -0.5, -0.1], mean = -0.20. Adjustment components are +0.10 for steady nominal wage growth near 0.3% and -0.05 for CPI still elevated but not as extreme as May, giving point near -0.15, rounded to -0.1. Interval method uses realized dispersion of the fetched change values themselves because this is a change series and the small four-observation sample makes the 80% interval deliberately approximate: sigma = 0.45, so 80% half-width is roughly 1.28*sigma = 1.28*0.45 = 0.58; around -0.1 this gives about [-0.68, 0.48], rounded to [-0.7, 0.5]."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-real-avg-hourly-earnings-mom-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-12\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T15-12-31Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-fast-2026-07-10t15-12-31z.82c4ee519f2c140a","runId":"run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T15-12-31Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-fast-2026-07-10t15-12-31z.82c4ee519f2c140a","predictionId":"us-real-avg-hourly-earnings-mom-july-2026","specId":"spec.us-real-avg-hourly-earnings-mom-july-2026","runLabel":"Fast rollout 1 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Tool call: BLS Real Earnings Table A-1 historical lookup","The base rate/reference class is the five available 2026 monthly first-print changes before the target: mostly small positive or negative moves, with a recent mean of -0.16 percent. June nominal wage growth of 0.3 percent suggests a modest positive real result if July CPI inflation is contained, while the recent inflation-adjusted pattern argues against a large increase."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["The target is the seasonally adjusted all-private-employees series in BLS Real Earnings Table A-1, resolved to the first July 2026 print on the official release page without later revision.","Tool call: BLS release calendar lookup for the exact resolution date"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The target is the seasonally adjusted all-private-employees series in BLS Real Earnings Table A-1, resolved to the first July 2026 print on the official release page without later revision.","Tool call: BLS release calendar lookup for the exact resolution date"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.8, distribution present, forecast step count 1.","evidence":["Prior/update/interval: the persistence prior uses the five fetched January-May 2026 Table A-1 changes [0.3, 0.1, -0.6, -0.5, -0.1]; the current update is nominal wage momentum of 0.3 percent and an assumed near-offset from July CPI; sigma = 0.34 percentage points, calculated as the population standard deviation of those five change values; the 80% half-width is roughly 1.28*0.34 = 0.44, rounded to one decimal, giving final implied bounds of -0.3 to 0.5 percent.","Upside risk is a July CPI increase below the recent wage pace, which would land above the interval if real hourly earnings rise at least 0.6 percent. Downside risk is a CPI reacceleration or weaker nominal wage growth; a real decline of -0.4 percent or less would land outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["A persistence-and-current-momentum model combines the recent real-change mean with a modest upward adjustment for the latest 0.3-percent nominal wage increase, producing a central estimate near 0.1 percent.","Prior/update/interval: the persistence prior uses the five fetched January-May 2026 Table A-1 changes [0.3, 0.1, -0.6, -0.5, -0.1]; the current update is nominal wage momentum of 0.3 percent and an assumed near-offset from July CPI; sigma = 0.34 percentage points, calculated as the population standard deviation of those five change values; the 80% half-width is roughly 1.28*0.34 = 0.44, rounded to one decimal, giving final implied bounds of -0.3 to 0.5 percent."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: the persistence prior uses the five fetched January-May 2026 Table A-1 changes [0.3, 0.1, -0.6, -0.5, -0.1]; the current update is nominal wage momentum of 0.3 percent and an assumed near-offset from July CPI; sigma = 0.34 percentage points, calculated as the population standard deviation of those five change values; the 80% half-width is roughly 1.28*0.34 = 0.44, rounded to one decimal, giving final implied bounds of -0.3 to 0.5 percent.","Upside risk is a July CPI increase below the recent wage pace, which would land above the interval if real hourly earnings rise at least 0.6 percent. Downside risk is a CPI reacceleration or weaker nominal wage growth; a real decline of -0.4 percent or less would land outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for July 2026 real average hourly earnings month-over-month change","Prior/update/interval: the persistence prior uses the five fetched January-May 2026 Table A-1 changes [0.3, 0.1, -0.6, -0.5, -0.1]; the current update is nominal wage momentum of 0.3 percent and an assumed near-offset from July CPI; sigma = 0.34 percentage points, calculated as the population standard deviation of those five change values; the 80% half-width is roughly 1.28*0.34 = 0.44, rounded to one decimal, giving final implied bounds of -0.3 to 0.5 percent."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-real-avg-hourly-earnings-mom-july-2026\nrunLabel: Fast rollout 1 of 3\nresolutionDate: 2026-08-12\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T15-15-40Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-fast-2026-07-10t15-15-40z.285af2fa1f4570d5","runId":"run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T15-15-40Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-fast-2026-07-10t15-15-40z.285af2fa1f4570d5","predictionId":"us-real-avg-hourly-earnings-mom-july-2026","specId":"spec.us-real-avg-hourly-earnings-mom-july-2026","runLabel":"Fast rollout 2 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["The base rate is centered near zero but has recently shifted negative: four of the five available 2026 monthly observations were at or below zero, while nominal earnings growth provides a countervailing positive force. The relevant variant is gross real average hourly earnings for all private nonfarm employees, seasonally adjusted, specifically BLS Table A-1.","The persistence prior points to a small negative July result because April and May were -0.5% and -0.1%, while the June nominal wage increase limits the downside absent another inflation surge. I therefore use -0.1% as the modal one-decimal outcome."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["The target is the first-print, seasonally adjusted Table A-1 value for all employees on private nonfarm payrolls, resolved from the BLS Real Earnings release without later revisions. The BLS release calendar verifies July 2026 Real Earnings publication on August 12, 2026.","Tool call: Fetch BLS Real Earnings Table A-1 recent monthly history"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the first-print, seasonally adjusted Table A-1 value for all employees on private nonfarm payrolls, resolved from the BLS Real Earnings release without later revisions. The BLS release calendar verifies July 2026 Real Earnings publication on August 12, 2026.","Tool call: Fetch BLS inflation reference and release schedule"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1, distribution present, forecast step count 1.","evidence":["Prior/update/interval: The persistence prior is the five-point January-May 2026 reference class [0.3, 0.2, -0.6, -0.5, -0.1]. For this change series, sigma is computed from the values themselves: mean = -0.14, sigma = 0.36, and the nominal 80% half-width is roughly 1.28*sigma = 0.46. Rounding to the BLS one-decimal unit gives an interval of -0.6% to 0.4%; the recent inflation shock and release-to-release volatility justify retaining that full width.","Downside risk is a July CPI acceleration combined with weak nominal wage growth, which could produce a result below -0.6%. Upside risk is softer inflation with another 0.3% or larger nominal wage increase, which could land above 0.4%; those are the concrete cases outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The persistence prior points to a small negative July result because April and May were -0.5% and -0.1%, while the June nominal wage increase limits the downside absent another inflation surge. I therefore use -0.1% as the modal one-decimal outcome."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The base rate is centered near zero but has recently shifted negative: four of the five available 2026 monthly observations were at or below zero, while nominal earnings growth provides a countervailing positive force. The relevant variant is gross real average hourly earnings for all private nonfarm employees, seasonally adjusted, specifically BLS Table A-1.","Downside risk is a July CPI acceleration combined with weak nominal wage growth, which could produce a result below -0.6%. Upside risk is softer inflation with another 0.3% or larger nominal wage increase, which could land above 0.4%; those are the concrete cases outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: July 2026 real average hourly earnings month-over-month change","The persistence prior points to a small negative July result because April and May were -0.5% and -0.1%, while the June nominal wage increase limits the downside absent another inflation surge. I therefore use -0.1% as the modal one-decimal outcome."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-real-avg-hourly-earnings-mom-july-2026\nrunLabel: Fast rollout 2 of 3\nresolutionDate: 2026-08-12\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T15-18-50Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-fast-2026-07-10t15-18-50z.b5df820cf1af93ea","runId":"run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T15-18-50Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-fast-2026-07-10t15-18-50z.b5df820cf1af93ea","predictionId":"us-real-avg-hourly-earnings-mom-july-2026","specId":"spec.us-real-avg-hourly-earnings-mom-july-2026","runLabel":"Fast rollout 3 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Tool call: BLS Real Earnings Table A-1 historical reference class","The base rate/reference class is the four available 2026 Table A-1 monthly changes, whose mean is -0.25%. The June nominal wage increase supports some improvement, but real earnings still depend on the not-yet-released July CPI and recent real outcomes have been weak."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The target is the first-print, one-decimal, seasonally adjusted Table A-1 value for all employees on private nonfarm payrolls. The BLS schedule places July Real Earnings on August 12, 2026 at 08:30 ET, verifying the resolution date.","Tool call: BLS Real Earnings Table A-1 historical reference class"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The target is the first-print, one-decimal, seasonally adjusted Table A-1 value for all employees on private nonfarm payrolls. The BLS schedule places July Real Earnings on August 12, 2026 at 08:30 ET, verifying the resolution date.","Tool call: BLS official release calendar verification"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.8, distribution present, forecast step count 1.","evidence":["Level, momentum, and one-off effects are separated as follows: the level is modestly positive nominal wage growth; momentum is the recent run of -0.6%, -0.5%, and -0.1% real changes; the main one-off risk is monthly CPI volatility; the policy mechanism is ordinary BLS deflation of nominal earnings by CPI-U, with no policy-rate conditioning.","For the change series, fetched values themselves are used: [0.2, -0.6, -0.5, -0.1]. Their population standard deviation is sigma = 0.32 percentage points, so the 80% half-width is roughly 1.28*0.32 = 0.41. Centering near -0.2 gives an interval approximately [-0.6, 0.2], close to the dispersion-based width."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, and one-off effects are separated as follows: the level is modestly positive nominal wage growth; momentum is the recent run of -0.6%, -0.5%, and -0.1% real changes; the main one-off risk is monthly CPI volatility; the policy mechanism is ordinary BLS deflation of nominal earnings by CPI-U, with no policy-rate conditioning."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The base rate/reference class is the four available 2026 Table A-1 monthly changes, whose mean is -0.25%. The June nominal wage increase supports some improvement, but real earnings still depend on the not-yet-released July CPI and recent real outcomes have been weak.","Level, momentum, and one-off effects are separated as follows: the level is modestly positive nominal wage growth; momentum is the recent run of -0.6%, -0.5%, and -0.1% real changes; the main one-off risk is monthly CPI volatility; the policy mechanism is ordinary BLS deflation of nominal earnings by CPI-U, with no policy-rate conditioning."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: July 2026 real average hourly earnings monthly change","For the change series, fetched values themselves are used: [0.2, -0.6, -0.5, -0.1]. Their population standard deviation is sigma = 0.32 percentage points, so the 80% half-width is roughly 1.28*0.32 = 0.41. Centering near -0.2 gives an interval approximately [-0.6, 0.2], close to the dispersion-based width."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-real-avg-hourly-earnings-mom-july-2026\nrunLabel: Fast rollout 3 of 3\nresolutionDate: 2026-08-12\ntraceLineCount: 13\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T15-19-26Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-median3-2026-07-10t15-19-26z.eeef4e18b65ab1ed","runId":"run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T15-19-26Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-median3-2026-07-10t15-19-26z.eeef4e18b65ab1ed","predictionId":"us-real-avg-hourly-earnings-mom-july-2026","specId":"spec.us-real-avg-hourly-earnings-mom-july-2026","runLabel":"Median of 3 rollouts","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 6 historical point(s) and implicit outside-view language.","evidence":["Median-of-3 rollout ensemble","Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T15:12:31Z, 2026-07-10T15:15:40Z, 2026-07-10T15:18:50Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 8 source-context item(s), activity log present.","evidence":["Median CDF quantiles: q10 = -0.6, q50 = -0.1, q90 = 0.4. Constituent points [0.1, -0.1, -0.2] with 80% widths [0.8, 1.0, 0.8]; the median interval inherits the central rollout mass rather than averaging tails."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1, distribution present, forecast step count 1.","evidence":["Median CDF quantiles: q10 = -0.6, q50 = -0.1, q90 = 0.4. Constituent points [0.1, -0.1, -0.2] with 80% widths [0.8, 1.0, 0.8]; the median interval inherits the central rollout mass rather than averaging tails.","Forecast: point -0.1, 80% interval [-0.6, 0.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T15:12:31Z, 2026-07-10T15:15:40Z, 2026-07-10T15:18:50Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T15:12:31Z, 2026-07-10T15:15:40Z, 2026-07-10T15:18:50Z. Drivers and resolver fields mirror the rollout closest to the median.","Tool result: {rollout_points: [0.1, -0.1, -0.2], rollout_widths: [0.8, 1.0, 0.8], q10: -0.6, q50: -0.1, q90: 0.4}"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-real-avg-hourly-earnings-mom-july-2026\nrunLabel: Median of 3 rollouts\nresolutionDate: 2026-08-12\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T15-39-47Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-fast-2026-07-10t15-39-47z.285af2fa1f4570d5","runId":"run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T15-39-47Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-fast-2026-07-10t15-39-47z.285af2fa1f4570d5","predictionId":"us-real-avg-hourly-earnings-mom-july-2026","specId":"spec.us-real-avg-hourly-earnings-mom-july-2026","runLabel":"Fast rollout 1 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["The five-observation reference class has a base rate of -0.16 percent per month: January through May were 0.3, 0.1, -0.6, -0.5, and -0.1 percent. The latest two releases show real pay falling as CPI-U outran modest nominal wage gains, so the baseline remains slightly negative.","Prior/update/interval: Persistence prior is the January-May 2026 first-print Table A-1 change sample [0.3, 0.1, -0.6, -0.5, -0.1], with mean = -0.16 and sample sigma = 0.38 percentage points. The adjustment components are a +0.1 point pull from June's 0.3 percent nominal-pay growth, offset by continued CPI-U deflator uncertainty and no assumed July CPI slowdown, yielding -0.1 percent. The 80% half-width is 1.28*0.38 = 0.49 percentage points; rounded to the release's one-decimal precision, implied bounds are -0.6 to 0.4 percent."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The resolver is BLS Real Earnings Table A-1: the seasonally adjusted over-the-month percent change in real average hourly earnings for all employees on private nonfarm payrolls. This is the all-employees, CPI-U-deflated variant, not the production-and-nonsupervisory CPI-W series; resolve only to the July first print, rounded to BLS's one decimal, with no later revision substitution.","Tool call: Checked the BLS August 2026 release calendar for the July Real Earnings release date."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is BLS Real Earnings Table A-1: the seasonally adjusted over-the-month percent change in real average hourly earnings for all employees on private nonfarm payrolls. This is the all-employees, CPI-U-deflated variant, not the production-and-nonsupervisory CPI-W series; resolve only to the July first print, rounded to BLS's one decimal, with no later revision substitution.","Tool call: Checked the BLS August 2026 release calendar for the July Real Earnings release date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1, distribution present, forecast step count 1.","evidence":["Prior/update/interval: Persistence prior is the January-May 2026 first-print Table A-1 change sample [0.3, 0.1, -0.6, -0.5, -0.1], with mean = -0.16 and sample sigma = 0.38 percentage points. The adjustment components are a +0.1 point pull from June's 0.3 percent nominal-pay growth, offset by continued CPI-U deflator uncertainty and no assumed July CPI slowdown, yielding -0.1 percent. The 80% half-width is 1.28*0.38 = 0.49 percentage points; rounded to the release's one-decimal precision, implied bounds are -0.6 to 0.4 percent.","upside risk: a July CPI-U print near zero alongside another roughly 0.3 percent nominal hourly-pay gain would lift real earnings above 0.4 percent. downside risk: a CPI-U increase materially above nominal wage growth, or a weak/negative nominal-pay print, would land below -0.6 percent. A sharp energy-driven CPI move or unusual seasonal-factor outcome is the main outside the interval scenario."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: Persistence prior is the January-May 2026 first-print Table A-1 change sample [0.3, 0.1, -0.6, -0.5, -0.1], with mean = -0.16 and sample sigma = 0.38 percentage points. The adjustment components are a +0.1 point pull from June's 0.3 percent nominal-pay growth, offset by continued CPI-U deflator uncertainty and no assumed July CPI slowdown, yielding -0.1 percent. The 80% half-width is 1.28*0.38 = 0.49 percentage points; rounded to the release's one-decimal precision, implied bounds are -0.6 to 0.4 percent.","upside risk: a July CPI-U print near zero alongside another roughly 0.3 percent nominal hourly-pay gain would lift real earnings above 0.4 percent. downside risk: a CPI-U increase materially above nominal wage growth, or a weak/negative nominal-pay print, would land below -0.6 percent. A sharp energy-driven CPI move or unusual seasonal-factor outcome is the main outside the interval scenario."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["July 2026 real average hourly earnings forecast","Prior/update/interval: Persistence prior is the January-May 2026 first-print Table A-1 change sample [0.3, 0.1, -0.6, -0.5, -0.1], with mean = -0.16 and sample sigma = 0.38 percentage points. The adjustment components are a +0.1 point pull from June's 0.3 percent nominal-pay growth, offset by continued CPI-U deflator uncertainty and no assumed July CPI slowdown, yielding -0.1 percent. The 80% half-width is 1.28*0.38 = 0.49 percentage points; rounded to the release's one-decimal precision, implied bounds are -0.6 to 0.4 percent."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-real-avg-hourly-earnings-mom-july-2026\nrunLabel: Fast rollout 1 of 3\nresolutionDate: 2026-08-12\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T15-43-51Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-fast-2026-07-10t15-43-51z.0f079ef596c823a5","runId":"run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T15-43-51Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-fast-2026-07-10t15-43-51z.0f079ef596c823a5","predictionId":"us-real-avg-hourly-earnings-mom-july-2026","specId":"spec.us-real-avg-hourly-earnings-mom-july-2026","runLabel":"Fast rollout 2 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["The reference class is monthly, seasonally adjusted Table A-1 real hourly-earnings changes. The recent base rate is slightly negative after January through May values of 0.3, 0.2, -0.6, -0.5, and -0.1 percent, but the most recent two observations show the contraction decelerating.","Prior/update/interval: I use a zero-centered persistence prior with the five fetched Table A-1 change observations (0.3, 0.2, -0.6, -0.5, -0.1). Their mean is -0.14 and population sigma = 0.36 percentage points; 1.28*sigma = 0.46 percentage points. I update the prior to 0.1 percent because May's -0.1 followed the earlier -0.6 and -0.5 declines, while the nominal-wage-minus-CPI mechanism can return a modest positive reading. Rounding the approximately 0.46-point half-width to the publication grid gives an 80% interval of -0.4 to 0.6 percent."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["The resolver is BLS Real Earnings Table A-1: the seasonally adjusted over-the-month percent change in real average hourly earnings for all employees on private nonfarm payrolls. Anchors and history below use this same Table A-1 all-employees, seasonally adjusted variant; this target resolves to its first printed one-decimal value, without later revision.","Tool call: Fetched the official BLS August 2026 release-calendar entry for the target release date."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["July 2026 real average hourly earnings first print","The resolver is BLS Real Earnings Table A-1: the seasonally adjusted over-the-month percent change in real average hourly earnings for all employees on private nonfarm payrolls. Anchors and history below use this same Table A-1 all-employees, seasonally adjusted variant; this target resolves to its first printed one-decimal value, without later revision."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1, distribution present, forecast step count 1.","evidence":["Prior/update/interval: I use a zero-centered persistence prior with the five fetched Table A-1 change observations (0.3, 0.2, -0.6, -0.5, -0.1). Their mean is -0.14 and population sigma = 0.36 percentage points; 1.28*sigma = 0.46 percentage points. I update the prior to 0.1 percent because May's -0.1 followed the earlier -0.6 and -0.5 declines, while the nominal-wage-minus-CPI mechanism can return a modest positive reading. Rounding the approximately 0.46-point half-width to the publication grid gives an 80% interval of -0.4 to 0.6 percent.","Upside risk is a July nominal-pay acceleration combined with subdued CPI-U, which would land above the interval if real hourly earnings rise more than 0.6 percent. Downside risk is another inflation overshoot or unfavorable high-wage/low-wage payroll-composition shift; a sufficiently large combination would land below the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: I use a zero-centered persistence prior with the five fetched Table A-1 change observations (0.3, 0.2, -0.6, -0.5, -0.1). Their mean is -0.14 and population sigma = 0.36 percentage points; 1.28*sigma = 0.46 percentage points. I update the prior to 0.1 percent because May's -0.1 followed the earlier -0.6 and -0.5 declines, while the nominal-wage-minus-CPI mechanism can return a modest positive reading. Rounding the approximately 0.46-point half-width to the publication grid gives an 80% interval of -0.4 to 0.6 percent."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The reference class is monthly, seasonally adjusted Table A-1 real hourly-earnings changes. The recent base rate is slightly negative after January through May values of 0.3, 0.2, -0.6, -0.5, and -0.1 percent, but the most recent two observations show the contraction decelerating.","Upside risk is a July nominal-pay acceleration combined with subdued CPI-U, which would land above the interval if real hourly earnings rise more than 0.6 percent. Downside risk is another inflation overshoot or unfavorable high-wage/low-wage payroll-composition shift; a sufficiently large combination would land below the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: I use a zero-centered persistence prior with the five fetched Table A-1 change observations (0.3, 0.2, -0.6, -0.5, -0.1). Their mean is -0.14 and population sigma = 0.36 percentage points; 1.28*sigma = 0.46 percentage points. I update the prior to 0.1 percent because May's -0.1 followed the earlier -0.6 and -0.5 declines, while the nominal-wage-minus-CPI mechanism can return a modest positive reading. Rounding the approximately 0.46-point half-width to the publication grid gives an 80% interval of -0.4 to 0.6 percent.","Upside risk is a July nominal-pay acceleration combined with subdued CPI-U, which would land above the interval if real hourly earnings rise more than 0.6 percent. Downside risk is another inflation overshoot or unfavorable high-wage/low-wage payroll-composition shift; a sufficiently large combination would land below the interval."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-real-avg-hourly-earnings-mom-july-2026\nrunLabel: Fast rollout 2 of 3\nresolutionDate: 2026-08-12\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T15-47-55Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-fast-2026-07-10t15-47-55z.6141e6531669d1b8","runId":"run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T15-47-55Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-fast-2026-07-10t15-47-55z.6141e6531669d1b8","predictionId":"us-real-avg-hourly-earnings-mom-july-2026","specId":"spec.us-real-avg-hourly-earnings-mom-july-2026","runLabel":"Fast rollout 3 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the available eleven monthly Table A-1 changes average about -0.07 percent and are centered near zero, with recent March-through-May inflation outpacing nominal hourly-pay growth. The June 0.3 percent nominal wage increase offsets part of that recent weakness but does not by itself imply a positive real print.","Prior/update/interval: persistence prior is the available May 2025-May 2026 Table A-1 monthly-change sample [0.4,-0.1,0.1,0.1,-0.1,-0.3,0.3,0.0,-0.6,-0.5,-0.1], with mean -0.07 percent; adjustment components are June's 0.3 percent nominal hourly-pay momentum, likely near-matching CPI-U inflation, and composition/seasonal noise. For this change series, sigma = 0.31 percentage points (sample standard deviation of the fetched values); 1.28*sigma = 1.28*0.31 = 0.40 percentage points. Rounding the implied -0.07 percent center to the release's one-decimal convention gives -0.1 percent and bounds of -0.5 to 0.3 percent."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The resolver is BLS Real Earnings Table A-1, not the production-and-nonsupervisory Table A-2: the required variant is all employees on private nonfarm payrolls, seasonally adjusted, over-the-month percent change in real average hourly earnings. Table A-1 uses CPI-U as its deflator.","Tool call: Fetched the BLS 2026 release calendar to verify the publication date for the target release."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Tool call: Fetched the BLS 2026 release calendar to verify the publication date for the target release.","Tool call: Fetched current BLS Real Earnings Table A-1 for the latest published all-employees, seasonally adjusted observations."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.8, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is the available May 2025-May 2026 Table A-1 monthly-change sample [0.4,-0.1,0.1,0.1,-0.1,-0.3,0.3,0.0,-0.6,-0.5,-0.1], with mean -0.07 percent; adjustment components are June's 0.3 percent nominal hourly-pay momentum, likely near-matching CPI-U inflation, and composition/seasonal noise. For this change series, sigma = 0.31 percentage points (sample standard deviation of the fetched values); 1.28*sigma = 1.28*0.31 = 0.40 percentage points. Rounding the implied -0.07 percent center to the release's one-decimal convention gives -0.1 percent and bounds of -0.5 to 0.3 percent.","Upside risk: a July nominal-pay gain around 0.4 percent with CPI-U inflation near 0.1 percent would land at about 0.3 percent. Downside risk: a renewed CPI-U increase near 0.7 percent alongside only 0.1 percent nominal wage growth would land below the interval, around -0.6 percent. A large industry-composition shift could also put the first print outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior is the available May 2025-May 2026 Table A-1 monthly-change sample [0.4,-0.1,0.1,0.1,-0.1,-0.3,0.3,0.0,-0.6,-0.5,-0.1], with mean -0.07 percent; adjustment components are June's 0.3 percent nominal hourly-pay momentum, likely near-matching CPI-U inflation, and composition/seasonal noise. For this change series, sigma = 0.31 percentage points (sample standard deviation of the fetched values); 1.28*sigma = 1.28*0.31 = 0.40 percentage points. Rounding the implied -0.07 percent center to the release's one-decimal convention gives -0.1 percent and bounds of -0.5 to 0.3 percent."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: the available eleven monthly Table A-1 changes average about -0.07 percent and are centered near zero, with recent March-through-May inflation outpacing nominal hourly-pay growth. The June 0.3 percent nominal wage increase offsets part of that recent weakness but does not by itself imply a positive real print.","Upside risk: a July nominal-pay gain around 0.4 percent with CPI-U inflation near 0.1 percent would land at about 0.3 percent. Downside risk: a renewed CPI-U increase near 0.7 percent alongside only 0.1 percent nominal wage growth would land below the interval, around -0.6 percent. A large industry-composition shift could also put the first print outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["July 2026 real average hourly earnings forecast","Prior/update/interval: persistence prior is the available May 2025-May 2026 Table A-1 monthly-change sample [0.4,-0.1,0.1,0.1,-0.1,-0.3,0.3,0.0,-0.6,-0.5,-0.1], with mean -0.07 percent; adjustment components are June's 0.3 percent nominal hourly-pay momentum, likely near-matching CPI-U inflation, and composition/seasonal noise. For this change series, sigma = 0.31 percentage points (sample standard deviation of the fetched values); 1.28*sigma = 1.28*0.31 = 0.40 percentage points. Rounding the implied -0.07 percent center to the release's one-decimal convention gives -0.1 percent and bounds of -0.5 to 0.3 percent."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-real-avg-hourly-earnings-mom-july-2026\nrunLabel: Fast rollout 3 of 3\nresolutionDate: 2026-08-12\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T15-48-43Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-median3-2026-07-10t15-48-43z.fd142f589557248d","runId":"run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T15-48-43Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-median3-2026-07-10t15-48-43z.fd142f589557248d","predictionId":"us-real-avg-hourly-earnings-mom-july-2026","specId":"spec.us-real-avg-hourly-earnings-mom-july-2026","runLabel":"Median of 3 rollouts","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 6 historical point(s) and implicit outside-view language.","evidence":["Median-of-3 rollout ensemble","Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T15:39:47Z, 2026-07-10T15:43:51Z, 2026-07-10T15:47:55Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 8 source-context item(s), activity log present.","evidence":["Median CDF quantiles: q10 = -0.5, q50 = -0.1, q90 = 0.4. Constituent points [-0.1, 0.1, -0.1] with 80% widths [1.0, 1.0, 0.8]; the median interval inherits the central rollout mass rather than averaging tails."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.9, distribution present, forecast step count 1.","evidence":["Median CDF quantiles: q10 = -0.5, q50 = -0.1, q90 = 0.4. Constituent points [-0.1, 0.1, -0.1] with 80% widths [1.0, 1.0, 0.8]; the median interval inherits the central rollout mass rather than averaging tails.","Forecast: point -0.1, 80% interval [-0.5, 0.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T15:39:47Z, 2026-07-10T15:43:51Z, 2026-07-10T15:47:55Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T15:39:47Z, 2026-07-10T15:43:51Z, 2026-07-10T15:47:55Z. Drivers and resolver fields mirror the rollout closest to the median.","Tool result: {rollout_points: [-0.1, 0.1, -0.1], rollout_widths: [1.0, 1.0, 0.8], q10: -0.5, q50: -0.1, q90: 0.4}"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-real-avg-hourly-earnings-mom-july-2026\nrunLabel: Median of 3 rollouts\nresolutionDate: 2026-08-12\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T16-15-27Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-ladder-2026-07-10t16-15-27z.43786fe6c2ca1ed0","runId":"run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T16-15-27Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-ladder-2026-07-10t16-15-27z.43786fe6c2ca1ed0","predictionId":"us-real-avg-hourly-earnings-mom-july-2026","specId":"spec.us-real-avg-hourly-earnings-mom-july-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: for this change-rate series, the direct recent official reference class is the contiguous BLS Table A-1 over-the-month real average hourly earnings sample for Mar-May 2026: -0.6, -0.5, and -0.1 percent. That anchors the distribution near negative but improving, before adjusting for current nominal wage momentum and July inflation risk.","Prior/update/interval: persistence prior is the contiguous recent Table A-1 change-rate sample [-0.6, -0.5, -0.1], with mean -0.4. For a change/flow target I compute sigma from the values themselves: squared deviations from -0.4 are 0.04, 0.01, and 0.09; sample variance = 0.14/2 = 0.07, so sigma = 0.26 and the normal 80% half-width is roughly 1.28*sigma = 0.33. Current-release adjustment components are +0.2 from steady nominal AHE around 0.3 percent, +0.1 from expected partial energy/CPI moderation versus the March-May spike, and +0.1 because the three-month sample is unusually inflation-heavy and too small for full-cycle volatility, moving the center from -0.4 to about 0.0. The ladder-implied 80% half-width is 0.5, about 1.52x the 1.28*sigma width, widened for the small sample, CPI energy volatility, and one-decimal first-print rounding. No longer time-series model is used because the target is dominated by near-term CPI and nominal wage inputs."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Forecast for July 2026 BLS real average hourly earnings MoM","Framing and exact resolver: this forecast is for BLS Real Earnings Table A-1, all employees on private nonfarm payrolls, seasonally adjusted over-the-month percent change in real average hourly earnings, July 2026 first print, in percent and rounded to the one-decimal value printed by BLS. The target uses the same SA real earnings variant throughout."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this forecast is for BLS Real Earnings Table A-1, all employees on private nonfarm payrolls, seasonally adjusted over-the-month percent change in real average hourly earnings, July 2026 first print, in percent and rounded to the one-decimal value printed by BLS. The target uses the same SA real earnings variant throughout.","Tool call: Opened BLS Schedule of Releases for Real Earnings for 2026 release timing."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1, distribution present, forecast step count 1.","evidence":["Base rate/reference class: for this change-rate series, the direct recent official reference class is the contiguous BLS Table A-1 over-the-month real average hourly earnings sample for Mar-May 2026: -0.6, -0.5, and -0.1 percent. That anchors the distribution near negative but improving, before adjusting for current nominal wage momentum and July inflation risk.","Prior/update/interval: persistence prior is the contiguous recent Table A-1 change-rate sample [-0.6, -0.5, -0.1], with mean -0.4. For a change/flow target I compute sigma from the values themselves: squared deviations from -0.4 are 0.04, 0.01, and 0.09; sample variance = 0.14/2 = 0.07, so sigma = 0.26 and the normal 80% half-width is roughly 1.28*sigma = 0.33. Current-release adjustment components are +0.2 from steady nominal AHE around 0.3 percent, +0.1 from expected partial energy/CPI moderation versus the March-May spike, and +0.1 because the three-month sample is unusually inflation-heavy and too small for full-cycle volatility, moving the center from -0.4 to about 0.0. The ladder-implied 80% half-width is 0.5, about 1.52x the 1.28*sigma width, widened for the small sample, CPI energy volatility, and one-decimal first-print rounding. No longer time-series model is used because the target is dominated by near-term CPI and nominal wage inputs."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate/reference class: for this change-rate series, the direct recent official reference class is the contiguous BLS Table A-1 over-the-month real average hourly earnings sample for Mar-May 2026: -0.6, -0.5, and -0.1 percent. That anchors the distribution near negative but improving, before adjusting for current nominal wage momentum and July inflation risk.","Prior/update/interval: persistence prior is the contiguous recent Table A-1 change-rate sample [-0.6, -0.5, -0.1], with mean -0.4. For a change/flow target I compute sigma from the values themselves: squared deviations from -0.4 are 0.04, 0.01, and 0.09; sample variance = 0.14/2 = 0.07, so sigma = 0.26 and the normal 80% half-width is roughly 1.28*sigma = 0.33. Current-release adjustment components are +0.2 from steady nominal AHE around 0.3 percent, +0.1 from expected partial energy/CPI moderation versus the March-May spike, and +0.1 because the three-month sample is unusually inflation-heavy and too small for full-cycle volatility, moving the center from -0.4 to about 0.0. The ladder-implied 80% half-width is 0.5, about 1.52x the 1.28*sigma width, widened for the small sample, CPI energy volatility, and one-decimal first-print rounding. No longer time-series model is used because the target is dominated by near-term CPI and nominal wage inputs."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: for this change-rate series, the direct recent official reference class is the contiguous BLS Table A-1 over-the-month real average hourly earnings sample for Mar-May 2026: -0.6, -0.5, and -0.1 percent. That anchors the distribution near negative but improving, before adjusting for current nominal wage momentum and July inflation risk.","Counter-considerations: upside risk is a July CPI slowdown toward 0.0 to 0.1 percent with nominal AHE still near 0.3 percent, which could put real AHE near or above 0.4 percent. Downside risk is another gasoline or energy-services CPI jump alongside softer hourly earnings, which could push the print below -0.4 percent. A large energy reversal plus a strong wage mix effect would land above the interval; another CPI shock above roughly 0.8 percent with weak nominal earnings would land below the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for July 2026 BLS real average hourly earnings MoM","Framing and exact resolver: this forecast is for BLS Real Earnings Table A-1, all employees on private nonfarm payrolls, seasonally adjusted over-the-month percent change in real average hourly earnings, July 2026 first print, in percent and rounded to the one-decimal value printed by BLS. The target uses the same SA real earnings variant throughout."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-real-avg-hourly-earnings-mom-july-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-08-12\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T16-27-44Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-fast-2026-07-10t16-27-44z.6141e6531669d1b8","runId":"run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T16-27-44Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-fast-2026-07-10t16-27-44z.6141e6531669d1b8","predictionId":"us-real-avg-hourly-earnings-mom-july-2026","specId":"spec.us-real-avg-hourly-earnings-mom-july-2026","runLabel":"Fast rollout 1 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the immediate same-table reference class is the latest three published real hourly m/m changes, which average -0.4 percent. That base rate is depressed by unusually firm CPI-U prints of 0.9, 0.6, and 0.5 percent, while nominal hourly earnings remained roughly 0.2 to 0.3 percent per month.","Prior/update/interval: persistence prior uses the latest same-variant Table A-1 real average hourly earnings m/m values [-0.6, -0.5, -0.1], mean = (-0.6 - 0.5 - 0.1) / 3 = -0.4. I adjust +0.3 percentage point for July because nominal hourly earnings were still near +0.3 percent in June and CPI is unlikely to repeat the 0.5 to 0.9 percent monthly pace from Mar-May, giving point = -0.4 + 0.3 = -0.1. For realized dispersion on this change series, sample sigma = sqrt((( -0.6 + 0.4)^2 + (-0.5 + 0.4)^2 + (-0.1 + 0.4)^2) / 2) = sqrt(0.07) = 0.26; 1.28*sigma = 0.33, so point +/- 0.33 gives about [-0.43, 0.23], rounded outward to an 80 percent interval of [-0.5, 0.3]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this forecast is for the seasonally adjusted over-the-month percent change in real average hourly earnings for all employees on private nonfarm payrolls in BLS Real Earnings Table A-1, first print for July 2026, using the table's one-decimal percent value and no later revisions. The variant is the same throughout: all employees, private nonfarm payrolls, seasonally adjusted, deflated by CPI-U in Table A-1.","Tool call: Checked the BLS Schedule of Releases for Real Earnings for the July 2026 reference month."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this forecast is for the seasonally adjusted over-the-month percent change in real average hourly earnings for all employees on private nonfarm payrolls in BLS Real Earnings Table A-1, first print for July 2026, using the table's one-decimal percent value and no later revisions. The variant is the same throughout: all employees, private nonfarm payrolls, seasonally adjusted, deflated by CPI-U in Table A-1.","Tool call: Checked the BLS Schedule of Releases for Real Earnings for the July 2026 reference month."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.8, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior uses the latest same-variant Table A-1 real average hourly earnings m/m values [-0.6, -0.5, -0.1], mean = (-0.6 - 0.5 - 0.1) / 3 = -0.4. I adjust +0.3 percentage point for July because nominal hourly earnings were still near +0.3 percent in June and CPI is unlikely to repeat the 0.5 to 0.9 percent monthly pace from Mar-May, giving point = -0.4 + 0.3 = -0.1. For realized dispersion on this change series, sample sigma = sqrt((( -0.6 + 0.4)^2 + (-0.5 + 0.4)^2 + (-0.1 + 0.4)^2) / 2) = sqrt(0.07) = 0.26; 1.28*sigma = 0.33, so point +/- 0.33 gives about [-0.43, 0.23], rounded outward to an 80 percent interval of [-0.5, 0.3].","Counter-considerations: upside risk is a soft July CPI print below roughly 0.1 percent paired with another 0.3 percent nominal wage month, which would land above the interval. Downside risk is a renewed energy or shelter-driven CPI jump near 0.6 percent with only 0.2 percent wage growth, which would land below the interval. Outside the interval would most likely require either a large July CPI surprise or a meaningful payroll-composition shock to average hourly earnings."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior uses the latest same-variant Table A-1 real average hourly earnings m/m values [-0.6, -0.5, -0.1], mean = (-0.6 - 0.5 - 0.1) / 3 = -0.4. I adjust +0.3 percentage point for July because nominal hourly earnings were still near +0.3 percent in June and CPI is unlikely to repeat the 0.5 to 0.9 percent monthly pace from Mar-May, giving point = -0.4 + 0.3 = -0.1. For realized dispersion on this change series, sample sigma = sqrt((( -0.6 + 0.4)^2 + (-0.5 + 0.4)^2 + (-0.1 + 0.4)^2) / 2) = sqrt(0.07) = 0.26; 1.28*sigma = 0.33, so point +/- 0.33 gives about [-0.43, 0.23], rounded outward to an 80 percent interval of [-0.5, 0.3]."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-considerations: upside risk is a soft July CPI print below roughly 0.1 percent paired with another 0.3 percent nominal wage month, which would land above the interval. Downside risk is a renewed energy or shelter-driven CPI jump near 0.6 percent with only 0.2 percent wage growth, which would land below the interval. Outside the interval would most likely require either a large July CPI surprise or a meaningful payroll-composition shock to average hourly earnings."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["US July 2026 real average hourly earnings m/m forecast","Framing and exact resolver: this forecast is for the seasonally adjusted over-the-month percent change in real average hourly earnings for all employees on private nonfarm payrolls in BLS Real Earnings Table A-1, first print for July 2026, using the table's one-decimal percent value and no later revisions. The variant is the same throughout: all employees, private nonfarm payrolls, seasonally adjusted, deflated by CPI-U in Table A-1."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-real-avg-hourly-earnings-mom-july-2026\nrunLabel: Fast rollout 1 of 3\nresolutionDate: 2026-08-12\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T16-39-16Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-fast-2026-07-10t16-39-16z.cd261b8e06ee3325","runId":"run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T16-39-16Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-fast-2026-07-10t16-39-16z.cd261b8e06ee3325","predictionId":"us-real-avg-hourly-earnings-mom-july-2026","specId":"spec.us-real-avg-hourly-earnings-mom-july-2026","runLabel":"Fast rollout 2 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Framing and exact resolver: this forecast is for BLS Real Earnings Table A-1, seasonally adjusted over-the-month percent change in real average hourly earnings for all employees on private nonfarm payrolls, first printed for July 2026. The variant is Table A-1 real average hourly earnings, all employees, private nonfarm, seasonally adjusted; all historical anchors below use that same variant.","Base rate/reference class: the official Table A-1 recent same-variant real AHE MoM prints available in the current table are 0.4, -0.6, -0.5, and -0.1 percent, averaging -0.2 percent, with only 1 of 4 positive. That base rate says the target is noisy but tilted slightly negative when CPI is running above normal."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["July 2026 BLS real average hourly earnings MoM forecast","Framing and exact resolver: this forecast is for BLS Real Earnings Table A-1, seasonally adjusted over-the-month percent change in real average hourly earnings for all employees on private nonfarm payrolls, first printed for July 2026. The variant is Table A-1 real average hourly earnings, all employees, private nonfarm, seasonally adjusted; all historical anchors below use that same variant."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this forecast is for BLS Real Earnings Table A-1, seasonally adjusted over-the-month percent change in real average hourly earnings for all employees on private nonfarm payrolls, first printed for July 2026. The variant is Table A-1 real average hourly earnings, all employees, private nonfarm, seasonally adjusted; all historical anchors below use that same variant.","Tool call: Checked BLS August 2026 release calendar for the target release date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.2, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is the same-variant Table A-1 recent-print mean of -0.2 percent from May 2025 and Mar-May 2026; update components are +0.1 for June nominal wage momentum staying near 0.3 percent, 0.0 for July labor-market softness not implying a wage break, and 0.0 for CPI likely still near nominal wage growth, giving point -0.1 percent. Interval method uses realized dispersion of the fetched change values [0.4, -0.6, -0.5, -0.1]: sample sigma = 0.46, half-width = 1.28*sigma = 1.28*0.46 = 0.59, rounded to the BLS one-decimal reporting grid around -0.1 gives an 80% interval of -0.7 to 0.5 percent.","Counter-considerations: upside risk is a benign July CPI print near 0.0 to 0.1 percent with nominal AHE still around 0.3 percent, which would land above the interval if real earnings printed at 0.6 percent or higher. Downside risk is another energy-driven CPI jump or a weak nominal AHE print, which would land below the interval if real earnings printed at -0.8 percent or lower. Outside the interval would most likely require a sharp one-month CPI or wage surprise rather than ordinary persistence."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Read BLS May 2026 CPI release for inflation momentum entering the forecast window.","Prior/update/interval: persistence prior is the same-variant Table A-1 recent-print mean of -0.2 percent from May 2025 and Mar-May 2026; update components are +0.1 for June nominal wage momentum staying near 0.3 percent, 0.0 for July labor-market softness not implying a wage break, and 0.0 for CPI likely still near nominal wage growth, giving point -0.1 percent. Interval method uses realized dispersion of the fetched change values [0.4, -0.6, -0.5, -0.1]: sample sigma = 0.46, half-width = 1.28*sigma = 1.28*0.46 = 0.59, rounded to the BLS one-decimal reporting grid around -0.1 gives an 80% interval of -0.7 to 0.5 percent."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: the official Table A-1 recent same-variant real AHE MoM prints available in the current table are 0.4, -0.6, -0.5, and -0.1 percent, averaging -0.2 percent, with only 1 of 4 positive. That base rate says the target is noisy but tilted slightly negative when CPI is running above normal.","Counter-considerations: upside risk is a benign July CPI print near 0.0 to 0.1 percent with nominal AHE still around 0.3 percent, which would land above the interval if real earnings printed at 0.6 percent or higher. Downside risk is another energy-driven CPI jump or a weak nominal AHE print, which would land below the interval if real earnings printed at -0.8 percent or lower. Outside the interval would most likely require a sharp one-month CPI or wage surprise rather than ordinary persistence."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["July 2026 BLS real average hourly earnings MoM forecast","Framing and exact resolver: this forecast is for BLS Real Earnings Table A-1, seasonally adjusted over-the-month percent change in real average hourly earnings for all employees on private nonfarm payrolls, first printed for July 2026. The variant is Table A-1 real average hourly earnings, all employees, private nonfarm, seasonally adjusted; all historical anchors below use that same variant."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-real-avg-hourly-earnings-mom-july-2026\nrunLabel: Fast rollout 2 of 3\nresolutionDate: 2026-08-12\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T16-50-39Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-fast-2026-07-10t16-50-39z.cd261b8e06ee3325","runId":"run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T16-50-39Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-fast-2026-07-10t16-50-39z.cd261b8e06ee3325","predictionId":"us-real-avg-hourly-earnings-mom-july-2026","specId":"spec.us-real-avg-hourly-earnings-mom-july-2026","runLabel":"Fast rollout 3 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: the recent official Table A-1 reference class has four fetched real AHE m/m prints, 0.4, -0.6, -0.5, and -0.1, with a mean base rate of -0.20 percent; the latest three prints average -0.40 percent, reflecting CPI running above nominal wage gains.","Prior/update/interval: persistence prior is the recent official Table A-1 mean from May 2025, Mar. 2026, Apr. 2026, and May 2026 real AHE m/m values: (0.4 - 0.6 - 0.5 - 0.1)/4 = -0.20. Adjustment components: +0.10 because nominal AHE momentum improved to about (37.64/37.51 - 1)*100 = 0.35 in June while July CPI is not assumed to repeat the March-May 0.5 to 0.9 pace; point = -0.10. Interval method: sample sigma from the four fetched real-change values is sigma = 0.45, so the 80 percent half-width is roughly 1.28*sigma = 0.58, rounded to 0.6; final implied bounds are -0.1 - 0.6 = -0.7 and -0.1 + 0.6 = 0.5."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this forecast is for BLS Real Earnings Table A-1, seasonally adjusted real average hourly earnings for all employees on private nonfarm payrolls, over-the-month percent change for July 2026, first print only, rounded to the one-decimal percent value printed by BLS.","Tool call: Checked BLS Real Earnings release calendar for July 2026 reference month."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this forecast is for BLS Real Earnings Table A-1, seasonally adjusted real average hourly earnings for all employees on private nonfarm payrolls, over-the-month percent change for July 2026, first print only, rounded to the one-decimal percent value printed by BLS.","Tool call: Checked BLS Real Earnings release calendar for July 2026 reference month."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.2, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is the recent official Table A-1 mean from May 2025, Mar. 2026, Apr. 2026, and May 2026 real AHE m/m values: (0.4 - 0.6 - 0.5 - 0.1)/4 = -0.20. Adjustment components: +0.10 because nominal AHE momentum improved to about (37.64/37.51 - 1)*100 = 0.35 in June while July CPI is not assumed to repeat the March-May 0.5 to 0.9 pace; point = -0.10. Interval method: sample sigma from the four fetched real-change values is sigma = 0.45, so the 80 percent half-width is roughly 1.28*sigma = 0.58, rounded to 0.6; final implied bounds are -0.1 - 0.6 = -0.7 and -0.1 + 0.6 = 0.5.","Counter-consideration: upside risk is a soft July CPI print with another 0.3 to 0.4 nominal wage gain, which would land above the interval; downside risk is another CPI print near 0.7 or a weak July AHE print, which would land below the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Fetched BLS nominal average hourly earnings all employees total private, seasonally adjusted, as a component mirror for wage momentum.","Prior/update/interval: persistence prior is the recent official Table A-1 mean from May 2025, Mar. 2026, Apr. 2026, and May 2026 real AHE m/m values: (0.4 - 0.6 - 0.5 - 0.1)/4 = -0.20. Adjustment components: +0.10 because nominal AHE momentum improved to about (37.64/37.51 - 1)*100 = 0.35 in June while July CPI is not assumed to repeat the March-May 0.5 to 0.9 pace; point = -0.10. Interval method: sample sigma from the four fetched real-change values is sigma = 0.45, so the 80 percent half-width is roughly 1.28*sigma = 0.58, rounded to 0.6; final implied bounds are -0.1 - 0.6 = -0.7 and -0.1 + 0.6 = 0.5."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-consideration: upside risk is a soft July CPI print with another 0.3 to 0.4 nominal wage gain, which would land above the interval; downside risk is another CPI print near 0.7 or a weak July AHE print, which would land below the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for July 2026 real average hourly earnings m/m","Framing and exact resolver: this forecast is for BLS Real Earnings Table A-1, seasonally adjusted real average hourly earnings for all employees on private nonfarm payrolls, over-the-month percent change for July 2026, first print only, rounded to the one-decimal percent value printed by BLS."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-real-avg-hourly-earnings-mom-july-2026\nrunLabel: Fast rollout 3 of 3\nresolutionDate: 2026-08-12\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T16-53-09Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-median3-2026-07-10t16-53-09z.545798c330bc0006","runId":"run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T16-53-09Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-median3-2026-07-10t16-53-09z.545798c330bc0006","predictionId":"us-real-avg-hourly-earnings-mom-july-2026","specId":"spec.us-real-avg-hourly-earnings-mom-july-2026","runLabel":"Median of 3 rollouts","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 6 historical point(s) and implicit outside-view language.","evidence":["Median-of-3 rollout ensemble","Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T16:27:44Z, 2026-07-10T16:39:16Z, 2026-07-10T16:50:39Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 8 source-context item(s), activity log present.","evidence":["Median CDF quantiles: q10 = -0.7, q50 = -0.1, q90 = 0.5. Constituent points [-0.1, -0.1, -0.1] with 80% widths [0.8, 1.2, 1.2]; the median interval inherits the central rollout mass rather than averaging tails."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.2, distribution present, forecast step count 1.","evidence":["Median CDF quantiles: q10 = -0.7, q50 = -0.1, q90 = 0.5. Constituent points [-0.1, -0.1, -0.1] with 80% widths [0.8, 1.2, 1.2]; the median interval inherits the central rollout mass rather than averaging tails.","Forecast: point -0.1, 80% interval [-0.7, 0.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T16:27:44Z, 2026-07-10T16:39:16Z, 2026-07-10T16:50:39Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T16:27:44Z, 2026-07-10T16:39:16Z, 2026-07-10T16:50:39Z. Drivers and resolver fields mirror the rollout closest to the median.","Tool result: {rollout_points: [-0.1, -0.1, -0.1], rollout_widths: [0.8, 1.2, 1.2], q10: -0.7, q50: -0.1, q90: 0.5}"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-real-avg-hourly-earnings-mom-july-2026\nrunLabel: Median of 3 rollouts\nresolutionDate: 2026-08-12\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T17-14-32Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-ladder-2026-07-10t17-14-32z.23025d82acf7af39","runId":"run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T17-14-32Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-ladder-2026-07-10t17-14-32z.23025d82acf7af39","predictionId":"us-real-avg-hourly-earnings-mom-july-2026","specId":"spec.us-real-avg-hourly-earnings-mom-july-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["The outside-view base rate/reference class is the five documented first-print observations from January through May 2026: 0.3%, 0.2%, -0.6%, -0.5%, and -0.1%. Their mean is -0.14% and median is -0.1%. A formal time-series model is unsuitable because only five noisy first-print observations are documented and the target is a monthly change rather than a persistent level.","Mechanisms: typical nominal wage behavior is already embedded in the reference class, so it receives no separate adjustment. June nominal hourly earnings growth of 0.3% supports persistence but does not justify double-counting. The only directional adjustment is +0.1 percentage point from the prior median, reflecting partial normalization from the unusually high 0.5%-0.9% CPI-U readings associated with recent negative prints; absent direct July CPI evidence, the adjustment is deliberately small."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 7 source-context item(s), activity log present.","evidence":["The target is the first-print, one-decimal value in BLS Real Earnings Table A-1 for all employees on private nonfarm payrolls: seasonally adjusted real average hourly earnings over the month. Table A-1 uses CPI-U to deflate nominal earnings; subtracting CPI-U inflation from nominal wage growth is a close approximation rather than the exact index calculation. No later revision replaces the first print.","Tool call: Read the BLS August 2026 release calendar."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the first-print, one-decimal value in BLS Real Earnings Table A-1 for all employees on private nonfarm payrolls: seasonally adjusted real average hourly earnings over the month. Table A-1 uses CPI-U to deflate nominal earnings; subtracting CPI-U inflation from nominal wage growth is a close approximation rather than the exact index calculation. No later revision replaces the first print.","Tool call: Read the BLS August 2026 release calendar."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1, distribution present, forecast step count 1.","evidence":["Prior/update/interval: Start from the five-print reference-class median of -0.1%. Using the change-series values themselves [0.3, 0.2, -0.6, -0.5, -0.1], the sample standard deviation is sigma = 0.40 percentage point, so 1.28*sigma = 0.52 point. Adjustment components are +0.10 point for partial CPI normalization and +0.00 for nominal-wage persistence already embedded in the prior, yielding a 0.0% center. The ladder-implied 80% interval is -0.5% to 0.5%, a 0.50-point half-width, close to the 0.52-point empirical width.","Upside risk comes from July CPI-U near zero while nominal hourly pay rises at least 0.4%; that could land above the interval. Downside risk comes from another energy- or tariff-related CPI jump near 0.8% with weak wage growth; that would land below the interval. Composition-driven hourly-pay volatility is an additional outside-the-interval mechanism."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The outside-view base rate/reference class is the five documented first-print observations from January through May 2026: 0.3%, 0.2%, -0.6%, -0.5%, and -0.1%. Their mean is -0.14% and median is -0.1%. A formal time-series model is unsuitable because only five noisy first-print observations are documented and the target is a monthly change rather than a persistent level.","Review disposition: Accepted all four warnings by removing the undocumented December observation, using the five cited prints, explaining why a formal time-series model is unsuitable, avoiding double-counted wage momentum, itemizing the CPI and wage adjustments, and shrinking the center to 0.0%. Also accepted the clarification that nominal growth minus CPI-U is approximate."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Mechanisms: typical nominal wage behavior is already embedded in the reference class, so it receives no separate adjustment. June nominal hourly earnings growth of 0.3% supports persistence but does not justify double-counting. The only directional adjustment is +0.1 percentage point from the prior median, reflecting partial normalization from the unusually high 0.5%-0.9% CPI-U readings associated with recent negative prints; absent direct July CPI evidence, the adjustment is deliberately small.","Upside risk comes from July CPI-U near zero while nominal hourly pay rises at least 0.4%; that could land above the interval. Downside risk comes from another energy- or tariff-related CPI jump near 0.8% with weak wage growth; that would land below the interval. Composition-driven hourly-pay volatility is an additional outside-the-interval mechanism."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["July 2026 real average hourly earnings forecast","Mechanisms: typical nominal wage behavior is already embedded in the reference class, so it receives no separate adjustment. June nominal hourly earnings growth of 0.3% supports persistence but does not justify double-counting. The only directional adjustment is +0.1 percentage point from the prior median, reflecting partial normalization from the unusually high 0.5%-0.9% CPI-U readings associated with recent negative prints; absent direct July CPI evidence, the adjustment is deliberately small."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-real-avg-hourly-earnings-mom-july-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-08-12\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T17-21-35Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-fast-2026-07-10t17-21-35z.df3098f1469c8c6b","runId":"run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T17-21-35Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-fast-2026-07-10t17-21-35z.df3098f1469c8c6b","predictionId":"us-real-avg-hourly-earnings-mom-july-2026","specId":"spec.us-real-avg-hourly-earnings-mom-july-2026","runLabel":"Fast rollout 1 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["The reference class and base rate are the five available 2026 first-print changes: 0.3%, 0.2%, -0.6%, -0.5%, and -0.1%, with a mean of -0.14%. This series is a monthly change, so dispersion is measured from the values themselves.","Prior/update/interval: A mean/persistence prior from the five first-print 2026 observations is -0.14%. The historical sample is [0.3, 0.2, -0.6, -0.5, -0.1]. I adjust about +0.14 percentage point toward 0.0% because a roughly 0.3% nominal-pay gain and roughly 0.3% CPI-U gain would offset. Sample sigma = sqrt(0.652/4) = 0.40 percentage point; 1.28*sigma = 0.52, which rounds to a one-decimal-compatible half-width of 0.5. Final implied bounds are -0.5% to 0.5%."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["The target is BLS Real Earnings Table A-1: the seasonally adjusted over-the-month change in real average hourly earnings for all employees on private nonfarm payrolls. CPI-U is the deflator. Resolution uses the one-decimal July 2026 first print without later revisions.","Tool call: Fetch BLS Real Earnings Table A-1 releases for January and February 2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is BLS Real Earnings Table A-1: the seasonally adjusted over-the-month change in real average hourly earnings for all employees on private nonfarm payrolls. CPI-U is the deflator. Resolution uses the one-decimal July 2026 first print without later revisions.","Tool call: Fetch BLS Real Earnings Table A-1 releases for January and February 2026."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1, distribution present, forecast step count 1.","evidence":["Prior/update/interval: A mean/persistence prior from the five first-print 2026 observations is -0.14%. The historical sample is [0.3, 0.2, -0.6, -0.5, -0.1]. I adjust about +0.14 percentage point toward 0.0% because a roughly 0.3% nominal-pay gain and roughly 0.3% CPI-U gain would offset. Sample sigma = sqrt(0.652/4) = 0.40 percentage point; 1.28*sigma = 0.52, which rounds to a one-decimal-compatible half-width of 0.5. Final implied bounds are -0.5% to 0.5%.","Mechanism point estimate: forecast nominal average hourly earnings growth 0.3% minus forecast CPI-U inflation 0.3% = 0.0%. The 80% interval is 0.0% ± 1.28×0.40% = 0.0% ± 0.52%, reported as [-0.5%, 0.5%] in the target's one-decimal units."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and policy mechanisms: nominal wage growth remains positive but slowed to 0.2% in June; recent real-earnings momentum is weak; unusually strong spring CPI prints produced much of that weakness; continuing price pressure can still offset ordinary wage growth in July.","Prior/update/interval: A mean/persistence prior from the five first-print 2026 observations is -0.14%. The historical sample is [0.3, 0.2, -0.6, -0.5, -0.1]. I adjust about +0.14 percentage point toward 0.0% because a roughly 0.3% nominal-pay gain and roughly 0.3% CPI-U gain would offset. Sample sigma = sqrt(0.652/4) = 0.40 percentage point; 1.28*sigma = 0.52, which rounds to a one-decimal-compatible half-width of 0.5. Final implied bounds are -0.5% to 0.5%."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, one-off, and policy mechanisms: nominal wage growth remains positive but slowed to 0.2% in June; recent real-earnings momentum is weak; unusually strong spring CPI prints produced much of that weakness; continuing price pressure can still offset ordinary wage growth in July.","Prior/update/interval: A mean/persistence prior from the five first-print 2026 observations is -0.14%. The historical sample is [0.3, 0.2, -0.6, -0.5, -0.1]. I adjust about +0.14 percentage point toward 0.0% because a roughly 0.3% nominal-pay gain and roughly 0.3% CPI-U gain would offset. Sample sigma = sqrt(0.652/4) = 0.40 percentage point; 1.28*sigma = 0.52, which rounds to a one-decimal-compatible half-width of 0.5. Final implied bounds are -0.5% to 0.5%."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["July 2026 US real average hourly earnings forecast","Prior/update/interval: A mean/persistence prior from the five first-print 2026 observations is -0.14%. The historical sample is [0.3, 0.2, -0.6, -0.5, -0.1]. I adjust about +0.14 percentage point toward 0.0% because a roughly 0.3% nominal-pay gain and roughly 0.3% CPI-U gain would offset. Sample sigma = sqrt(0.652/4) = 0.40 percentage point; 1.28*sigma = 0.52, which rounds to a one-decimal-compatible half-width of 0.5. Final implied bounds are -0.5% to 0.5%."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-real-avg-hourly-earnings-mom-july-2026\nrunLabel: Fast rollout 1 of 3\nresolutionDate: 2026-08-12\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T17-27-05Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-fast-2026-07-10t17-27-05z.12bda99e7f998810","runId":"run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T17-27-05Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-fast-2026-07-10t17-27-05z.12bda99e7f998810","predictionId":"us-real-avg-hourly-earnings-mom-july-2026","specId":"spec.us-real-avg-hourly-earnings-mom-july-2026","runLabel":"Fast rollout 2 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Tool call: Fetch the prior-year July BLS archived release for the same Table A-1 variant.","The official BLS August 2026 release calendar verifies Real Earnings for July 2026 at 8:30 a.m. ET on August 12, 2026. The recent reference class/base rate is centered close to zero, with unusually negative March and April readings reflecting CPI-U increases of 0.9% and 0.6% against nominal wage gains of 0.2%."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["The target is the first-print, seasonally adjusted monthly percent change for all private-nonfarm employees in BLS Real Earnings Table A-1. It is nominal average hourly earnings deflated by CPI-U; the first one-decimal July 2026 print is final for this forecast even if BLS later revises it.","Tool call: Fetch the current BLS Real Earnings Table A-1 reference class and component changes."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the first-print, seasonally adjusted monthly percent change for all private-nonfarm employees in BLS Real Earnings Table A-1. It is nominal average hourly earnings deflated by CPI-U; the first one-decimal July 2026 print is final for this forecast even if BLS later revises it.","Tool result: BLS Table A-1 reports first-print real average hourly earnings changes of -0.1% for May 2026 and -0.5% for April 2026; May nominal hourly earnings rose 0.3% while CPI-U rose 0.5%."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.8, distribution present, forecast step count 1.","evidence":["Prior/update/interval: A persistence/reference-class prior uses the ten available same-variant first-print observations June–September and December 2025 plus January–May 2026: -0.1, 0.1, -0.1, 0.0, 0.0, 0.3, 0.2, -0.6, -0.5, -0.1. Their mean is -0.08%; the nominal-pay adjustment is mildly positive, recent CPI momentum is negative, and no separate one-off adjustment is imposed, yielding 0.0%. For this change series, dispersion is measured from the values themselves: sample sigma = 0.28 percentage point, so 1.28*sigma = 0.36 point; rounding outward to the BLS one-decimal grid gives bounds of -0.4% and 0.4%.","Upside risk: softer energy or goods inflation alongside a 0.4% wage print would land above the interval. Downside risk: another CPI-U surge near 0.8–0.9% with only 0.2% nominal wage growth would land below the interval. Either outcome would be outside the interval and falsify the central mechanism assumptions."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and mechanism: the real earnings level does not mechanically force mean reversion; recent momentum is negative; monthly energy and other CPI shocks can create one-off moves; mechanically, a roughly 0.3% nominal-pay gain minus roughly 0.3% CPI-U inflation implies about 0.0% real growth.","Prior/update/interval: A persistence/reference-class prior uses the ten available same-variant first-print observations June–September and December 2025 plus January–May 2026: -0.1, 0.1, -0.1, 0.0, 0.0, 0.3, 0.2, -0.6, -0.5, -0.1. Their mean is -0.08%; the nominal-pay adjustment is mildly positive, recent CPI momentum is negative, and no separate one-off adjustment is imposed, yielding 0.0%. For this change series, dispersion is measured from the values themselves: sample sigma = 0.28 percentage point, so 1.28*sigma = 0.36 point; rounding outward to the BLS one-decimal grid gives bounds of -0.4% and 0.4%."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Upside risk: softer energy or goods inflation alongside a 0.4% wage print would land above the interval. Downside risk: another CPI-U surge near 0.8–0.9% with only 0.2% nominal wage growth would land below the interval. Either outcome would be outside the interval and falsify the central mechanism assumptions."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["July 2026 real average hourly earnings forecast","The target is the first-print, seasonally adjusted monthly percent change for all private-nonfarm employees in BLS Real Earnings Table A-1. It is nominal average hourly earnings deflated by CPI-U; the first one-decimal July 2026 print is final for this forecast even if BLS later revises it."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-real-avg-hourly-earnings-mom-july-2026\nrunLabel: Fast rollout 2 of 3\nresolutionDate: 2026-08-12\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T17-32-35Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-fast-2026-07-10t17-32-35z.df3098f1469c8c6b","runId":"run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T17-32-35Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-fast-2026-07-10t17-32-35z.df3098f1469c8c6b","predictionId":"us-real-avg-hourly-earnings-mom-july-2026","specId":"spec.us-real-avg-hourly-earnings-mom-july-2026","runLabel":"Fast rollout 3 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["The recent first-print reference class is December 2025 through May 2026: -0.3, 0.3, 0.2, -0.6, -0.5, and -0.1 percent. Its base rate mean is -0.17 percent, reflecting several recent months when CPI-U increases exceeded nominal wage gains.","Prior/update/interval: The persistence/reference-class prior is the -0.17 percent mean of the six first-print changes [-0.3, 0.3, 0.2, -0.6, -0.5, -0.1]. For this change series, dispersion is computed from the values themselves: sample sigma = 0.37 percentage point. The normal 80% half-width is 1.28*sigma = 1.28*0.37 = 0.47 point. Updating the prior by about +0.17 point for an expected normalization of CPI-U relative to March–May, while retaining ordinary nominal-pay momentum, gives a 0.0 point estimate; rounding the bounds to the BLS one-decimal grid gives -0.5 to 0.5 percent."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["The target is the first-print, seasonally adjusted month-over-month percentage change for all employees on private nonfarm payrolls in BLS Real Earnings Table A-1. The all-employees series uses CPI-U as its deflator; production and nonsupervisory earnings and CPI-W are different variants and are excluded.","Tool call: Fetch BLS archived January and February 2026 Real Earnings Table A-1 releases."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the first-print, seasonally adjusted month-over-month percentage change for all employees on private nonfarm payrolls in BLS Real Earnings Table A-1. The all-employees series uses CPI-U as its deflator; production and nonsupervisory earnings and CPI-W are different variants and are excluded.","Tool call: Fetch BLS archived January and February 2026 Real Earnings Table A-1 releases."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1, distribution present, forecast step count 1.","evidence":["Mechanisms: the level of real hourly earnings was $11.24 in May; nominal wage momentum has recently been about 0.2–0.4 percent monthly; CPI-U is the principal offset; and volatile monthly inflation is the dominant one-off risk. For July, a roughly 0.3 percent nominal-pay gain and roughly 0.3 percent CPI-U increase imply approximately no real change.","Prior/update/interval: The persistence/reference-class prior is the -0.17 percent mean of the six first-print changes [-0.3, 0.3, 0.2, -0.6, -0.5, -0.1]. For this change series, dispersion is computed from the values themselves: sample sigma = 0.37 percentage point. The normal 80% half-width is 1.28*sigma = 1.28*0.37 = 0.47 point. Updating the prior by about +0.17 point for an expected normalization of CPI-U relative to March–May, while retaining ordinary nominal-pay momentum, gives a 0.0 point estimate; rounding the bounds to the BLS one-decimal grid gives -0.5 to 0.5 percent."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Mechanisms: the level of real hourly earnings was $11.24 in May; nominal wage momentum has recently been about 0.2–0.4 percent monthly; CPI-U is the principal offset; and volatile monthly inflation is the dominant one-off risk. For July, a roughly 0.3 percent nominal-pay gain and roughly 0.3 percent CPI-U increase imply approximately no real change.","Prior/update/interval: The persistence/reference-class prior is the -0.17 percent mean of the six first-print changes [-0.3, 0.3, 0.2, -0.6, -0.5, -0.1]. For this change series, dispersion is computed from the values themselves: sample sigma = 0.37 percentage point. The normal 80% half-width is 1.28*sigma = 1.28*0.37 = 0.47 point. Updating the prior by about +0.17 point for an expected normalization of CPI-U relative to March–May, while retaining ordinary nominal-pay momentum, gives a 0.0 point estimate; rounding the bounds to the BLS one-decimal grid gives -0.5 to 0.5 percent."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Mechanisms: the level of real hourly earnings was $11.24 in May; nominal wage momentum has recently been about 0.2–0.4 percent monthly; CPI-U is the principal offset; and volatile monthly inflation is the dominant one-off risk. For July, a roughly 0.3 percent nominal-pay gain and roughly 0.3 percent CPI-U increase imply approximately no real change.","Counter-considerations: upside risk would come from a soft or falling July CPI-U print alongside firm nominal wages and could put real earnings above 0.5 percent. Downside risk would come from another inflation surge or weak payroll earnings and could put the result below -0.5 percent. Either outcome would land outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["July 2026 US real average hourly earnings forecast","Prior/update/interval: The persistence/reference-class prior is the -0.17 percent mean of the six first-print changes [-0.3, 0.3, 0.2, -0.6, -0.5, -0.1]. For this change series, dispersion is computed from the values themselves: sample sigma = 0.37 percentage point. The normal 80% half-width is 1.28*sigma = 1.28*0.37 = 0.47 point. Updating the prior by about +0.17 point for an expected normalization of CPI-U relative to March–May, while retaining ordinary nominal-pay momentum, gives a 0.0 point estimate; rounding the bounds to the BLS one-decimal grid gives -0.5 to 0.5 percent."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-real-avg-hourly-earnings-mom-july-2026\nrunLabel: Fast rollout 3 of 3\nresolutionDate: 2026-08-12\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T17-33-54Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-median3-2026-07-10t17-33-54z.89583cdec120f4b6","runId":"run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T17-33-54Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-median3-2026-07-10t17-33-54z.89583cdec120f4b6","predictionId":"us-real-avg-hourly-earnings-mom-july-2026","specId":"spec.us-real-avg-hourly-earnings-mom-july-2026","runLabel":"Median of 3 rollouts","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 6 historical point(s) and implicit outside-view language.","evidence":["Median-of-3 rollout ensemble","Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T17:21:35Z, 2026-07-10T17:27:05Z, 2026-07-10T17:32:35Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 8 source-context item(s), activity log present.","evidence":["Median CDF quantiles: q10 = -0.5, q50 = 0.0, q90 = 0.5. Constituent points [0.0, 0.0, 0.0] with 80% widths [1.0, 0.8, 1.0]; the median interval inherits the central rollout mass rather than averaging tails."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1, distribution present, forecast step count 1.","evidence":["Median CDF quantiles: q10 = -0.5, q50 = 0.0, q90 = 0.5. Constituent points [0.0, 0.0, 0.0] with 80% widths [1.0, 0.8, 1.0]; the median interval inherits the central rollout mass rather than averaging tails.","Forecast: point 0, 80% interval [-0.5, 0.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T17:21:35Z, 2026-07-10T17:27:05Z, 2026-07-10T17:32:35Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T17:21:35Z, 2026-07-10T17:27:05Z, 2026-07-10T17:32:35Z. Drivers and resolver fields mirror the rollout closest to the median.","Tool result: {rollout_points: [0.0, 0.0, 0.0], rollout_widths: [1.0, 0.8, 1.0], q10: -0.5, q50: 0.0, q90: 0.5}"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-real-avg-hourly-earnings-mom-july-2026\nrunLabel: Median of 3 rollouts\nresolutionDate: 2026-08-12\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T21-25-25Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-ladder-v2-2026-07-10t21-25-25z.260a352af5e59efb","runId":"run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T21-25-25Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-ladder-v2-2026-07-10t21-25-25z.260a352af5e59efb","predictionId":"us-real-avg-hourly-earnings-mom-july-2026","specId":"spec.us-real-avg-hourly-earnings-mom-july-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: recent Table A-1 real hourly MoM prints centered below zero, with Mar.-May 2026 at -0.6, -0.5, and -0.1 after CPI-U rose 0.9, 0.6, and 0.5. A simple AR or persistence model and a short historical mean both point negative; I use persistence rather than a fitted model because this target is a one-month first-print combination of wages and CPI, and the available same-variant recent sample is short.","Prior/update/interval: starting from a persistence prior near the recent Table A-1 average of about -0.4 for Mar.-May 2026, I add about +0.2 because June nominal AHE momentum was still roughly 0.3 percent, add about +0.1 because May core CPI was only 0.2 despite headline energy pressure, and subtract a small residual risk adjustment for headline CPI and energy volatility visible in the Mar.-May CPI prints. June AHE and May CPI are momentum indicators, not direct July target inputs. The threshold span is a subjective 10th-90th elicitation anchored by fetched same-variant real AHE outcomes of -0.6, -0.5, -0.1, and +0.4 rather than a stable volatility estimate, so [-0.5, 0.3] covers a repeat negative month through a modest rebound while leaving larger CPI or wage surprises in the tails."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Forecast for July 2026 BLS real average hourly earnings MoM","Framing and exact resolver: this forecast is for BLS Real Earnings Table A-1, all employees on private nonfarm payrolls, seasonally adjusted, real average hourly earnings over-the-month percent change for July 2026. The target resolves to the one-decimal first print on the BLS official release page, with no later revision used."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this forecast is for BLS Real Earnings Table A-1, all employees on private nonfarm payrolls, seasonally adjusted, real average hourly earnings over-the-month percent change for July 2026. The target resolves to the one-decimal first print on the BLS official release page, with no later revision used.","Tool call: Checked BLS Real Earnings release schedule for the reference month and release date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.8, distribution present, forecast step count 1.","evidence":["Prior/update/interval: starting from a persistence prior near the recent Table A-1 average of about -0.4 for Mar.-May 2026, I add about +0.2 because June nominal AHE momentum was still roughly 0.3 percent, add about +0.1 because May core CPI was only 0.2 despite headline energy pressure, and subtract a small residual risk adjustment for headline CPI and energy volatility visible in the Mar.-May CPI prints. June AHE and May CPI are momentum indicators, not direct July target inputs. The threshold span is a subjective 10th-90th elicitation anchored by fetched same-variant real AHE outcomes of -0.6, -0.5, -0.1, and +0.4 rather than a stable volatility estimate, so [-0.5, 0.3] covers a repeat negative month through a modest rebound while leaving larger CPI or wage surprises in the tails.","Ladder: P(X <= -0.9) = 0.02; P(X <= -0.7) = 0.06; P(X <= -0.5) = 0.10; P(X <= -0.4) = 0.17; P(X <= -0.3) = 0.26; P(X <= -0.2) = 0.38; P(X <= -0.1) = 0.52; P(X <= 0.0) = 0.65; P(X <= 0.1) = 0.76; P(X <= 0.2) = 0.84; P(X <= 0.3) = 0.90; P(X <= 0.5) = 0.97; P(X <= 0.7) = 0.99. Linear interpolation gives 10th percentile at -0.5, median at -0.1142857142857143, and 90th percentile at 0.3; rounded to BLS one-decimal print precision, the forecast is point -0.1 with 80 percent interval [-0.5, 0.3]."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Read BLS CPI summary for the latest CPI-U inflation reference class and deflator pressure.","Reference class and base rate: recent Table A-1 real hourly MoM prints centered below zero, with Mar.-May 2026 at -0.6, -0.5, and -0.1 after CPI-U rose 0.9, 0.6, and 0.5. A simple AR or persistence model and a short historical mean both point negative; I use persistence rather than a fitted model because this target is a one-month first-print combination of wages and CPI, and the available same-variant recent sample is short."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: starting from a persistence prior near the recent Table A-1 average of about -0.4 for Mar.-May 2026, I add about +0.2 because June nominal AHE momentum was still roughly 0.3 percent, add about +0.1 because May core CPI was only 0.2 despite headline energy pressure, and subtract a small residual risk adjustment for headline CPI and energy volatility visible in the Mar.-May CPI prints. June AHE and May CPI are momentum indicators, not direct July target inputs. The threshold span is a subjective 10th-90th elicitation anchored by fetched same-variant real AHE outcomes of -0.6, -0.5, -0.1, and +0.4 rather than a stable volatility estimate, so [-0.5, 0.3] covers a repeat negative month through a modest rebound while leaving larger CPI or wage surprises in the tails.","Upside risk: if July CPI-U cools sharply while nominal AHE keeps a 0.3 percent or better monthly pace, the real hourly print would land above the interval. Downside risk: renewed energy-price pressure, CPI above roughly 0.5 percent, or July nominal AHE below roughly 0.1 percent could put the deflator well above nominal wage growth and would land below the interval. An outside the interval outcome is most likely from a large CPI surprise or an unusually large July payroll wage surprise."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for July 2026 BLS real average hourly earnings MoM","Framing and exact resolver: this forecast is for BLS Real Earnings Table A-1, all employees on private nonfarm payrolls, seasonally adjusted, real average hourly earnings over-the-month percent change for July 2026. The target resolves to the one-decimal first print on the BLS official release page, with no later revision used."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-real-avg-hourly-earnings-mom-july-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-08-12\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T21-46-27Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-ladder-v2-2026-07-10t21-46-27z.87f4f37ec462d890","runId":"run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T21-46-27Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-ladder-v2-2026-07-10t21-46-27z.87f4f37ec462d890","predictionId":"us-real-avg-hourly-earnings-mom-july-2026","specId":"spec.us-real-avg-hourly-earnings-mom-july-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["This limited, non-contiguous reference class has a base rate near zero but substantial monthly variation: the fetched same-series prints span -0.6% to 0.3%, and the July 2025 analogue was 0.1%. Recent 2026 momentum is weaker, with March through May at -0.6%, -0.5%, and -0.1%.","Prior/update/interval: The persistence prior is the latest fetched first print, -0.1%; the median of the limited five-observation reference class is also -0.1%. I apply a -0.1 percentage-point momentum update for the three latest 2026 prints being negative, then a +0.1 percentage-point normalization update because May's 0.5% CPI-U increase was unusually strong relative to its 0.3% nominal-pay increase. These updates net to zero and retain a -0.1% point estimate. A separate formal time-series model was ruled out because the fetched first-print sample is limited and non-contiguous. The -0.6% and 0.3% fetched extremes anchor the ladder span, and linear interpolation of the ladder gives rounded 80% bounds of -0.5% and 0.3%."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["The target is the first printed one-decimal July 2026 over-the-month change in seasonally adjusted real average hourly earnings for all employees on private nonfarm payrolls in BLS Table A-1. Table A-1 uses CPI-U to deflate the all-employees CES earnings series; later revisions do not alter resolution.","Tool call: Inspect BLS Real Earnings Table A-1 archives for the recent 2026 first-print reference class."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the first printed one-decimal July 2026 over-the-month change in seasonally adjusted real average hourly earnings for all employees on private nonfarm payrolls in BLS Table A-1. Table A-1 uses CPI-U to deflate the all-employees CES earnings series; later revisions do not alter resolution.","Tool call: Inspect BLS Real Earnings Table A-1 archives for the recent 2026 first-print reference class."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.8, distribution present, forecast step count 1.","evidence":["Prior/update/interval: The persistence prior is the latest fetched first print, -0.1%; the median of the limited five-observation reference class is also -0.1%. I apply a -0.1 percentage-point momentum update for the three latest 2026 prints being negative, then a +0.1 percentage-point normalization update because May's 0.5% CPI-U increase was unusually strong relative to its 0.3% nominal-pay increase. These updates net to zero and retain a -0.1% point estimate. A separate formal time-series model was ruled out because the fetched first-print sample is limited and non-contiguous. The -0.6% and 0.3% fetched extremes anchor the ladder span, and linear interpolation of the ladder gives rounded 80% bounds of -0.5% and 0.3%.","Upside risk comes from softer-than-expected July CPI-U or a strong nominal-pay print and could put real earnings above 0.3%. Downside risk comes from another inflation surge combined with soft wage growth and could put the result below -0.5%; either outcome would land outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["This limited, non-contiguous reference class has a base rate near zero but substantial monthly variation: the fetched same-series prints span -0.6% to 0.3%, and the July 2025 analogue was 0.1%. Recent 2026 momentum is weaker, with March through May at -0.6%, -0.5%, and -0.1%.","Prior/update/interval: The persistence prior is the latest fetched first print, -0.1%; the median of the limited five-observation reference class is also -0.1%. I apply a -0.1 percentage-point momentum update for the three latest 2026 prints being negative, then a +0.1 percentage-point normalization update because May's 0.5% CPI-U increase was unusually strong relative to its 0.3% nominal-pay increase. These updates net to zero and retain a -0.1% point estimate. A separate formal time-series model was ruled out because the fetched first-print sample is limited and non-contiguous. The -0.6% and 0.3% fetched extremes anchor the ladder span, and linear interpolation of the ladder gives rounded 80% bounds of -0.5% and 0.3%."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["This limited, non-contiguous reference class has a base rate near zero but substantial monthly variation: the fetched same-series prints span -0.6% to 0.3%, and the July 2025 analogue was 0.1%. Recent 2026 momentum is weaker, with March through May at -0.6%, -0.5%, and -0.1%.","Upside risk comes from softer-than-expected July CPI-U or a strong nominal-pay print and could put real earnings above 0.3%. Downside risk comes from another inflation surge combined with soft wage growth and could put the result below -0.5%; either outcome would land outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["July 2026 US real average hourly earnings forecast","Prior/update/interval: The persistence prior is the latest fetched first print, -0.1%; the median of the limited five-observation reference class is also -0.1%. I apply a -0.1 percentage-point momentum update for the three latest 2026 prints being negative, then a +0.1 percentage-point normalization update because May's 0.5% CPI-U increase was unusually strong relative to its 0.3% nominal-pay increase. These updates net to zero and retain a -0.1% point estimate. A separate formal time-series model was ruled out because the fetched first-print sample is limited and non-contiguous. The -0.6% and 0.3% fetched extremes anchor the ladder span, and linear interpolation of the ladder gives rounded 80% bounds of -0.5% and 0.3%."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-real-avg-hourly-earnings-mom-july-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-08-12\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T22-05-19Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-ladder-v2-2026-07-10t22-05-19z.d8f6df0ad077d0e3","runId":"run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T22-05-19Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-ladder-v2-2026-07-10t22-05-19z.d8f6df0ad077d0e3","predictionId":"us-real-avg-hourly-earnings-mom-july-2026","specId":"spec.us-real-avg-hourly-earnings-mom-july-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Tool call: Fetched BLS Table A-1 historical observations for a reference-class check before reviewing the latest release.","Tool result: For the January 2016 through February 2026 Table A-1 seasonally adjusted monthly reference class, the central 80 percent of one-decimal monthly changes was approximately -0.7 percent to +0.8 percent, with a median near +0.1 percent; the sample spans 122 monthly prints."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The resolver is BLS Real Earnings Table A-1: the seasonally adjusted over-the-month percent-change row for real average hourly earnings of all employees on private nonfarm payrolls. Every anchor uses this exact variant; Table A-1 deflates nominal average hourly earnings using CPI-U.","Tool call: Fetched BLS Table A-1 historical observations for a reference-class check before reviewing the latest release."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["July 2026 real average hourly earnings, first print","Tool call: Fetched BLS Table A-1 historical observations for a reference-class check before reviewing the latest release."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.4, distribution present, forecast step count 1.","evidence":["Prior/update/interval: The historical prior is the January 2016-February 2026 Table A-1 reference class (122 monthly prints), with median about +0.1 percent and central 80 percent about -0.7 to +0.8 percent. The current-evidence update is the fetched March -0.6, April -0.5, and May -0.1 sequence, plus May's +0.3 percent nominal earnings change against +0.5 percent CPI-U, which moves the center to 0.0 percent while retaining roughly historical realized monthly dispersion for wage-growth, CPI-U, composition, and seasonal uncertainty. Ladder: P(X <= -1.0) = 0.03; P(X <= -0.8) = 0.06; P(X <= -0.6) = 0.13; P(X <= -0.4) = 0.23; P(X <= -0.2) = 0.37; P(X <= 0.0) = 0.53; P(X <= 0.2) = 0.68; P(X <= 0.4) = 0.79; P(X <= 0.6) = 0.87; P(X <= 0.8) = 0.93; P(X <= 1.0) = 0.96; P(X <= 1.2) = 0.98; P(X <= 1.4) = 0.99. Linear interpolation gives 10th percentile at -0.7, median at 0.0, and 90th percentile at 0.7; rounded to BLS's one-decimal print precision, the point is 0.0 percent and the 80% interval is -0.7 to 0.7 percent.","upside risk: a soft or negative July CPI-U print combined with firm nominal earnings could lift real hourly earnings above 0.7 percent. downside risk: a renewed CPI-U jump while nominal earnings growth slows could push the print below -0.7 percent. A larger energy-price or composition shock would land outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The reference class/base rate is the January 2016-February 2026 sequence of monthly seasonally adjusted Table A-1 real-hourly-earnings changes. I do not fit a separate predictive regression because the target is a one-decimal, short-horizon release with inflation, nominal-wage, and composition shocks that are not reliably known before release; the historical median near +0.1 percent and central 80 percent range of about -0.7 to +0.8 percent are the reproducible prior.","Review disposition: Accepted the requested ordering, explicit January 2016-February 2026 reference-class prior, quantified historical interval basis, and separate current-evidence update; retained the ladder-derived forecast because its bounds remain coherent with that evidence."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The March-to-May sequence (-0.6, -0.5, -0.1) updates the +0.1 percent historical-median prior downward, but the narrowing May shortfall argues against extending the earlier declines mechanically. Nominal earnings growth relative to CPI-U is the main near-term mechanism; changing private-nonfarm composition and seasonal adjustment remain residual sources of variation.","Prior/update/interval: The historical prior is the January 2016-February 2026 Table A-1 reference class (122 monthly prints), with median about +0.1 percent and central 80 percent about -0.7 to +0.8 percent. The current-evidence update is the fetched March -0.6, April -0.5, and May -0.1 sequence, plus May's +0.3 percent nominal earnings change against +0.5 percent CPI-U, which moves the center to 0.0 percent while retaining roughly historical realized monthly dispersion for wage-growth, CPI-U, composition, and seasonal uncertainty. Ladder: P(X <= -1.0) = 0.03; P(X <= -0.8) = 0.06; P(X <= -0.6) = 0.13; P(X <= -0.4) = 0.23; P(X <= -0.2) = 0.37; P(X <= 0.0) = 0.53; P(X <= 0.2) = 0.68; P(X <= 0.4) = 0.79; P(X <= 0.6) = 0.87; P(X <= 0.8) = 0.93; P(X <= 1.0) = 0.96; P(X <= 1.2) = 0.98; P(X <= 1.4) = 0.99. Linear interpolation gives 10th percentile at -0.7, median at 0.0, and 90th percentile at 0.7; rounded to BLS's one-decimal print precision, the point is 0.0 percent and the 80% interval is -0.7 to 0.7 percent."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: The historical prior is the January 2016-February 2026 Table A-1 reference class (122 monthly prints), with median about +0.1 percent and central 80 percent about -0.7 to +0.8 percent. The current-evidence update is the fetched March -0.6, April -0.5, and May -0.1 sequence, plus May's +0.3 percent nominal earnings change against +0.5 percent CPI-U, which moves the center to 0.0 percent while retaining roughly historical realized monthly dispersion for wage-growth, CPI-U, composition, and seasonal uncertainty. Ladder: P(X <= -1.0) = 0.03; P(X <= -0.8) = 0.06; P(X <= -0.6) = 0.13; P(X <= -0.4) = 0.23; P(X <= -0.2) = 0.37; P(X <= 0.0) = 0.53; P(X <= 0.2) = 0.68; P(X <= 0.4) = 0.79; P(X <= 0.6) = 0.87; P(X <= 0.8) = 0.93; P(X <= 1.0) = 0.96; P(X <= 1.2) = 0.98; P(X <= 1.4) = 0.99. Linear interpolation gives 10th percentile at -0.7, median at 0.0, and 90th percentile at 0.7; rounded to BLS's one-decimal print precision, the point is 0.0 percent and the 80% interval is -0.7 to 0.7 percent.","upside risk: a soft or negative July CPI-U print combined with firm nominal earnings could lift real hourly earnings above 0.7 percent. downside risk: a renewed CPI-U jump while nominal earnings growth slows could push the print below -0.7 percent. A larger energy-price or composition shock would land outside the interval."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-real-avg-hourly-earnings-mom-july-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-08-12\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T22-22-43Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-ladder-v2-2026-07-10t22-22-43z.9f7f2c5d786f5362","runId":"run.us-real-avg-hourly-earnings-mom-july-2026.2026-07-10T22-22-43Z.us-real-avg-hourly-earnings-mom-july-2026-thesis-analyst-ladder-v2-2026-07-10t22-22-43z.9f7f2c5d786f5362","predictionId":"us-real-avg-hourly-earnings-mom-july-2026","specId":"spec.us-real-avg-hourly-earnings-mom-july-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["The base rate/reference class is the five fetched 2026 observations: 0.3, 0.1, -0.6, -0.5, and -0.1 percent. Their median is -0.1 percent, with four of five values between -0.6 and 0.3.","The explicit model prior is a persistence time-series prior centered on the recent five-observation median, -0.1 percent. I do not use a richer autoregressive or structural model because the fetched sample is short and monthly real-earnings prints contain substantial deflator and seasonal-adjustment noise."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The target is the BLS CES series bls.real_earnings.avg_hourly_mom, specifically Table A-1 for all employees on private nonfarm payrolls, seasonally adjusted, and resolved at the first official July 2026 print without later revisions.","Tool call: BLS official release calendar lookup for the target release date"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["US real average hourly earnings, July 2026 first print","The target is the BLS CES series bls.real_earnings.avg_hourly_mom, specifically Table A-1 for all employees on private nonfarm payrolls, seasonally adjusted, and resolved at the first official July 2026 print without later revisions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.2, distribution present, forecast step count 1.","evidence":["Prior/update/interval: The persistence model prior is -0.1 percent. Recent negative momentum and CPI-U volatility are acknowledged, but no dated current evidence in the fetched release history warrants moving the point estimate from that prior. The fetched reference class anchors the ladder span from -0.6 to 0.3 percent; the ladder's interpolated 10th and 90th percentiles produce the 80% interval from -0.7 to 0.5 percent.","Downside risk is renewed CPI acceleration with nominal pay below trend, which would land below the interval; upside risk is softer CPI alongside firm nominal wage growth, which would land above the interval. An unusually large seasonal-adjustment change or release-month data shock would be outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The explicit model prior is a persistence time-series prior centered on the recent five-observation median, -0.1 percent. I do not use a richer autoregressive or structural model because the fetched sample is short and monthly real-earnings prints contain substantial deflator and seasonal-adjustment noise.","Prior/update/interval: The persistence model prior is -0.1 percent. Recent negative momentum and CPI-U volatility are acknowledged, but no dated current evidence in the fetched release history warrants moving the point estimate from that prior. The fetched reference class anchors the ladder span from -0.6 to 0.3 percent; the ladder's interpolated 10th and 90th percentiles produce the 80% interval from -0.7 to 0.5 percent."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: The persistence model prior is -0.1 percent. Recent negative momentum and CPI-U volatility are acknowledged, but no dated current evidence in the fetched release history warrants moving the point estimate from that prior. The fetched reference class anchors the ladder span from -0.6 to 0.3 percent; the ladder's interpolated 10th and 90th percentiles produce the 80% interval from -0.7 to 0.5 percent.","Downside risk is renewed CPI acceleration with nominal pay below trend, which would land below the interval; upside risk is softer CPI alongside firm nominal wage growth, which would land above the interval. An unusually large seasonal-adjustment change or release-month data shock would be outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: The persistence model prior is -0.1 percent. Recent negative momentum and CPI-U volatility are acknowledged, but no dated current evidence in the fetched release history warrants moving the point estimate from that prior. The fetched reference class anchors the ladder span from -0.6 to 0.3 percent; the ladder's interpolated 10th and 90th percentiles produce the 80% interval from -0.7 to 0.5 percent.","Downside risk is renewed CPI acceleration with nominal pay below trend, which would land below the interval; upside risk is softer CPI alongside firm nominal wage growth, which would land above the interval. An unusually large seasonal-adjustment change or release-month data shock would be outside the interval."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-real-avg-hourly-earnings-mom-july-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-08-12\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.wic-participation-may-2026.2026-07-10T05-07-34Z.001ef0202a223747","runId":"run.wic-participation-may-2026.2026-07-10T05-07-34Z.001ef0202a223747","predictionId":"wic-participation-may-2026","specId":"spec.wic-participation-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: for the same WIC total-participation variant, the three fetched May observations were 6.696739 million in 2023, 6.763710 million in 2024, and 6.894610 million in 2025. The three historical November-to-May moves were +0.300006 million from Nov 2022 to May 2023, +0.139673 million from Nov 2023 to May 2024, and +0.065289 million from Nov 2024 to May 2025.","Prior/update/interval: persistence prior uses the historical Nov-to-May reference class from fetched FNS monthly totals: changes were 0.300006, 0.139673, and 0.065289 million, average = 0.168323, so Nov 2025 initial 6.752138 + 0.168323 = 6.920461 million. May-trend prior uses May 2025 plus average of the two May-to-May gains: 6.894610 + ((0.066971 + 0.130900)/2) = 6.993546 million. I weight the persistence prior about 45% and the May-trend prior about 55%, then apply a small caution for the weak Nov 2025 first print, giving 6.960 million. Horizon-matched dispersion from the three Nov-to-May changes gives sigma = 0.119953 million; 1.28*sigma = 0.1535 million, rounded to 0.154. The three-observation volatility sample is thin, so this 80% interval is approximate, but it remains tied to the realized same-series dispersion: 6.960 - 0.154 = 6.806 and 6.960 + 0.154 = 7.114 million."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this is the USDA FNS WIC national Total Participants series for May 2026, not seasonally adjusted, resolved on the first official print from the WIC monthly program-data tables. The FNS WIC page is the exact series page; the target is a first-print value, so later revisions are excluded.","Tool call: Checked the official FNS program-data release calendar for the May 2026 WIC monthly release date."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["USDA FNS WIC total participation, May 2026 first print","Framing and exact resolver: this is the USDA FNS WIC national Total Participants series for May 2026, not seasonally adjusted, resolved on the first official print from the WIC monthly program-data tables. The FNS WIC page is the exact series page; the target is a first-print value, so later revisions are excluded."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.31, distribution present, forecast step count 1.","evidence":["Level and momentum: the clean May-to-May trend points upward, with May 2025 above May 2024 by 0.130900 million and May 2024 above May 2023 by 0.066971 million. The latest initial November 2025 level is unusually low relative to October 2025, so I discount a pure Nov 2025 persistence forecast and treat part of the drop as reporting/timing or temporary churn risk rather than a permanent level shift.","Prior/update/interval: persistence prior uses the historical Nov-to-May reference class from fetched FNS monthly totals: changes were 0.300006, 0.139673, and 0.065289 million, average = 0.168323, so Nov 2025 initial 6.752138 + 0.168323 = 6.920461 million. May-trend prior uses May 2025 plus average of the two May-to-May gains: 6.894610 + ((0.066971 + 0.130900)/2) = 6.993546 million. I weight the persistence prior about 45% and the May-trend prior about 55%, then apply a small caution for the weak Nov 2025 first print, giving 6.960 million. Horizon-matched dispersion from the three Nov-to-May changes gives sigma = 0.119953 million; 1.28*sigma = 0.1535 million, rounded to 0.154. The three-observation volatility sample is thin, so this 80% interval is approximate, but it remains tied to the realized same-series dispersion: 6.960 - 0.154 = 6.806 and 6.960 + 0.154 = 7.114 million."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level and momentum: the clean May-to-May trend points upward, with May 2025 above May 2024 by 0.130900 million and May 2024 above May 2023 by 0.066971 million. The latest initial November 2025 level is unusually low relative to October 2025, so I discount a pure Nov 2025 persistence forecast and treat part of the drop as reporting/timing or temporary churn risk rather than a permanent level shift."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level and momentum: the clean May-to-May trend points upward, with May 2025 above May 2024 by 0.130900 million and May 2024 above May 2023 by 0.066971 million. The latest initial November 2025 level is unusually low relative to October 2025, so I discount a pure Nov 2025 persistence forecast and treat part of the drop as reporting/timing or temporary churn risk rather than a permanent level shift.","Prior/update/interval: persistence prior uses the historical Nov-to-May reference class from fetched FNS monthly totals: changes were 0.300006, 0.139673, and 0.065289 million, average = 0.168323, so Nov 2025 initial 6.752138 + 0.168323 = 6.920461 million. May-trend prior uses May 2025 plus average of the two May-to-May gains: 6.894610 + ((0.066971 + 0.130900)/2) = 6.993546 million. I weight the persistence prior about 45% and the May-trend prior about 55%, then apply a small caution for the weak Nov 2025 first print, giving 6.960 million. Horizon-matched dispersion from the three Nov-to-May changes gives sigma = 0.119953 million; 1.28*sigma = 0.1535 million, rounded to 0.154. The three-observation volatility sample is thin, so this 80% interval is approximate, but it remains tied to the realized same-series dispersion: 6.960 - 0.154 = 6.806 and 6.960 + 0.154 = 7.114 million."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Level and momentum: the clean May-to-May trend points upward, with May 2025 above May 2024 by 0.130900 million and May 2024 above May 2023 by 0.066971 million. The latest initial November 2025 level is unusually low relative to October 2025, so I discount a pure Nov 2025 persistence forecast and treat part of the drop as reporting/timing or temporary churn risk rather than a permanent level shift.","Prior/update/interval: persistence prior uses the historical Nov-to-May reference class from fetched FNS monthly totals: changes were 0.300006, 0.139673, and 0.065289 million, average = 0.168323, so Nov 2025 initial 6.752138 + 0.168323 = 6.920461 million. May-trend prior uses May 2025 plus average of the two May-to-May gains: 6.894610 + ((0.066971 + 0.130900)/2) = 6.993546 million. I weight the persistence prior about 45% and the May-trend prior about 55%, then apply a small caution for the weak Nov 2025 first print, giving 6.960 million. Horizon-matched dispersion from the three Nov-to-May changes gives sigma = 0.119953 million; 1.28*sigma = 0.1535 million, rounded to 0.154. The three-observation volatility sample is thin, so this 80% interval is approximate, but it remains tied to the realized same-series dispersion: 6.960 - 0.154 = 6.806 and 6.960 + 0.154 = 7.114 million."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: wic-participation-may-2026\nrunLabel: Headline\nresolutionDate: 2026-08-14\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.wic-participation-may-2026.2026-07-10T15-40-26Z.wic-participation-may-2026-thesis-analyst-fast-2026-07-10t15-40-26z.eb00709dc445e977","runId":"run.wic-participation-may-2026.2026-07-10T15-40-26Z.wic-participation-may-2026-thesis-analyst-fast-2026-07-10t15-40-26z.eb00709dc445e977","predictionId":"wic-participation-may-2026","specId":"spec.wic-participation-may-2026","runLabel":"Fast rollout 1 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The reference class/base rate is recent May-to-May growth in this exact national monthly series: +0.067 million from May 2023 to May 2024 and +0.131 million from May 2024 to May 2025, for a two-change mean of +0.099 million. I use that seasonal persistence prior rather than extrapolating November's seasonal decline directly.","Prior/update/interval: persistence-plus-May-seasonality model using the two historical May-over-May changes (+0.067 and +0.131 million) implies 6.895 + 0.099 = 6.994 million, rounded to a 6.995 million point after modest support from the FY 2025 level. From the FY 2025 successive monthly changes in the fetched table, sigma = 0.041 million; 1.28*sigma = 0.052 million. The 80% interval is therefore 6.995 +/- 0.052 = [6.943, 7.047] million. No widening is applied because the historical May trend and recent annual level point in the same direction."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Tool result: The official table reports May total participants of 6,696,739 in 2023, 6,763,710 in 2024, and 6,894,610 in 2025; expressed in millions these are 6.697, 6.764, and 6.895.","Tool call: Fetched the official USDA FNS monthly WIC participation PDF through the WIC Data Tables page."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["USDA FNS WIC total participants, May 2026 first print","The resolver is the monthly national-level WIC table's Total Participants column, not annual quality-control material or a state table. The FNS release-calendar schedule verified the target's 2026-08-14 resolution date. The source variant is the unadjusted monthly national-level total-participant series; all anchors below use that same table."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.1, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence-plus-May-seasonality model using the two historical May-over-May changes (+0.067 and +0.131 million) implies 6.895 + 0.099 = 6.994 million, rounded to a 6.995 million point after modest support from the FY 2025 level. From the FY 2025 successive monthly changes in the fetched table, sigma = 0.041 million; 1.28*sigma = 0.052 million. The 80% interval is therefore 6.995 +/- 0.052 = [6.943, 7.047] million. No widening is applied because the historical May trend and recent annual level point in the same direction.","upside risk is continued enrollment expansion at the stronger 2024-to-2025 May pace, which could put May 2026 above 7.047 million. downside risk is a durable rather than seasonal post-October enrollment contraction, which could put it below 6.943 million. A large reporting or eligibility-policy discontinuity would land outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence-plus-May-seasonality model using the two historical May-over-May changes (+0.067 and +0.131 million) implies 6.895 + 0.099 = 6.994 million, rounded to a 6.995 million point after modest support from the FY 2025 level. From the FY 2025 successive monthly changes in the fetched table, sigma = 0.041 million; 1.28*sigma = 0.052 million. The 80% interval is therefore 6.995 +/- 0.052 = [6.943, 7.047] million. No widening is applied because the historical May trend and recent annual level point in the same direction."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["upside risk is continued enrollment expansion at the stronger 2024-to-2025 May pace, which could put May 2026 above 7.047 million. downside risk is a durable rather than seasonal post-October enrollment contraction, which could put it below 6.943 million. A large reporting or eligibility-policy discontinuity would land outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: persistence-plus-May-seasonality model using the two historical May-over-May changes (+0.067 and +0.131 million) implies 6.895 + 0.099 = 6.994 million, rounded to a 6.995 million point after modest support from the FY 2025 level. From the FY 2025 successive monthly changes in the fetched table, sigma = 0.041 million; 1.28*sigma = 0.052 million. The 80% interval is therefore 6.995 +/- 0.052 = [6.943, 7.047] million. No widening is applied because the historical May trend and recent annual level point in the same direction.","upside risk is continued enrollment expansion at the stronger 2024-to-2025 May pace, which could put May 2026 above 7.047 million. downside risk is a durable rather than seasonal post-October enrollment contraction, which could put it below 6.943 million. A large reporting or eligibility-policy discontinuity would land outside the interval."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: wic-participation-may-2026\nrunLabel: Fast rollout 1 of 3\nresolutionDate: 2026-08-14\ntraceLineCount: 12\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.wic-participation-may-2026.2026-07-10T15-44-49Z.wic-participation-may-2026-thesis-analyst-fast-2026-07-10t15-44-49z.c8acc86ead1c99d8","runId":"run.wic-participation-may-2026.2026-07-10T15-44-49Z.wic-participation-may-2026-thesis-analyst-fast-2026-07-10t15-44-49z.c8acc86ead1c99d8","predictionId":"wic-participation-may-2026","specId":"spec.wic-participation-may-2026","runLabel":"Fast rollout 2 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool call: Retrieved matching historical March-to-May rows from the FNS national monthly table for the seasonal reference class.","The base rate/reference class is the same national monthly total series: May rose by 0.067 million year over year in 2024 and 0.131 million in 2025, while the latest 2026 level is materially below March 2025. I therefore use the recent 2026 level and the historical March-to-May pattern rather than extrapolating the earlier annual acceleration."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 2 source-context item(s), activity log present.","evidence":["Tool result: FNS reports May 2023 Total Participants of 6,696,739, May 2024 of 6,763,710, May 2025 of 6,894,610, and March 2026 of 6,701,661 persons.","The official FNS release schedule was checked for the August 14, 2026 release window. Resolution remains strict first print: use the first FNS posting containing the May 2026 national total, convert the whole-person display to millions, and do not substitute later revisions."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The official FNS release schedule was checked for the August 14, 2026 release window. Resolution remains strict first print: use the first FNS posting containing the May 2026 national total, convert the whole-person display to millions, and do not substitute later revisions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.13, distribution present, forecast step count 1.","evidence":["Prior/update/interval: A seasonal-persistence prior starts from March 2026 at 6.702 million; the 2023-25 March-to-May increases average (0.075+0.083+0.044)/3 = 0.067 million. A downward momentum adjustment of 0.004 million for the weaker late-2025/early-2026 level gives 6.702+0.067-0.004 = 6.765 million. From the 11 successive monthly changes from April 2025 through March 2026, sigma = 0.050 million; 1.28*sigma = 0.064 million, so the 80% bounds are 6.765-0.064 = 6.701 and 6.765+0.064 = 6.829 million.","Upside risk is a renewed enrollment or retention increase that recreates the 2024-25 year-over-year gains; downside risk is continued weakness in women, infant, and child enrollment after the late-2025 fall. A sustained administrative or policy shock would land outside the interval, above 6.829 or below 6.701 million."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Retrieved the recent FNS monthly rows to measure current level and short-run momentum.","Prior/update/interval: A seasonal-persistence prior starts from March 2026 at 6.702 million; the 2023-25 March-to-May increases average (0.075+0.083+0.044)/3 = 0.067 million. A downward momentum adjustment of 0.004 million for the weaker late-2025/early-2026 level gives 6.702+0.067-0.004 = 6.765 million. From the 11 successive monthly changes from April 2025 through March 2026, sigma = 0.050 million; 1.28*sigma = 0.064 million, so the 80% bounds are 6.765-0.064 = 6.701 and 6.765+0.064 = 6.829 million."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Upside risk is a renewed enrollment or retention increase that recreates the 2024-25 year-over-year gains; downside risk is continued weakness in women, infant, and child enrollment after the late-2025 fall. A sustained administrative or policy shock would land outside the interval, above 6.829 or below 6.701 million."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["US WIC total participation forecast for May 2026","Prior/update/interval: A seasonal-persistence prior starts from March 2026 at 6.702 million; the 2023-25 March-to-May increases average (0.075+0.083+0.044)/3 = 0.067 million. A downward momentum adjustment of 0.004 million for the weaker late-2025/early-2026 level gives 6.702+0.067-0.004 = 6.765 million. From the 11 successive monthly changes from April 2025 through March 2026, sigma = 0.050 million; 1.28*sigma = 0.064 million, so the 80% bounds are 6.765-0.064 = 6.701 and 6.765+0.064 = 6.829 million."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: wic-participation-may-2026\nrunLabel: Fast rollout 2 of 3\nresolutionDate: 2026-08-14\ntraceLineCount: 13\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.wic-participation-may-2026.2026-07-10T15-48-42Z.wic-participation-may-2026-thesis-analyst-fast-2026-07-10t15-48-42z.811c9b7dee7b2519","runId":"run.wic-participation-may-2026.2026-07-10T15-48-42Z.wic-participation-may-2026-thesis-analyst-fast-2026-07-10t15-48-42z.811c9b7dee7b2519","predictionId":"wic-participation-may-2026","specId":"spec.wic-participation-may-2026","runLabel":"Fast rollout 3 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The reference class/base rate is recent May-to-May national participation growth: the two observed gains average 98,936 participants, or 0.099 million. This uses the same monthly-national Total Participants variant throughout.","Prior/update/interval: persistence-plus-seasonal-year-over-year prior using the May 2023-25 historical sample; adjustment components are the +0.099 million average May-to-May gain, no discrete policy-level adjustment, and modest first-print/reporting uncertainty. Applying 6.895 + 0.099 gives 6.994 million. From the fetched 2025 successive monthly changes, sigma = 0.062 million; 1.28*sigma = 0.079 million. The six-month forecast horizon and the unusually large Oct-to-Nov movement justify widening the half-width to 0.115 million (1.46x), giving 6.879 to 7.109 million."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The resolver is the unadjusted monthly national WIC Total Participants table, not an annual quality-control or eligibility estimate. The FNS WIC Data Tables page identifies the monthly national table; the value is a displayed person count converted to millions. The official FNS release-calendar lookup schedules the May 2026 program-data posting for 2026-08-14, which verifies the target resolution date.","Tool call: Fetched the official FNS WIC monthly-national table, data as of February 13, 2026, for recent Total Participants observations."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["USDA FNS WIC Total Participants — May 2026 first print","The resolver is the unadjusted monthly national WIC Total Participants table, not an annual quality-control or eligibility estimate. The FNS WIC Data Tables page identifies the monthly national table; the value is a displayed person count converted to millions. The official FNS release-calendar lookup schedules the May 2026 program-data posting for 2026-08-14, which verifies the target resolution date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.23, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence-plus-seasonal-year-over-year prior using the May 2023-25 historical sample; adjustment components are the +0.099 million average May-to-May gain, no discrete policy-level adjustment, and modest first-print/reporting uncertainty. Applying 6.895 + 0.099 gives 6.994 million. From the fetched 2025 successive monthly changes, sigma = 0.062 million; 1.28*sigma = 0.079 million. The six-month forecast horizon and the unusually large Oct-to-Nov movement justify widening the half-width to 0.115 million (1.46x), giving 6.879 to 7.109 million.","upside risk: faster enrollment uptake or a stronger spring rebound would land above the interval. downside risk: weaker retention, administrative disruption, or an unusually low first print would land below the interval. A May print outside the interval would falsify the persistence-plus-recent-May-growth assumption."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence-plus-seasonal-year-over-year prior using the May 2023-25 historical sample; adjustment components are the +0.099 million average May-to-May gain, no discrete policy-level adjustment, and modest first-print/reporting uncertainty. Applying 6.895 + 0.099 gives 6.994 million. From the fetched 2025 successive monthly changes, sigma = 0.062 million; 1.28*sigma = 0.079 million. The six-month forecast horizon and the unusually large Oct-to-Nov movement justify widening the half-width to 0.115 million (1.46x), giving 6.879 to 7.109 million.","upside risk: faster enrollment uptake or a stronger spring rebound would land above the interval. downside risk: weaker retention, administrative disruption, or an unusually low first print would land below the interval. A May print outside the interval would falsify the persistence-plus-recent-May-growth assumption."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: persistence-plus-seasonal-year-over-year prior using the May 2023-25 historical sample; adjustment components are the +0.099 million average May-to-May gain, no discrete policy-level adjustment, and modest first-print/reporting uncertainty. Applying 6.895 + 0.099 gives 6.994 million. From the fetched 2025 successive monthly changes, sigma = 0.062 million; 1.28*sigma = 0.079 million. The six-month forecast horizon and the unusually large Oct-to-Nov movement justify widening the half-width to 0.115 million (1.46x), giving 6.879 to 7.109 million.","upside risk: faster enrollment uptake or a stronger spring rebound would land above the interval. downside risk: weaker retention, administrative disruption, or an unusually low first print would land below the interval. A May print outside the interval would falsify the persistence-plus-recent-May-growth assumption."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: wic-participation-may-2026\nrunLabel: Fast rollout 3 of 3\nresolutionDate: 2026-08-14\ntraceLineCount: 12\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.wic-participation-may-2026.2026-07-10T15-48-43Z.wic-participation-may-2026-thesis-analyst-median3-2026-07-10t15-48-43z.4dcc4ab5cb95bf07","runId":"run.wic-participation-may-2026.2026-07-10T15-48-43Z.wic-participation-may-2026-thesis-analyst-median3-2026-07-10t15-48-43z.4dcc4ab5cb95bf07","predictionId":"wic-participation-may-2026","specId":"spec.wic-participation-may-2026","runLabel":"Median of 3 rollouts","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 5 historical point(s) and implicit outside-view language.","evidence":["Median-of-3 rollout ensemble","Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T15:40:26Z, 2026-07-10T15:44:49Z, 2026-07-10T15:48:42Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Median CDF quantiles: q10 = 6.879, q50 = 6.994, q90 = 7.048. Constituent points [6.995, 6.765, 6.994] with 80% widths [0.104, 0.128, 0.23]; the median interval inherits the central rollout mass rather than averaging tails."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.17, distribution present, forecast step count 1.","evidence":["Median CDF quantiles: q10 = 6.879, q50 = 6.994, q90 = 7.048. Constituent points [6.995, 6.765, 6.994] with 80% widths [0.104, 0.128, 0.23]; the median interval inherits the central rollout mass rather than averaging tails.","Forecast: point 6.994, 80% interval [6.879, 7.048]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T15:40:26Z, 2026-07-10T15:44:49Z, 2026-07-10T15:48:42Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T15:40:26Z, 2026-07-10T15:44:49Z, 2026-07-10T15:48:42Z. Drivers and resolver fields mirror the rollout closest to the median.","Tool result: {rollout_points: [6.995, 6.765, 6.994], rollout_widths: [0.104, 0.128, 0.23], q10: 6.879, q50: 6.994, q90: 7.048}"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: wic-participation-may-2026\nrunLabel: Median of 3 rollouts\nresolutionDate: 2026-08-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.wic-participation-may-2026.2026-07-10T16-17-58Z.wic-participation-may-2026-thesis-analyst-ladder-2026-07-10t16-17-58z.e8533e15bd3f81bc","runId":"run.wic-participation-may-2026.2026-07-10T16-17-58Z.wic-participation-may-2026-thesis-analyst-ladder-2026-07-10t16-17-58z.e8533e15bd3f81bc","predictionId":"wic-participation-may-2026","specId":"spec.wic-participation-may-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: recent same-variant May totals rose from 6.697 million in May 2023 to 6.764 million in May 2024 to 6.895 million in May 2025, but the latest first-print official observation, November 2025 at 6.752 million, was 1.1% below November 2024. A simple base rate is therefore May 2025 adjusted down roughly 0.5%-1.0%, with only partial recovery from the low November initial print.","Prior/update/interval: persistence prior = May 2025 level of 6.895 million, historical sample = monthly USDA FNS national WIC totals from Oct 2022 through Nov 2025, adjustment components = -0.060 million for weaker latest year-over-year level, +0.015 million as a small judgmental spring adjustment after a low initial November, giving 6.850 million. Using successive monthly changes from the fetched history, sigma = 0.054 million, so 1.28*sigma = 0.069 million. I widen to a ladder-implied 80% half-width of 0.120 million, 1.74x the one-step half-width, because the target is six months beyond the latest available first print and November 2025 showed an unusually large -0.157 million one-month change."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this is the USDA FNS national monthly WIC Total Participants series for May 2026, first official print only, converted from whole persons to millions. I use the WIC Data Tables page and the national monthly WIC Participation and Costs table for the same national monthly variant; annual summaries are context only, not the resolution vintage.","Tool call: Open USDA FNS WIC Data Tables page and identify the official monthly WIC data materials, latest-month materials, and current coverage."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this is the USDA FNS national monthly WIC Total Participants series for May 2026, first official print only, converted from whole persons to millions. I use the WIC Data Tables page and the national monthly WIC Participation and Costs table for the same national monthly variant; annual summaries are context only, not the resolution vintage.","Tool call: Check USDA FNS data release calendar for the scheduled May 2026 WIC monthly release date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.24, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = May 2025 level of 6.895 million, historical sample = monthly USDA FNS national WIC totals from Oct 2022 through Nov 2025, adjustment components = -0.060 million for weaker latest year-over-year level, +0.015 million as a small judgmental spring adjustment after a low initial November, giving 6.850 million. Using successive monthly changes from the fetched history, sigma = 0.054 million, so 1.28*sigma = 0.069 million. I widen to a ladder-implied 80% half-width of 0.120 million, 1.74x the one-step half-width, because the target is six months beyond the latest available first print and November 2025 showed an unusually large -0.157 million one-month change.","Ladder: P(X <= 6.640) = 0.03; P(X <= 6.680) = 0.06; P(X <= 6.710) = 0.085; P(X <= 6.730) = 0.10; P(X <= 6.760) = 0.17; P(X <= 6.790) = 0.27; P(X <= 6.820) = 0.39; P(X <= 6.850) = 0.50; P(X <= 6.880) = 0.62; P(X <= 6.910) = 0.73; P(X <= 6.940) = 0.83; P(X <= 6.970) = 0.90; P(X <= 7.010) = 0.96. Linear interpolation gives the 10th percentile 6.730, median 6.850, and 90th percentile 6.970 million, so the 80% interval is the threshold-ladder 10th-to-90th percentile range."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior = May 2025 level of 6.895 million, historical sample = monthly USDA FNS national WIC totals from Oct 2022 through Nov 2025, adjustment components = -0.060 million for weaker latest year-over-year level, +0.015 million as a small judgmental spring adjustment after a low initial November, giving 6.850 million. Using successive monthly changes from the fetched history, sigma = 0.054 million, so 1.28*sigma = 0.069 million. I widen to a ladder-implied 80% half-width of 0.120 million, 1.74x the one-step half-width, because the target is six months beyond the latest available first print and November 2025 showed an unusually large -0.157 million one-month change."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Reference class and base rate: recent same-variant May totals rose from 6.697 million in May 2023 to 6.764 million in May 2024 to 6.895 million in May 2025, but the latest first-print official observation, November 2025 at 6.752 million, was 1.1% below November 2024. A simple base rate is therefore May 2025 adjusted down roughly 0.5%-1.0%, with only partial recovery from the low November initial print.","Counter-considerations: upside risk is a rebound from the unusually low November 2025 initial print plus normal spring enrollment strength, which would land above the interval if May 2026 prints above 6.970 million. Downside risk is that the November drop reflects a durable eligibility, outreach, or reporting decline; a continuation below roughly 6.730 million would land outside the interval on the low side."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["US WIC May 2026 total participation forecast","Prior/update/interval: persistence prior = May 2025 level of 6.895 million, historical sample = monthly USDA FNS national WIC totals from Oct 2022 through Nov 2025, adjustment components = -0.060 million for weaker latest year-over-year level, +0.015 million as a small judgmental spring adjustment after a low initial November, giving 6.850 million. Using successive monthly changes from the fetched history, sigma = 0.054 million, so 1.28*sigma = 0.069 million. I widen to a ladder-implied 80% half-width of 0.120 million, 1.74x the one-step half-width, because the target is six months beyond the latest available first print and November 2025 showed an unusually large -0.157 million one-month change."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: wic-participation-may-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-08-14\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.wic-participation-may-2026.2026-07-10T16-29-32Z.wic-participation-may-2026-thesis-analyst-fast-2026-07-10t16-29-32z.4d8424574f8eda6d","runId":"run.wic-participation-may-2026.2026-07-10T16-29-32Z.wic-participation-may-2026-thesis-analyst-fast-2026-07-10t16-29-32z.4d8424574f8eda6d","predictionId":"wic-participation-may-2026","specId":"spec.wic-participation-may-2026","runLabel":"Fast rollout 1 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: using the same national Total Participants variant, recent May levels were 6.697 million in 2023, 6.764 million in 2024, and 6.895 million in 2025, while the latest observed November 2025 level was 6.752 million. Prior Nov-to-May moves were +0.300 million from Nov 2022 to May 2023, +0.140 million from Nov 2023 to May 2024, and +0.065 million from Nov 2024 to May 2025, so I anchor on a positive but smaller seasonal rebound from the depressed November 2025 print.","Prior/update/interval: persistence prior from latest Nov 2025 is 6.752 million; seasonal reference-class adjustment uses the shrinking Nov-to-May rebound, adding about +0.090 million rather than the full three-cycle mean of +0.168 million, giving 6.842 million. For interval sizing, successive monthly changes from Oct 2024 through Nov 2025 are -0.078, -0.045, +0.038, -0.021, +0.049, +0.026, +0.017, -0.011, +0.040, -0.028, +0.026, -0.013, -0.157 million, so sigma = 0.057 million and 1.28*sigma = 0.073 million. I widen to 0.100 million because the target is six unobserved months ahead and the latest observation included a large November drop, implying final bounds 6.842 - 0.100 = 6.742 and 6.842 + 0.100 = 6.942."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this is the USDA FNS WIC national Monthly Data Total Participants series, not state-level detail, not annual fiscal-year average participation, and not a revised final vintage. The target unit is millions, so the first-print whole-person count for May 2026 will be divided by 1,000,000 and rounded to 0.001 million.","Tool call: Checked the FNS Data & Research listing for posted program-data cadence and the official release-date contract for this target."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this is the USDA FNS WIC national Monthly Data Total Participants series, not state-level detail, not annual fiscal-year average participation, and not a revised final vintage. The target unit is millions, so the first-print whole-person count for May 2026 will be divided by 1,000,000 and rounded to 0.001 million.","Tool call: Checked the FNS Data & Research listing for posted program-data cadence and the official release-date contract for this target."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.2, distribution present, forecast step count 1.","evidence":["Framing and exact resolver: this is the USDA FNS WIC national Monthly Data Total Participants series, not state-level detail, not annual fiscal-year average participation, and not a revised final vintage. The target unit is millions, so the first-print whole-person count for May 2026 will be divided by 1,000,000 and rounded to 0.001 million.","Prior/update/interval: persistence prior from latest Nov 2025 is 6.752 million; seasonal reference-class adjustment uses the shrinking Nov-to-May rebound, adding about +0.090 million rather than the full three-cycle mean of +0.168 million, giving 6.842 million. For interval sizing, successive monthly changes from Oct 2024 through Nov 2025 are -0.078, -0.045, +0.038, -0.021, +0.049, +0.026, +0.017, -0.011, +0.040, -0.028, +0.026, -0.013, -0.157 million, so sigma = 0.057 million and 1.28*sigma = 0.073 million. I widen to 0.100 million because the target is six unobserved months ahead and the latest observation included a large November drop, implying final bounds 6.842 - 0.100 = 6.742 and 6.842 + 0.100 = 6.942."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior from latest Nov 2025 is 6.752 million; seasonal reference-class adjustment uses the shrinking Nov-to-May rebound, adding about +0.090 million rather than the full three-cycle mean of +0.168 million, giving 6.842 million. For interval sizing, successive monthly changes from Oct 2024 through Nov 2025 are -0.078, -0.045, +0.038, -0.021, +0.049, +0.026, +0.017, -0.011, +0.040, -0.028, +0.026, -0.013, -0.157 million, so sigma = 0.057 million and 1.28*sigma = 0.073 million. I widen to 0.100 million because the target is six unobserved months ahead and the latest observation included a large November drop, implying final bounds 6.842 - 0.100 = 6.742 and 6.842 + 0.100 = 6.942.","Level and momentum adjustment: the May-to-May trend was positive through 2025, but November 2025 was 0.077 million below November 2024 and 0.157 million below October 2025. That argues against simply extrapolating May 2025 upward, while the prior three Nov-to-May recoveries argue against treating November 2025 as the May 2026 level."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: using the same national Total Participants variant, recent May levels were 6.697 million in 2023, 6.764 million in 2024, and 6.895 million in 2025, while the latest observed November 2025 level was 6.752 million. Prior Nov-to-May moves were +0.300 million from Nov 2022 to May 2023, +0.140 million from Nov 2023 to May 2024, and +0.065 million from Nov 2024 to May 2025, so I anchor on a positive but smaller seasonal rebound from the depressed November 2025 print.","Level and momentum adjustment: the May-to-May trend was positive through 2025, but November 2025 was 0.077 million below November 2024 and 0.157 million below October 2025. That argues against simply extrapolating May 2025 upward, while the prior three Nov-to-May recoveries argue against treating November 2025 as the May 2026 level."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["USDA FNS WIC May 2026 Total Participation Forecast","Prior/update/interval: persistence prior from latest Nov 2025 is 6.752 million; seasonal reference-class adjustment uses the shrinking Nov-to-May rebound, adding about +0.090 million rather than the full three-cycle mean of +0.168 million, giving 6.842 million. For interval sizing, successive monthly changes from Oct 2024 through Nov 2025 are -0.078, -0.045, +0.038, -0.021, +0.049, +0.026, +0.017, -0.011, +0.040, -0.028, +0.026, -0.013, -0.157 million, so sigma = 0.057 million and 1.28*sigma = 0.073 million. I widen to 0.100 million because the target is six unobserved months ahead and the latest observation included a large November drop, implying final bounds 6.842 - 0.100 = 6.742 and 6.842 + 0.100 = 6.942."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: wic-participation-may-2026\nrunLabel: Fast rollout 1 of 3\nresolutionDate: 2026-08-14\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.wic-participation-may-2026.2026-07-10T16-41-06Z.wic-participation-may-2026-thesis-analyst-fast-2026-07-10t16-41-06z.d895169c8bc56276","runId":"run.wic-participation-may-2026.2026-07-10T16-41-06Z.wic-participation-may-2026-thesis-analyst-fast-2026-07-10t16-41-06z.d895169c8bc56276","predictionId":"wic-participation-may-2026","specId":"spec.wic-participation-may-2026","runLabel":"Fast rollout 2 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.51,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the recent official-source reference class is the prior November-to-May movement in national WIC total participation. The fetched November-to-May changes were +0.300006 million from Nov 2022 to May 2023, +0.139673 million from Nov 2023 to May 2024, and +0.065289 million from Nov 2024 to May 2025, so a positive seasonal lift is normal but has been shrinking as participation flattened.","Prior/update/interval: persistence prior starts from the latest official November 2025 initial value of 6.752138 million. The historical Nov-to-May base-rate average is +0.168 million, but the sequence has decelerated from +0.300 to +0.140 to +0.065 million, so I use a conservative +0.068 million update: 6.752 + 0.068 = 6.820 million. For uncertainty, using the three fetched Nov-to-May changes, sigma = 0.120 million; 1.28*sigma = 0.154 million, giving 6.820 +/- 0.154 = [6.666, 6.974]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this is USDA FNS WIC national Total Participants, not SNAP, not annual WIC quality-control data, and not a revised annual summary. The target resolves on the first official FNS monthly WIC table that first includes May 2026, using the national total participants count converted to millions.","Tool call: Checked the official FNS data-release-calendar target timing for the WIC May 2026 first-print row."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this is USDA FNS WIC national Total Participants, not SNAP, not annual WIC quality-control data, and not a revised annual summary. The target resolves on the first official FNS monthly WIC table that first includes May 2026, using the national total participants count converted to millions.","Tool call: Checked the official FNS data-release-calendar target timing for the WIC May 2026 first-print row."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.31, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior starts from the latest official November 2025 initial value of 6.752138 million. The historical Nov-to-May base-rate average is +0.168 million, but the sequence has decelerated from +0.300 to +0.140 to +0.065 million, so I use a conservative +0.068 million update: 6.752 + 0.068 = 6.820 million. For uncertainty, using the three fetched Nov-to-May changes, sigma = 0.120 million; 1.28*sigma = 0.154 million, giving 6.820 +/- 0.154 = [6.666, 6.974].","Counter-considerations: upside risk is a cleaner rebound from the weak November 2025 initial print or stronger enrollment retention, which would land above the interval if May 2026 exceeds about 6.974 million. Downside risk is continued attrition or first-print under-reporting similar to the November 2025 drop, which would land below the interval if May 2026 is under about 6.666 million. A large funding or reporting disruption would be the main outside the interval scenario."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: the recent official-source reference class is the prior November-to-May movement in national WIC total participation. The fetched November-to-May changes were +0.300006 million from Nov 2022 to May 2023, +0.139673 million from Nov 2023 to May 2024, and +0.065289 million from Nov 2024 to May 2025, so a positive seasonal lift is normal but has been shrinking as participation flattened.","Prior/update/interval: persistence prior starts from the latest official November 2025 initial value of 6.752138 million. The historical Nov-to-May base-rate average is +0.168 million, but the sequence has decelerated from +0.300 to +0.140 to +0.065 million, so I use a conservative +0.068 million update: 6.752 + 0.068 = 6.820 million. For uncertainty, using the three fetched Nov-to-May changes, sigma = 0.120 million; 1.28*sigma = 0.154 million, giving 6.820 +/- 0.154 = [6.666, 6.974]."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["US WIC Total Participation May 2026 Forecast","Prior/update/interval: persistence prior starts from the latest official November 2025 initial value of 6.752138 million. The historical Nov-to-May base-rate average is +0.168 million, but the sequence has decelerated from +0.300 to +0.140 to +0.065 million, so I use a conservative +0.068 million update: 6.752 + 0.068 = 6.820 million. For uncertainty, using the three fetched Nov-to-May changes, sigma = 0.120 million; 1.28*sigma = 0.154 million, giving 6.820 +/- 0.154 = [6.666, 6.974]."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: wic-participation-may-2026\nrunLabel: Fast rollout 2 of 3\nresolutionDate: 2026-08-14\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.wic-participation-may-2026.2026-07-10T16-53-08Z.wic-participation-may-2026-thesis-analyst-fast-2026-07-10t16-53-08z.a3f8e9b7d1c816db","runId":"run.wic-participation-may-2026.2026-07-10T16-53-08Z.wic-participation-may-2026-thesis-analyst-fast-2026-07-10t16-53-08z.a3f8e9b7d1c816db","predictionId":"wic-participation-may-2026","specId":"spec.wic-participation-may-2026","runLabel":"Fast rollout 3 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: the cleanest reference class is national WIC monthly Total Participants around the same spring months. May seasonality has been positive in recent years: Mar-to-May was +75,428 in 2023, +82,736 in 2024, and +43,774 in 2025, averaging +67,313 participants, while the latest Mar 2026 level is materially below Mar 2025.","Prior/update/interval: persistence prior = Mar 2026 initial 6.701661 million; seasonal update = average Mar-to-May lift of (0.075428 + 0.082736 + 0.043774)/3 = 0.067313 million; trend/policy adjustment = -0.010 million for the -2.2% YoY latest print and weak winter level; point = 6.701661 + 0.067313 - 0.010 = 6.758974, rounded to 6.759. For the 80% interval, recent official monthly successive-change dispersion gives sigma = 0.066 million; half-width = 1.28*sigma = 0.084 million, so 6.759 +/- 0.084 gives 6.675 to 6.843."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this is the USDA FNS WIC Program national Total Participants series, first official May 2026 monthly print, displayed as persons and converted to millions. I am using the same first-print national variant for anchors where available; annual summaries and later revisions are context only, not the resolution value. The official FNS release calendar was checked this run for the May 2026 WIC monthly release date, matching 2026-08-14.","Tool result: Official national monthly table values: May 2023 Total Participants 6,696,739; May 2024 6,763,710; May 2025 6,894,610; Oct 2025 6,909,050; Nov 2025 6,752,138."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["WIC May 2026 First-Print Participation Forecast","Framing and exact resolver: this is the USDA FNS WIC Program national Total Participants series, first official May 2026 monthly print, displayed as persons and converted to millions. I am using the same first-print national variant for anchors where available; annual summaries and later revisions are context only, not the resolution value. The official FNS release calendar was checked this run for the May 2026 WIC monthly release date, matching 2026-08-14."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.17, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = Mar 2026 initial 6.701661 million; seasonal update = average Mar-to-May lift of (0.075428 + 0.082736 + 0.043774)/3 = 0.067313 million; trend/policy adjustment = -0.010 million for the -2.2% YoY latest print and weak winter level; point = 6.701661 + 0.067313 - 0.010 = 6.758974, rounded to 6.759. For the 80% interval, recent official monthly successive-change dispersion gives sigma = 0.066 million; half-width = 1.28*sigma = 0.084 million, so 6.759 +/- 0.084 gives 6.675 to 6.843.","Counter-considerations: upside risk would be a faster spring rebound in large states such as California, Texas, New York, or Florida that pushes May above the usual seasonal lift and would land above the interval. Downside risk would be continued enrollment attrition, reporting disruptions, or state-level administrative tightening that keeps May near the weak February-March level and would land below the interval. Outside the interval would require roughly more than 84,000 participants above or below this adjusted seasonal path."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-considerations: upside risk would be a faster spring rebound in large states such as California, Texas, New York, or Florida that pushes May above the usual seasonal lift and would land above the interval. Downside risk would be continued enrollment attrition, reporting disruptions, or state-level administrative tightening that keeps May near the weak February-March level and would land below the interval. Outside the interval would require roughly more than 84,000 participants above or below this adjusted seasonal path."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["WIC May 2026 First-Print Participation Forecast","Prior/update/interval: persistence prior = Mar 2026 initial 6.701661 million; seasonal update = average Mar-to-May lift of (0.075428 + 0.082736 + 0.043774)/3 = 0.067313 million; trend/policy adjustment = -0.010 million for the -2.2% YoY latest print and weak winter level; point = 6.701661 + 0.067313 - 0.010 = 6.758974, rounded to 6.759. For the 80% interval, recent official monthly successive-change dispersion gives sigma = 0.066 million; half-width = 1.28*sigma = 0.084 million, so 6.759 +/- 0.084 gives 6.675 to 6.843."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: wic-participation-may-2026\nrunLabel: Fast rollout 3 of 3\nresolutionDate: 2026-08-14\ntraceLineCount: 12\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.wic-participation-may-2026.2026-07-10T16-53-09Z.wic-participation-may-2026-thesis-analyst-median3-2026-07-10t16-53-09z.bff506d4f640c286","runId":"run.wic-participation-may-2026.2026-07-10T16-53-09Z.wic-participation-may-2026-thesis-analyst-median3-2026-07-10t16-53-09z.bff506d4f640c286","predictionId":"wic-participation-may-2026","specId":"spec.wic-participation-may-2026","runLabel":"Median of 3 rollouts","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 5 historical point(s) and implicit outside-view language.","evidence":["Median-of-3 rollout ensemble","Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T16:29:32Z, 2026-07-10T16:41:06Z, 2026-07-10T16:53:08Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 8 source-context item(s), activity log present.","evidence":["Median CDF quantiles: q10 = 6.674, q50 = 6.82, q90 = 6.943. Constituent points [6.842, 6.82, 6.759] with 80% widths [0.2, 0.308, 0.168]; the median interval inherits the central rollout mass rather than averaging tails."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.27, distribution present, forecast step count 1.","evidence":["Median CDF quantiles: q10 = 6.674, q50 = 6.82, q90 = 6.943. Constituent points [6.842, 6.82, 6.759] with 80% widths [0.2, 0.308, 0.168]; the median interval inherits the central rollout mass rather than averaging tails.","Forecast: point 6.82, 80% interval [6.674, 6.943]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T16:29:32Z, 2026-07-10T16:41:06Z, 2026-07-10T16:53:08Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T16:29:32Z, 2026-07-10T16:41:06Z, 2026-07-10T16:53:08Z. Drivers and resolver fields mirror the rollout closest to the median.","Tool result: {rollout_points: [6.842, 6.82, 6.759], rollout_widths: [0.2, 0.308, 0.168], q10: 6.674, q50: 6.82, q90: 6.943}"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: wic-participation-may-2026\nrunLabel: Median of 3 rollouts\nresolutionDate: 2026-08-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.wic-participation-may-2026.2026-07-10T17-16-30Z.wic-participation-may-2026-thesis-analyst-ladder-2026-07-10t17-16-30z.4b87e756be2e2f8e","runId":"run.wic-participation-may-2026.2026-07-10T17-16-30Z.wic-participation-may-2026-thesis-analyst-ladder-2026-07-10t17-16-30z.4b87e756be2e2f8e","predictionId":"wic-participation-may-2026","specId":"spec.wic-participation-may-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The outside-view reference class is successive monthly changes in the official Table 21 national total from October 2023 through May 2025. Its base rate is small month-to-month movement around a slowly changing level, with May 2025 about 0.131 million above May 2024 but November 2025 initial about 0.142 million below October preliminary.","Prior/update/interval: A persistence/local-level prior centered near 6.85 million uses the 19 successive changes from the fetched October 2023–May 2025 Table 21 history. Their realized standard deviation is approximately sigma = 0.047 million, so a normal 80% half-width is 1.28*sigma = 1.28*0.047 = 0.060 million. The update combines +0.025 million for the earlier year-over-year rise, -0.015 million for late-2025 weakness, and no large policy shock, giving a central value near 6.86 million. The ladder implies bounds of 6.760–6.940, a 0.090-million average half-width, 1.50 times the sigma half-width; this widening reflects first-print state-reporting noise and uncertainty about whether the November weakness persists."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The target is USDA FNS Table 21 national WIC Total Participation for May 2026, measured as people issued benefits during the calendar month. This forecast uses the first posted monthly value, converted from people to millions; subsequent revisions are excluded.","Tool result: The official table reported 6,763,710 participants in May 2024, 6,876,342 in April 2025, and 6,889,500 in the later May 2025 table vintage; the target's documented May 2025 first print was 6,894,610."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["May 2026 national WIC participation first print","The target is USDA FNS Table 21 national WIC Total Participation for May 2026, measured as people issued benefits during the calendar month. This forecast uses the first posted monthly value, converted from people to millions; subsequent revisions are excluded."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.18, distribution present, forecast step count 1.","evidence":["Prior/update/interval: A persistence/local-level prior centered near 6.85 million uses the 19 successive changes from the fetched October 2023–May 2025 Table 21 history. Their realized standard deviation is approximately sigma = 0.047 million, so a normal 80% half-width is 1.28*sigma = 1.28*0.047 = 0.060 million. The update combines +0.025 million for the earlier year-over-year rise, -0.015 million for late-2025 weakness, and no large policy shock, giving a central value near 6.86 million. The ladder implies bounds of 6.760–6.940, a 0.090-million average half-width, 1.50 times the sigma half-width; this widening reflects first-print state-reporting noise and uncertainty about whether the November weakness persists.","Upside risk comes from renewed outreach, retention, or normalization after the weak November initial print and could put participation above 6.940 million. Downside risk comes from continued caseload attrition or incomplete first-print state reporting and could put it below 6.760 million. A major reporting disruption or abrupt eligibility-policy effect would land outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Fetch the USDA FNS latest-month WIC participation table for late-2025 momentum.","Level and momentum are separated as follows: the level anchor is roughly 6.85 million; the earlier year-over-year rise contributes a modest positive adjustment, while late-2025 weakness contributes a negative adjustment. No discrete May 2026 eligibility or benefit-policy shock is evident; FY 2026 cash-value benefit adjustments are treated as broadly supportive rather than a large caseload mechanism."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The outside-view reference class is successive monthly changes in the official Table 21 national total from October 2023 through May 2025. Its base rate is small month-to-month movement around a slowly changing level, with May 2025 about 0.131 million above May 2024 but November 2025 initial about 0.142 million below October preliminary.","Level and momentum are separated as follows: the level anchor is roughly 6.85 million; the earlier year-over-year rise contributes a modest positive adjustment, while late-2025 weakness contributes a negative adjustment. No discrete May 2026 eligibility or benefit-policy shock is evident; FY 2026 cash-value benefit adjustments are treated as broadly supportive rather than a large caseload mechanism."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The target is USDA FNS Table 21 national WIC Total Participation for May 2026, measured as people issued benefits during the calendar month. This forecast uses the first posted monthly value, converted from people to millions; subsequent revisions are excluded.","Prior/update/interval: A persistence/local-level prior centered near 6.85 million uses the 19 successive changes from the fetched October 2023–May 2025 Table 21 history. Their realized standard deviation is approximately sigma = 0.047 million, so a normal 80% half-width is 1.28*sigma = 1.28*0.047 = 0.060 million. The update combines +0.025 million for the earlier year-over-year rise, -0.015 million for late-2025 weakness, and no large policy shock, giving a central value near 6.86 million. The ladder implies bounds of 6.760–6.940, a 0.090-million average half-width, 1.50 times the sigma half-width; this widening reflects first-print state-reporting noise and uncertainty about whether the November weakness persists."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: wic-participation-may-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-08-14\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.wic-participation-may-2026.2026-07-10T17-22-38Z.wic-participation-may-2026-thesis-analyst-fast-2026-07-10t17-22-38z.f63846308644295e","runId":"run.wic-participation-may-2026.2026-07-10T17-22-38Z.wic-participation-may-2026-thesis-analyst-fast-2026-07-10t17-22-38z.f63846308644295e","predictionId":"wic-participation-may-2026","specId":"spec.wic-participation-may-2026","runLabel":"Fast rollout 1 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The outside-view reference class is the official national monthly series. Its base rate shows May rising by 0.067 million from 2023 to 2024 and by 0.131 million from 2024 to 2025, while FY2025 averaged 6.866095 million versus 6.704329 million in FY2024.","Prior/update/interval: persistence prior = May 2025 at 6.894610 million; historical sample = the 12 successive official monthly changes from October 2024 through October 2025; adjustments = +0.025 million for the positive May reference-class trend, -0.010 million for weak late-2025 momentum, and 0.000 million for identified policy effects, giving 6.910 million after rounding. The sample standard deviation of those successive changes is sigma = 0.039 million, so the 80% normal half-width is approximately 1.28*sigma = 1.28*0.039 = 0.050 million, implying bounds of 6.910-0.050 = 6.860 and 6.910+0.050 = 6.960 million."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The target is the unadjusted national Total Participants series in the USDA FNS WIC monthly table, not an annual fiscal-year quality-control measure. Resolution uses the first May 2026 posting and converts persons to millions.","Tool call: Fetch the USDA FNS national WIC monthly participation table and read May observations."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the unadjusted national Total Participants series in the USDA FNS WIC monthly table, not an annual fiscal-year quality-control measure. Resolution uses the first May 2026 posting and converts persons to millions.","Tool call: Verify the target date against the official FNS release schedule recorded for this release."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.1, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = May 2025 at 6.894610 million; historical sample = the 12 successive official monthly changes from October 2024 through October 2025; adjustments = +0.025 million for the positive May reference-class trend, -0.010 million for weak late-2025 momentum, and 0.000 million for identified policy effects, giving 6.910 million after rounding. The sample standard deviation of those successive changes is sigma = 0.039 million, so the 80% normal half-width is approximately 1.28*sigma = 1.28*0.039 = 0.050 million, implying bounds of 6.910-0.050 = 6.860 and 6.910+0.050 = 6.960 million.","Upside risk comes from continued child-participation growth and stronger retention, which could put the print above 6.960 million. Downside risk comes from broad caseload attrition or incomplete state reporting; a repeat of the November 2025 initial-report disruption would land below the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level and momentum are separated as follows: the May 2025 level supplies the seasonal anchor; the two-year May momentum is positive; October 2025 was nearly flat against that anchor; and the November 2025 initial decline is treated mainly as reporting noise rather than a persistent policy effect.","Prior/update/interval: persistence prior = May 2025 at 6.894610 million; historical sample = the 12 successive official monthly changes from October 2024 through October 2025; adjustments = +0.025 million for the positive May reference-class trend, -0.010 million for weak late-2025 momentum, and 0.000 million for identified policy effects, giving 6.910 million after rounding. The sample standard deviation of those successive changes is sigma = 0.039 million, so the 80% normal half-width is approximately 1.28*sigma = 1.28*0.039 = 0.050 million, implying bounds of 6.910-0.050 = 6.860 and 6.910+0.050 = 6.960 million."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Upside risk comes from continued child-participation growth and stronger retention, which could put the print above 6.960 million. Downside risk comes from broad caseload attrition or incomplete state reporting; a repeat of the November 2025 initial-report disruption would land below the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["May 2026 national WIC participation forecast","Prior/update/interval: persistence prior = May 2025 at 6.894610 million; historical sample = the 12 successive official monthly changes from October 2024 through October 2025; adjustments = +0.025 million for the positive May reference-class trend, -0.010 million for weak late-2025 momentum, and 0.000 million for identified policy effects, giving 6.910 million after rounding. The sample standard deviation of those successive changes is sigma = 0.039 million, so the 80% normal half-width is approximately 1.28*sigma = 1.28*0.039 = 0.050 million, implying bounds of 6.910-0.050 = 6.860 and 6.910+0.050 = 6.960 million."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: wic-participation-may-2026\nrunLabel: Fast rollout 1 of 3\nresolutionDate: 2026-08-14\ntraceLineCount: 13\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.wic-participation-may-2026.2026-07-10T17-28-34Z.wic-participation-may-2026-thesis-analyst-fast-2026-07-10t17-28-34z.c86edafca922e849","runId":"run.wic-participation-may-2026.2026-07-10T17-28-34Z.wic-participation-may-2026-thesis-analyst-fast-2026-07-10t17-28-34z.c86edafca922e849","predictionId":"wic-participation-may-2026","specId":"spec.wic-participation-may-2026","runLabel":"Fast rollout 2 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool call: Fetched the same official WIC national table's historical May observations.","The reference class and base rate are the three prior March-to-May moves: +0.075428 million in 2023, +0.082736 million in 2024, and +0.043774 million in 2025, averaging +0.067313 million. However, the latest year-over-year level change is materially negative: March 2026 was 0.149175 million below March 2025."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The target is the first national monthly WIC Total Participants print for May 2026. The series is a calendar-month, not seasonally adjusted FNS-798 participation count; the official table identifier is the WIC Monthly Data—National Level table. Resolution preserves the ledger's strict first-print rule and converts persons to millions.","Tool result: The June 12, 2026 official table reports total participation of 6,701,661 in March 2026, 6,664,580 in February 2026, and 6,696,300 in January 2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The target is the first national monthly WIC Total Participants print for May 2026. The series is a calendar-month, not seasonally adjusted FNS-798 participation count; the official table identifier is the WIC Monthly Data—National Level table. Resolution preserves the ledger's strict first-print rule and converts persons to millions.","Tool call: Checked the official WIC program-data publication schedule and target release window for the first table expected to include May 2026."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.13, distribution present, forecast step count 1.","evidence":["Prior/update/interval: The persistence prior is May 2025's 6.894610 million adjusted by the March year-over-year change of -0.149175 million, giving 6.745435 million, rounded to 6.745. The historical sample is the 12 successive monthly changes from March 2025 through March 2026 in the official national table. Their sample standard deviation is sigma = 0.049 million, so the 80% half-width is approximately 1.28*sigma = 1.28*0.049 = 0.0627 million. Applying that to 6.745 gives 6.6823 to 6.8077, rounded outward to final bounds of 6.683 and 6.808 million. The seasonal March-to-May increase is acknowledged but not added separately because the year-over-year persistence construction already compares like months and avoids double-counting seasonality.","An upside risk is a return to the 2023-2025 March-to-May gains alongside stabilization in child participation, which could land above 6.808 million. A downside risk is continued attrition in women and infant participation or reporting disruption comparable to late 2025, which could land below 6.683 million. Either outcome would be outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: The persistence prior is May 2025's 6.894610 million adjusted by the March year-over-year change of -0.149175 million, giving 6.745435 million, rounded to 6.745. The historical sample is the 12 successive monthly changes from March 2025 through March 2026 in the official national table. Their sample standard deviation is sigma = 0.049 million, so the 80% half-width is approximately 1.28*sigma = 1.28*0.049 = 0.0627 million. Applying that to 6.745 gives 6.6823 to 6.8077, rounded outward to final bounds of 6.683 and 6.808 million. The seasonal March-to-May increase is acknowledged but not added separately because the year-over-year persistence construction already compares like months and avoids double-counting seasonality."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The reference class and base rate are the three prior March-to-May moves: +0.075428 million in 2023, +0.082736 million in 2024, and +0.043774 million in 2025, averaging +0.067313 million. However, the latest year-over-year level change is materially negative: March 2026 was 0.149175 million below March 2025.","Prior/update/interval: The persistence prior is May 2025's 6.894610 million adjusted by the March year-over-year change of -0.149175 million, giving 6.745435 million, rounded to 6.745. The historical sample is the 12 successive monthly changes from March 2025 through March 2026 in the official national table. Their sample standard deviation is sigma = 0.049 million, so the 80% half-width is approximately 1.28*sigma = 1.28*0.049 = 0.0627 million. Applying that to 6.745 gives 6.6823 to 6.8077, rounded outward to final bounds of 6.683 and 6.808 million. The seasonal March-to-May increase is acknowledged but not added separately because the year-over-year persistence construction already compares like months and avoids double-counting seasonality."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["May 2026 national WIC participation forecast","Prior/update/interval: The persistence prior is May 2025's 6.894610 million adjusted by the March year-over-year change of -0.149175 million, giving 6.745435 million, rounded to 6.745. The historical sample is the 12 successive monthly changes from March 2025 through March 2026 in the official national table. Their sample standard deviation is sigma = 0.049 million, so the 80% half-width is approximately 1.28*sigma = 1.28*0.049 = 0.0627 million. Applying that to 6.745 gives 6.6823 to 6.8077, rounded outward to final bounds of 6.683 and 6.808 million. The seasonal March-to-May increase is acknowledged but not added separately because the year-over-year persistence construction already compares like months and avoids double-counting seasonality."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: wic-participation-may-2026\nrunLabel: Fast rollout 2 of 3\nresolutionDate: 2026-08-14\ntraceLineCount: 12\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.wic-participation-may-2026.2026-07-10T17-33-53Z.wic-participation-may-2026-thesis-analyst-fast-2026-07-10t17-33-53z.b536a6c5c95c11d2","runId":"run.wic-participation-may-2026.2026-07-10T17-33-53Z.wic-participation-may-2026-thesis-analyst-fast-2026-07-10t17-33-53z.b536a6c5c95c11d2","predictionId":"wic-participation-may-2026","specId":"spec.wic-participation-may-2026","runLabel":"Fast rollout 3 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The reference class and base rate are monthly national WIC participation prints. The 2025 spring sequence rose from 6.851 million in March to 6.876 million in April and 6.890 million in May, while the later December 2025 level was lower at 6.695 million. A persistence-plus-seasonality forecast therefore starts near the recent 6.7-million regime and adds a modest spring lift.","Prior/update/interval: persistence prior = 6.695 million from December 2025; historical sample = October 2024 through May 2025 official monthly totals; adjustments = +0.039 million spring pattern and +0.016 million partial normalization, giving 6.750 million. Successive changes in that sample were -0.078, -0.045, +0.036, -0.020, +0.050, +0.026, and +0.013 million; their realized standard deviation is sigma = 0.045 million. The 80% half-width is approximately 1.28*sigma = 1.28*0.045 = 0.058 million, implying 6.750 ± 0.058 = [6.692, 6.808]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Tool result: The official page was updated June 18, 2026 and identifies national monthly data through March 2026; its May 2025 table vintage reports totals of 6,850,711 in March 2025, 6,876,342 in April 2025, and 6,889,500 in May 2025.","Tool call: Check the official FNS data-release calendar for the posting expected to first include May 2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The target is the first USDA FNS national monthly WIC Total Participants print for May 2026, measured as certified individuals issued food benefits during that calendar month. The WIC national monthly table is the exact series; no seasonal adjustment or alternative eligibility measure is used.","Tool call: Check the official FNS data-release calendar for the posting expected to first include May 2026."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.12, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = 6.695 million from December 2025; historical sample = October 2024 through May 2025 official monthly totals; adjustments = +0.039 million spring pattern and +0.016 million partial normalization, giving 6.750 million. Successive changes in that sample were -0.078, -0.045, +0.036, -0.020, +0.050, +0.026, and +0.013 million; their realized standard deviation is sigma = 0.045 million. The 80% half-width is approximately 1.28*sigma = 1.28*0.045 = 0.058 million, implying 6.750 ± 0.058 = [6.692, 6.808].","Upside risk: stronger outreach, recertification retention, or a broad rise in adjunct eligibility would land above 6.808 million. Downside risk: continued caseload attrition, delayed state reporting, or administrative disruptions would land below 6.692 million. Either outcome would be outside the interval and falsify the assumed stable spring regime."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level effect: anchor near 6.70 million from the late-2025 regime. Momentum effect: participation had declined from 6.908 million in October 2024 to 6.695 million in December 2025. Seasonal effect: March-to-May 2025 added about 0.039 million. Policy/one-off effect: no quantified nationwide May 2026 eligibility or benefit-issuance discontinuity is added, so the adjustment is deliberately small."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Upside risk: stronger outreach, recertification retention, or a broad rise in adjunct eligibility would land above 6.808 million. Downside risk: continued caseload attrition, delayed state reporting, or administrative disruptions would land below 6.692 million. Either outcome would be outside the interval and falsify the assumed stable spring regime."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["May 2026 national WIC participation forecast","The reference class and base rate are monthly national WIC participation prints. The 2025 spring sequence rose from 6.851 million in March to 6.876 million in April and 6.890 million in May, while the later December 2025 level was lower at 6.695 million. A persistence-plus-seasonality forecast therefore starts near the recent 6.7-million regime and adds a modest spring lift."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: wic-participation-may-2026\nrunLabel: Fast rollout 3 of 3\nresolutionDate: 2026-08-14\ntraceLineCount: 13\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.wic-participation-may-2026.2026-07-10T17-33-54Z.wic-participation-may-2026-thesis-analyst-median3-2026-07-10t17-33-54z.b0fa9223fb078f9c","runId":"run.wic-participation-may-2026.2026-07-10T17-33-54Z.wic-participation-may-2026-thesis-analyst-median3-2026-07-10t17-33-54z.b0fa9223fb078f9c","predictionId":"wic-participation-may-2026","specId":"spec.wic-participation-may-2026","runLabel":"Median of 3 rollouts","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 5 historical point(s) and implicit outside-view language.","evidence":["Median-of-3 rollout ensemble","Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T17:22:38Z, 2026-07-10T17:28:34Z, 2026-07-10T17:33:53Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 8 source-context item(s), activity log present.","evidence":["Median CDF quantiles: q10 = 6.691, q50 = 6.75, q90 = 6.808. Constituent points [6.91, 6.745, 6.75] with 80% widths [0.1, 0.125, 0.116]; the median interval inherits the central rollout mass rather than averaging tails."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.12, distribution present, forecast step count 1.","evidence":["Median CDF quantiles: q10 = 6.691, q50 = 6.75, q90 = 6.808. Constituent points [6.91, 6.745, 6.75] with 80% widths [0.1, 0.125, 0.116]; the median interval inherits the central rollout mass rather than averaging tails.","Forecast: point 6.75, 80% interval [6.691, 6.808]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T17:22:38Z, 2026-07-10T17:28:34Z, 2026-07-10T17:33:53Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T17:22:38Z, 2026-07-10T17:28:34Z, 2026-07-10T17:33:53Z. Drivers and resolver fields mirror the rollout closest to the median.","Tool result: {rollout_points: [6.91, 6.745, 6.75], rollout_widths: [0.1, 0.125, 0.116], q10: 6.691, q50: 6.75, q90: 6.808}"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: wic-participation-may-2026\nrunLabel: Median of 3 rollouts\nresolutionDate: 2026-08-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.wic-participation-may-2026.2026-07-10T21-27-30Z.wic-participation-may-2026-thesis-analyst-ladder-v2-2026-07-10t21-27-30z.da0350e42e86e913","runId":"run.wic-participation-may-2026.2026-07-10T21-27-30Z.wic-participation-may-2026-thesis-analyst-ladder-v2-2026-07-10t21-27-30z.da0350e42e86e913","predictionId":"wic-participation-may-2026","specId":"spec.wic-participation-may-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: the most relevant reference class is recent national WIC monthly first prints on the same FNS WIC table. The Nov 2025 initial count was 1.1% below Nov 2024, while May 2025 was 6.895 million; applying roughly the recent year-over-year softness to the May seasonal anchor gives an outside-view base rate near 6.82 million before current-policy adjustments.","Prior/update/interval: model prior = simple same-month persistence/seasonal-drift model, with base prior = May 2025 same-month value of 6.894610 million; historical sample = fetched FNS latest-month totals of 6.829321 million for Nov 2024, 6.909050 million for Oct 2025 preliminary, and 6.752138 million for Nov 2025 initial; adjustment components = about -0.075 million for recent year-over-year softness, -0.020 million for funding/administrative risk, and -0.010 million for first-print noise/momentum, implying a center near 6.79 million. The interval method is the threshold ladder below, with rung span anchored by the fetched 6.752138 latest initial, 6.909050 prior-month preliminary, and 6.894610 May same-month values plus allowance for first-print and policy disruption; the derived 6.583-7.010 range has an approximate 80% half-width of 0.214 million, wider than the recent 0.157 million anchor spread to cover normal first-print noise plus administrative and funding risk."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this is the national USDA FNS WIC Total Participants monthly table value for May 2026, not annual fiscal-year WIC participation and not a quality-control release. The target unit is millions, so the FNS person count is divided by 1,000,000 and rounded to 0.001 million. I keep the strict first-print policy and do not add a same-day correction or revision grace rule.","Tool call: Checked the official FNS data-release calendar for the registered May 2026 WIC monthly-data release date and cross-checked the WIC series page."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["USDA FNS WIC total participation, May 2026 first print","Framing and exact resolver: this is the national USDA FNS WIC Total Participants monthly table value for May 2026, not annual fiscal-year WIC participation and not a quality-control release. The target unit is millions, so the FNS person count is divided by 1,000,000 and rounded to 0.001 million. I keep the strict first-print policy and do not add a same-day correction or revision grace rule."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.43, distribution present, forecast step count 1.","evidence":["Level, momentum, and mechanism: the level anchor is May 2025 at 6.895 million, the latest observed initial level is lower at 6.752 million in November 2025, and the six-month seasonal path from November to May is usually not a large structural break. I make a modest downward update for reported year-over-year softness and administrative/funding uncertainty, partly offset by normal eligibility continuity and the tendency for WIC caseloads to be sticky month to month. The October 2025 value is preliminary, so I use it as context for current level rather than as a final-resolution analogue.","Prior/update/interval: model prior = simple same-month persistence/seasonal-drift model, with base prior = May 2025 same-month value of 6.894610 million; historical sample = fetched FNS latest-month totals of 6.829321 million for Nov 2024, 6.909050 million for Oct 2025 preliminary, and 6.752138 million for Nov 2025 initial; adjustment components = about -0.075 million for recent year-over-year softness, -0.020 million for funding/administrative risk, and -0.010 million for first-print noise/momentum, implying a center near 6.79 million. The interval method is the threshold ladder below, with rung span anchored by the fetched 6.752138 latest initial, 6.909050 prior-month preliminary, and 6.894610 May same-month values plus allowance for first-print and policy disruption; the derived 6.583-7.010 range has an approximate 80% half-width of 0.214 million, wider than the recent 0.157 million anchor spread to cover normal first-print noise plus administrative and funding risk."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, and mechanism: the level anchor is May 2025 at 6.895 million, the latest observed initial level is lower at 6.752 million in November 2025, and the six-month seasonal path from November to May is usually not a large structural break. I make a modest downward update for reported year-over-year softness and administrative/funding uncertainty, partly offset by normal eligibility continuity and the tendency for WIC caseloads to be sticky month to month. The October 2025 value is preliminary, so I use it as context for current level rather than as a final-resolution analogue.","Prior/update/interval: model prior = simple same-month persistence/seasonal-drift model, with base prior = May 2025 same-month value of 6.894610 million; historical sample = fetched FNS latest-month totals of 6.829321 million for Nov 2024, 6.909050 million for Oct 2025 preliminary, and 6.752138 million for Nov 2025 initial; adjustment components = about -0.075 million for recent year-over-year softness, -0.020 million for funding/administrative risk, and -0.010 million for first-print noise/momentum, implying a center near 6.79 million. The interval method is the threshold ladder below, with rung span anchored by the fetched 6.752138 latest initial, 6.909050 prior-month preliminary, and 6.894610 May same-month values plus allowance for first-print and policy disruption; the derived 6.583-7.010 range has an approximate 80% half-width of 0.214 million, wider than the recent 0.157 million anchor spread to cover normal first-print noise plus administrative and funding risk."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, and mechanism: the level anchor is May 2025 at 6.895 million, the latest observed initial level is lower at 6.752 million in November 2025, and the six-month seasonal path from November to May is usually not a large structural break. I make a modest downward update for reported year-over-year softness and administrative/funding uncertainty, partly offset by normal eligibility continuity and the tendency for WIC caseloads to be sticky month to month. The October 2025 value is preliminary, so I use it as context for current level rather than as a final-resolution analogue.","Prior/update/interval: model prior = simple same-month persistence/seasonal-drift model, with base prior = May 2025 same-month value of 6.894610 million; historical sample = fetched FNS latest-month totals of 6.829321 million for Nov 2024, 6.909050 million for Oct 2025 preliminary, and 6.752138 million for Nov 2025 initial; adjustment components = about -0.075 million for recent year-over-year softness, -0.020 million for funding/administrative risk, and -0.010 million for first-print noise/momentum, implying a center near 6.79 million. The interval method is the threshold ladder below, with rung span anchored by the fetched 6.752138 latest initial, 6.909050 prior-month preliminary, and 6.894610 May same-month values plus allowance for first-print and policy disruption; the derived 6.583-7.010 range has an approximate 80% half-width of 0.214 million, wider than the recent 0.157 million anchor spread to cover normal first-print noise plus administrative and funding risk."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: Opened USDA FNS WIC Latest Month Participation PDF for the latest national first-print/state-level reference point.","Prior/update/interval: model prior = simple same-month persistence/seasonal-drift model, with base prior = May 2025 same-month value of 6.894610 million; historical sample = fetched FNS latest-month totals of 6.829321 million for Nov 2024, 6.909050 million for Oct 2025 preliminary, and 6.752138 million for Nov 2025 initial; adjustment components = about -0.075 million for recent year-over-year softness, -0.020 million for funding/administrative risk, and -0.010 million for first-print noise/momentum, implying a center near 6.79 million. The interval method is the threshold ladder below, with rung span anchored by the fetched 6.752138 latest initial, 6.909050 prior-month preliminary, and 6.894610 May same-month values plus allowance for first-print and policy disruption; the derived 6.583-7.010 range has an approximate 80% half-width of 0.214 million, wider than the recent 0.157 million anchor spread to cover normal first-print noise plus administrative and funding risk."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: wic-participation-may-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-08-14\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.wic-participation-may-2026.2026-07-10T21-48-07Z.wic-participation-may-2026-thesis-analyst-ladder-v2-2026-07-10t21-48-07z.a1ba09ab0ed6c882","runId":"run.wic-participation-may-2026.2026-07-10T21-48-07Z.wic-participation-may-2026-thesis-analyst-ladder-v2-2026-07-10t21-48-07z.a1ba09ab0ed6c882","predictionId":"wic-participation-may-2026","specId":"spec.wic-participation-may-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The reference class is the same-series March-to-May movement: +75,428 in 2023, +82,736 in 2024, and +43,774 in 2025. Its median increase is 75,428. Applying that base rate to March 2026 gives 6,777,089, while the May year-over-year decline implied by that anchor is about 1.7%.","Prior/update/interval: The persistence prior is March 2026 participation of 6.701661 million, with the historical sample consisting of the fetched 2023-2025 March-to-May changes. A formal time-series model is unsuitable because only three directly comparable March-to-May first-print changes were fetched and the latest observations are preliminary, making parameter estimates unstable. I add the median seasonal change of 0.075428 million and make no separate level adjustment because current weakness is embedded in March. The resulting 6.777089 million anchor rounds to 6.777 million; the ladder's coarser elicited median is 6.780 million, a 0.003 million difference representing negligible centering and print-grid rounding rather than a new substantive adjustment. Reporting incompleteness and variation across the three seasonal changes broaden the ladder, which implies final 80% bounds of 6.650 to 6.900 million."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The target is the first USDA FNS national monthly-table print of Total Participants for May 2026, not an annual average, eligibility estimate, revised value, or state-only measure. The official table has no separate seasonal adjustment. The displayed person count is converted to millions and rounded to 0.001.","Tool call: Fetched the latest available FY 2026 observations from the USDA WIC national monthly table."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the first USDA FNS national monthly-table print of Total Participants for May 2026, not an annual average, eligibility estimate, revised value, or state-only measure. The official table has no separate seasonal adjustment. The displayed person count is converted to millions and rounded to 0.001.","Tool call: Checked the official program-data schedule associated with the registered release window for the May 2026 posting."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.25, distribution present, forecast step count 1.","evidence":["Tool call: Fetched category detail for the latest month and annual reference values from the official USDA table.","Prior/update/interval: The persistence prior is March 2026 participation of 6.701661 million, with the historical sample consisting of the fetched 2023-2025 March-to-May changes. A formal time-series model is unsuitable because only three directly comparable March-to-May first-print changes were fetched and the latest observations are preliminary, making parameter estimates unstable. I add the median seasonal change of 0.075428 million and make no separate level adjustment because current weakness is embedded in March. The resulting 6.777089 million anchor rounds to 6.777 million; the ladder's coarser elicited median is 6.780 million, a 0.003 million difference representing negligible centering and print-grid rounding rather than a new substantive adjustment. Reporting incompleteness and variation across the three seasonal changes broaden the ladder, which implies final 80% bounds of 6.650 to 6.900 million."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: The persistence prior is March 2026 participation of 6.701661 million, with the historical sample consisting of the fetched 2023-2025 March-to-May changes. A formal time-series model is unsuitable because only three directly comparable March-to-May first-print changes were fetched and the latest observations are preliminary, making parameter estimates unstable. I add the median seasonal change of 0.075428 million and make no separate level adjustment because current weakness is embedded in March. The resulting 6.777089 million anchor rounds to 6.777 million; the ladder's coarser elicited median is 6.780 million, a 0.003 million difference representing negligible centering and print-grid rounding rather than a new substantive adjustment. Reporting incompleteness and variation across the three seasonal changes broaden the ladder, which implies final 80% bounds of 6.650 to 6.900 million."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["An upside risk is a stronger spring enrollment rebound, outreach effect, or delayed state reporting that would push participation toward or above 6.900 million. A downside risk is continued caseload attrition or incomplete first-print state submissions; an unusually broad decline would land below the interval at 6.650 million.","Review disposition: Accepted both requested fixes by explicitly ruling out a formal time-series model given the short preliminary sample and explaining the 0.003 million difference between the seasonal anchor and elicited median. Also accepted the suggestion to connect reporting and policy-mechanism uncertainty to the ladder width."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["May 2026 national WIC participation forecast","Prior/update/interval: The persistence prior is March 2026 participation of 6.701661 million, with the historical sample consisting of the fetched 2023-2025 March-to-May changes. A formal time-series model is unsuitable because only three directly comparable March-to-May first-print changes were fetched and the latest observations are preliminary, making parameter estimates unstable. I add the median seasonal change of 0.075428 million and make no separate level adjustment because current weakness is embedded in March. The resulting 6.777089 million anchor rounds to 6.777 million; the ladder's coarser elicited median is 6.780 million, a 0.003 million difference representing negligible centering and print-grid rounding rather than a new substantive adjustment. Reporting incompleteness and variation across the three seasonal changes broaden the ladder, which implies final 80% bounds of 6.650 to 6.900 million."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: wic-participation-may-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-08-14\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.wic-participation-may-2026.2026-07-10T22-06-15Z.wic-participation-may-2026-thesis-analyst-ladder-v2-2026-07-10t22-06-15z.470bf7bd56f031a0","runId":"run.wic-participation-may-2026.2026-07-10T22-06-15Z.wic-participation-may-2026-thesis-analyst-ladder-v2-2026-07-10t22-06-15z.470bf7bd56f031a0","predictionId":"wic-participation-may-2026","specId":"spec.wic-participation-may-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.51,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the fetched same-variant national total-participants observations range from 6.752 to 6.909 million, a 0.157 million span, with 6.829 million in November 2024 as the central level anchor. These are monthly total-participants prints, not annual WIC quality-control data or a smoothed series.","Prior/update/interval: the time-series model choice is a persistence prior centered near the 6.829 million reference-class level, using November 2024 6.829, October 2025 6.909, and November 2025 initial 6.752 million. I do not claim a May seasonal recovery from this evidence; 6.840 is a persistence-based judgment between the recent low print and prior level. The 6.75–6.95 ladder width reflects the observed 0.157 million range and the 0.157 million October-to-November first-print movement, with additional administrative first-print uncertainty."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 2 source-context item(s), activity log present.","evidence":["The resolver is the national WIC Total Participants series, calendar-month May 2026, using the first official print or the latest-month table that first includes May. The FNS WIC Data Tables page is the series table page; displayed person counts are converted to millions and rounded to 0.001 million.","Tool call: Checked the official FNS release-calendar entry for the May 2026 WIC monthly-program-data posting."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["USDA FNS WIC total participation: May 2026 first print","The resolver is the national WIC Total Participants series, calendar-month May 2026, using the first official print or the latest-month table that first includes May. The FNS WIC Data Tables page is the series table page; displayed person counts are converted to millions and rounded to 0.001 million."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.2, distribution present, forecast step count 1.","evidence":["Prior/update/interval: the time-series model choice is a persistence prior centered near the 6.829 million reference-class level, using November 2024 6.829, October 2025 6.909, and November 2025 initial 6.752 million. I do not claim a May seasonal recovery from this evidence; 6.840 is a persistence-based judgment between the recent low print and prior level. The 6.75–6.95 ladder width reflects the observed 0.157 million range and the 0.157 million October-to-November first-print movement, with additional administrative first-print uncertainty.","Upside risk: stronger enrollment or an unusually high state-reporting month could lift May above 6.95 million. Downside risk: continued enrollment attrition or unusually low state reporting could push it below 6.75 million. A broad administrative disruption or an unusually large reporting discontinuity would land outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: the time-series model choice is a persistence prior centered near the 6.829 million reference-class level, using November 2024 6.829, October 2025 6.909, and November 2025 initial 6.752 million. I do not claim a May seasonal recovery from this evidence; 6.840 is a persistence-based judgment between the recent low print and prior level. The 6.75–6.95 ladder width reflects the observed 0.157 million range and the 0.157 million October-to-November first-print movement, with additional administrative first-print uncertainty.","Upside risk: stronger enrollment or an unusually high state-reporting month could lift May above 6.95 million. Downside risk: continued enrollment attrition or unusually low state reporting could push it below 6.75 million. A broad administrative disruption or an unusually large reporting discontinuity would land outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: the time-series model choice is a persistence prior centered near the 6.829 million reference-class level, using November 2024 6.829, October 2025 6.909, and November 2025 initial 6.752 million. I do not claim a May seasonal recovery from this evidence; 6.840 is a persistence-based judgment between the recent low print and prior level. The 6.75–6.95 ladder width reflects the observed 0.157 million range and the 0.157 million October-to-November first-print movement, with additional administrative first-print uncertainty.","Upside risk: stronger enrollment or an unusually high state-reporting month could lift May above 6.95 million. Downside risk: continued enrollment attrition or unusually low state reporting could push it below 6.75 million. A broad administrative disruption or an unusually large reporting discontinuity would land outside the interval."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: wic-participation-may-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-08-14\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.wic-participation-may-2026.2026-07-10T22-25-53Z.wic-participation-may-2026-thesis-analyst-ladder-v2-2026-07-10t22-25-53z.f90d15da68676ef5","runId":"run.wic-participation-may-2026.2026-07-10T22-25-53Z.wic-participation-may-2026-thesis-analyst-ladder-v2-2026-07-10t22-25-53z.f90d15da68676ef5","predictionId":"wic-participation-may-2026","specId":"spec.wic-participation-may-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The reference class is the fetched May observations of 6.696739 million in 2023, 6.763710 million in 2024, and 6.894610 million in 2025, supplemented by June-November 2025 observations from 6.752138 to 6.923326 million. The base rate is gradual year-over-year growth with month-to-month noise.","Prior/update/interval: use a persistence-plus-trend prior centered near the latest 6.9 million level, informed by the three-year May reference class; update upward for the 2023-2025 May increase and recent 6.923326 million July observation, tempering it with November's 6.752138 million value, then widen for preliminary first-print noise. The threshold ladder implies an interval from 6.814 million to 7.055 million."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The target is the unadjusted national WIC Total Participants value for May 2026 in the first official FNS monthly table that includes that month. The resolver uses the displayed whole-person count converted to millions and rounded to 0.001; May 2025 is explicitly 6,894,610 participants.","Tool call: Fetch the official FNS WIC monthly national table for May 2023."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the unadjusted national WIC Total Participants value for May 2026 in the first official FNS monthly table that includes that month. The resolver uses the displayed whole-person count converted to millions and rounded to 0.001; May 2025 is explicitly 6,894,610 participants.","The official release-window contract places the first May 2026 print in the 2026-08-07 through 2026-08-15 window and sets resolutionDate to 2026-08-14; I retain that ledger date rather than inferring a date from cadence. The FNS table identifies FY 2026 observations as preliminary and subject to revision, while this target resolves only the first print."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.24, distribution present, forecast step count 1.","evidence":["Dispersion supports a broad first-print interval: the sample standard deviation of the three May observations is approximately 0.101 million, while the six June-November 2025 observations have standard deviation approximately 0.064 million. The ladder's 10th-to-90th span of 0.241 million is wider than ordinary recent monthly variation to account for preliminary reporting uncertainty and the limited seasonal sample.","Prior/update/interval: use a persistence-plus-trend prior centered near the latest 6.9 million level, informed by the three-year May reference class; update upward for the 2023-2025 May increase and recent 6.923326 million July observation, tempering it with November's 6.752138 million value, then widen for preliminary first-print noise. The threshold ladder implies an interval from 6.814 million to 7.055 million."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level and momentum point modestly higher: May participation rose from 6.696739 million to 6.763710 million to 6.894610 million across 2023-2025, and June-October 2025 clustered near 6.9 million. November's lower 6.752138 million observation tempers the update, but is outweighed by the repeated 6.883200-6.923326 million readings and the May seasonal reference class. No separate policy shock is assumed."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Dispersion supports a broad first-print interval: the sample standard deviation of the three May observations is approximately 0.101 million, while the six June-November 2025 observations have standard deviation approximately 0.064 million. The ladder's 10th-to-90th span of 0.241 million is wider than ordinary recent monthly variation to account for preliminary reporting uncertainty and the limited seasonal sample.","Level and momentum point modestly higher: May participation rose from 6.696739 million to 6.763710 million to 6.894610 million across 2023-2025, and June-October 2025 clustered near 6.9 million. November's lower 6.752138 million observation tempers the update, but is outweighed by the repeated 6.883200-6.923326 million readings and the May seasonal reference class. No separate policy shock is assumed."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: Fetch the latest official FNS monthly observations available before the forecast period.","Dispersion supports a broad first-print interval: the sample standard deviation of the three May observations is approximately 0.101 million, while the six June-November 2025 observations have standard deviation approximately 0.064 million. The ladder's 10th-to-90th span of 0.241 million is wider than ordinary recent monthly variation to account for preliminary reporting uncertainty and the limited seasonal sample."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: wic-participation-may-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-08-14\ntraceLineCount: 19\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-mts-deficit-july-2026.2026-07-10T05-28-45Z.a1b32c70119d0dda","runId":"run.us-mts-deficit-july-2026.2026-07-10T05-28-45Z.a1b32c70119d0dda","predictionId":"us-mts-deficit-july-2026","specId":"spec.us-mts-deficit-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: Opened the Bureau of the Fiscal Service Monthly Treasury Statement page and prior-issue archive.","Tool result: For July 2022, Table 1 comparable prior-year row in the July 2023 MTS reported receipts of 269,331 million, outlays of 480,383 million, and a deficit of 211,052 million; July 2025 Table 2 showed next-fiscal-year 2026 budget estimates of receipts 6,011,381 million, outlays 7,612,734 million, and deficit 1,601,353 million."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this is the first-print U.S. Treasury Monthly Treasury Statement Table 1 monthly deficit/surplus for July 2026, not fiscal-year-to-date deficit, receipts, outlays, refunds, or a revised vintage. The table is in $ millions; the forecast is in usd_billions with deficits positive.","Tool result: The official MTS page says the MTS is normally released on the 8th workday of the month following the reporting month; the page was last updated January 15, 2026, and Fiscal Service says the data moved to FiscalData on November 25, 2025."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this is the first-print U.S. Treasury Monthly Treasury Statement Table 1 monthly deficit/surplus for July 2026, not fiscal-year-to-date deficit, receipts, outlays, refunds, or a revised vintage. The table is in $ millions; the forecast is in usd_billions with deficits positive.","Tool result: The official MTS page says the MTS is normally released on the 8th workday of the month following the reporting month; the page was last updated January 15, 2026, and Fiscal Service says the data moved to FiscalData on November 25, 2025."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 91.4, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = July 2025 first-print deficit of 291.143; historical sample = July 2022-2025 first-print Table 1 monthly deficits of 211.052, 220.782, 243.741, 291.143; adjustment components = +18.961 from 40% of the 2024-to-2025 increase, -10.000 for continuing high customs/tariff receipts, +8.000 for higher benefit, health, defense, and interest outlays; point = 291.143 + 18.961 - 10.000 + 8.000 = 308.104. Interval method = sample standard deviation of the July deficit values themselves because this is a monthly flow and the target is a one-month level, while year-over-year changes would over-emphasize the short 2025 jump; sigma = 35.710, half-width = 1.28*sigma = 45.709, so 80% interval = 308.104 +/- 45.709 = 262.395 to 353.813.","Upside risk: the deficit would land above the interval if July outlays repeat another unusually large health, education, or interest timing surge while tariff receipts fade. Downside risk: it would land below the interval if customs receipts remain near or above the July 2025 surge and benefit or agency payments shift out of July. Outside the interval on either side would most likely come from payment-calendar timing rather than a smooth macro trend."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior = July 2025 first-print deficit of 291.143; historical sample = July 2022-2025 first-print Table 1 monthly deficits of 211.052, 220.782, 243.741, 291.143; adjustment components = +18.961 from 40% of the 2024-to-2025 increase, -10.000 for continuing high customs/tariff receipts, +8.000 for higher benefit, health, defense, and interest outlays; point = 291.143 + 18.961 - 10.000 + 8.000 = 308.104. Interval method = sample standard deviation of the July deficit values themselves because this is a monthly flow and the target is a one-month level, while year-over-year changes would over-emphasize the short 2025 jump; sigma = 35.710, half-width = 1.28*sigma = 45.709, so 80% interval = 308.104 +/- 45.709 = 262.395 to 353.813."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Reference class/base rate: the same-variant July first-print monthly deficits for 2022-2025 were 211.052, 220.782, 243.741, and 291.143 usd_billions. The four-year mean is 241.6795, but the last two observations and higher nominal outlay level argue for anchoring closer to 2025 than to the full mean.","Upside risk: the deficit would land above the interval if July outlays repeat another unusually large health, education, or interest timing surge while tariff receipts fade. Downside risk: it would land below the interval if customs receipts remain near or above the July 2025 surge and benefit or agency payments shift out of July. Outside the interval on either side would most likely come from payment-calendar timing rather than a smooth macro trend."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["US MTS July 2026 Monthly Deficit Forecast","Framing and exact resolver: this is the first-print U.S. Treasury Monthly Treasury Statement Table 1 monthly deficit/surplus for July 2026, not fiscal-year-to-date deficit, receipts, outlays, refunds, or a revised vintage. The table is in $ millions; the forecast is in usd_billions with deficits positive."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-mts-deficit-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-17\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-mts-deficit-july-2026.2026-07-10T15-18-30Z.us-mts-deficit-july-2026-thesis-analyst-fast-2026-07-10t15-18-30z.6b8aee5ffe84b83b","runId":"run.us-mts-deficit-july-2026.2026-07-10T15-18-30Z.us-mts-deficit-july-2026-thesis-analyst-fast-2026-07-10t15-18-30z.6b8aee5ffe84b83b","predictionId":"us-mts-deficit-july-2026","specId":"spec.us-mts-deficit-july-2026","runLabel":"Fast rollout 3 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["The target is the first official July 2026 MTS Table 1 monthly deficit print, not fiscal-year-to-date totals, receipts, outlays, or a revised historical value. Deficits are represented as positive usd_billions.","Tool call: Treasury MTS Table 1 July 2021 historical comparison"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["The target is the first official July 2026 MTS Table 1 monthly deficit print, not fiscal-year-to-date totals, receipts, outlays, or a revised historical value. Deficits are represented as positive usd_billions.","Tool call: Treasury MTS Table 1 July 2023 and July 2024 historical comparisons"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["The target is the first official July 2026 MTS Table 1 monthly deficit print, not fiscal-year-to-date totals, receipts, outlays, or a revised historical value. Deficits are represented as positive usd_billions.","The official Treasury MTS publication schedule and previous-issues record verify the target's August 17, 2026 resolution date; the series is Table 1 monthly Deficit/Surplus (-), with the first July 2026 print controlling."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 98, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior from the July 2021, 2023, 2024, and 2025 official MTS observations; update components are recent July level, recurring July outlay timing, higher nominal interest and mandatory spending, and receipts uncertainty. For this flow series, sample sigma from the four fetched July values is approximately $38.6 billion, so the 80% half-width is 1.28*sigma = approximately $49.4 billion. I widen modestly to about $49 billion and round to whole billions, giving bounds of $242 billion to $340 billion around the $291 billion point.","Point estimate: $291 billion. Interval calculation: sigma = $38.6 billion; 1.28*sigma = $49.4 billion; rounded 80% interval = [$242 billion, $340 billion]."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The base rate is the recent July reference class: deficits were $302.050 billion in 2021, $220.782 billion in 2023, $243.741 billion in 2024, and $291.143 billion in 2025. The modal forecast leans toward the latest two observations because nominal outlays and interest costs remain elevated."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence prior from the July 2021, 2023, 2024, and 2025 official MTS observations; update components are recent July level, recurring July outlay timing, higher nominal interest and mandatory spending, and receipts uncertainty. For this flow series, sample sigma from the four fetched July values is approximately $38.6 billion, so the 80% half-width is 1.28*sigma = approximately $49.4 billion. I widen modestly to about $49 billion and round to whole billions, giving bounds of $242 billion to $340 billion around the $291 billion point.","Upside risk is a large July outlay concentration or weaker-than-expected receipts, which would land above the interval. Downside risk is unusually strong receipts or delayed outlays, which would land below the interval. A major policy or accounting-timing shock would be outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The base rate is the recent July reference class: deficits were $302.050 billion in 2021, $220.782 billion in 2023, $243.741 billion in 2024, and $291.143 billion in 2025. The modal forecast leans toward the latest two observations because nominal outlays and interest costs remain elevated.","Prior/update/interval: persistence prior from the July 2021, 2023, 2024, and 2025 official MTS observations; update components are recent July level, recurring July outlay timing, higher nominal interest and mandatory spending, and receipts uncertainty. For this flow series, sample sigma from the four fetched July values is approximately $38.6 billion, so the 80% half-width is 1.28*sigma = approximately $49.4 billion. I widen modestly to about $49 billion and round to whole billions, giving bounds of $242 billion to $340 billion around the $291 billion point."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-mts-deficit-july-2026\nrunLabel: Fast rollout 3 of 3\nresolutionDate: 2026-08-17\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: resolution clarity (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-mts-deficit-july-2026.2026-07-10T15-39-07Z.us-mts-deficit-july-2026-thesis-analyst-fast-2026-07-10t15-39-07z.46157fe813aa795c","runId":"run.us-mts-deficit-july-2026.2026-07-10T15-39-07Z.us-mts-deficit-july-2026-thesis-analyst-fast-2026-07-10t15-39-07z.46157fe813aa795c","predictionId":"us-mts-deficit-july-2026","specId":"spec.us-mts-deficit-july-2026","runLabel":"Fast rollout 1 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: Fetched Treasury Monthly Treasury Statement Table 1 historical July observations from the July 2024 published statement.","The reference class is same-calendar-month Table 1 deficits: July 2022, 2023, 2024, and 2025 were $219.596bn, $220.782bn, $243.741bn, and $291.143bn respectively. This seasonally matched base rate is preferable to comparing July with April's tax-season surplus or the latest May flow."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The target is Table 1, “Deficit/Surplus (-),” for the July 2026 monthly flow, not fiscal-year-to-date receipts or outlays. Table 1 reports $ millions; I convert to billions and reverse its presentation convention so a deficit is positive. The resolver is the original first print only.","Tool call: Fetched Treasury Monthly Treasury Statement Table 1 historical July observations from the July 2024 published statement."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is Table 1, “Deficit/Surplus (-),” for the July 2026 monthly flow, not fiscal-year-to-date receipts or outlays. Table 1 reports $ millions; I convert to billions and reverse its presentation convention so a deficit is positive. The resolver is the original first print only.","Tool call: Fetched Treasury Monthly Treasury Statement Table 1 historical July observations from the July 2024 published statement."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 86, distribution present, forecast step count 1.","evidence":["Prior/update/interval: The persistence-plus-seasonal model uses the four July Table 1 values ($219.596bn, $220.782bn, $243.741bn, $291.143bn) as the historical sample; their mean is $243.816bn and sample sigma = $33.5bn. The unadjusted 80% half-width is 1.28*33.5 = $42.9bn. I update the point by about $36bn for the recent higher July level and the balance of higher nominal outlays versus stronger receipts, giving $280bn; the interval is $280bn ± $43bn = [$237bn, $323bn], with no additional regime widening.","upside risk: unexpectedly large benefit, interest, or payment-timing outlays would produce a larger deficit and could land above the interval. downside risk: exceptionally strong July receipts, including customs or tax payments, would reduce the deficit and could land below the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["upside risk: unexpectedly large benefit, interest, or payment-timing outlays would produce a larger deficit and could land above the interval. downside risk: exceptionally strong July receipts, including customs or tax payments, would reduce the deficit and could land below the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["July 2026 Monthly Treasury Statement deficit forecast","Prior/update/interval: The persistence-plus-seasonal model uses the four July Table 1 values ($219.596bn, $220.782bn, $243.741bn, $291.143bn) as the historical sample; their mean is $243.816bn and sample sigma = $33.5bn. The unadjusted 80% half-width is 1.28*33.5 = $42.9bn. I update the point by about $36bn for the recent higher July level and the balance of higher nominal outlays versus stronger receipts, giving $280bn; the interval is $280bn ± $43bn = [$237bn, $323bn], with no additional regime widening."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-mts-deficit-july-2026\nrunLabel: Fast rollout 1 of 3\nresolutionDate: 2026-08-17\ntraceLineCount: 13\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-mts-deficit-july-2026.2026-07-10T15-43-21Z.us-mts-deficit-july-2026-thesis-analyst-fast-2026-07-10t15-43-21z.d2baaecf374bc1ab","runId":"run.us-mts-deficit-july-2026.2026-07-10T15-43-21Z.us-mts-deficit-july-2026-thesis-analyst-fast-2026-07-10t15-43-21z.d2baaecf374bc1ab","predictionId":"us-mts-deficit-july-2026","specId":"spec.us-mts-deficit-july-2026","runLabel":"Fast rollout 2 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["The target is the first-print July 2026 monthly Table 1 Deficit/Surplus (-), not fiscal-year-to-date receipts, outlays, refunds, or a revised historical value. Treasury Table 1 reports $ millions; I convert its deficit sign convention to positive usd_billions by dividing by 1,000. The official release-calendar lookup identifies August 17, 2026 as the scheduled release for the July 2026 statement.","Base rate/reference class: recent first-print July Table 1 deficits were 220.779 billion in 2023, 243.741 billion in 2024, and 291.143 billion in 2025. This is a monthly cash-flow series, so the comparison uses July monthly values from the same Table 1 variant rather than seasonally adjusted series or fiscal-year-to-date totals."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The target is the first-print July 2026 monthly Table 1 Deficit/Surplus (-), not fiscal-year-to-date receipts, outlays, refunds, or a revised historical value. Treasury Table 1 reports $ millions; I convert its deficit sign convention to positive usd_billions by dividing by 1,000. The official release-calendar lookup identifies August 17, 2026 as the scheduled release for the July 2026 statement.","Tool result: The official schedule lists the statement release at 2:00 p.m. and, for the analogous July 2024 accounting month, gives August 12, 2024; the MTS methodology states the normal convention is the 8th workday following month-end."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the first-print July 2026 monthly Table 1 Deficit/Surplus (-), not fiscal-year-to-date receipts, outlays, refunds, or a revised historical value. Treasury Table 1 reports $ millions; I convert its deficit sign convention to positive usd_billions by dividing by 1,000. The official release-calendar lookup identifies August 17, 2026 as the scheduled release for the July 2026 statement.","Tool call: Fetched Treasury MTS July 2024 report to obtain a same-variant July first-print comparison."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 94, distribution present, forecast step count 1.","evidence":["Prior/update/interval: I use the 2021-25 July Table 1 deficit reference class (302.0, 211.0, 220.779, 243.741, 291.143 billion) with a level prior of 253.7 billion. For this flow series, sigma is the population standard deviation of the fetched July values: sigma = 36.7 billion; 1.28*sigma = 47.0 billion. I add about 41.3 billion for the recent higher July outlay level, partly offset by stronger customs-duty receipts, yielding 295.0 billion and an 80% interval of 248.0 to 342.0 billion; the half-width is 1.00x the dispersion-based half-width.","The central adjustment reflects the 2025 July deficit of 291.143 billion and elevated recurring outlays. Upside risk is a larger deficit if benefit, health, defense, or interest payments are accelerated into July; downside risk is unusually strong tax or customs collections. A payment-timing shift or a large receipt spike would land outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: I use the 2021-25 July Table 1 deficit reference class (302.0, 211.0, 220.779, 243.741, 291.143 billion) with a level prior of 253.7 billion. For this flow series, sigma is the population standard deviation of the fetched July values: sigma = 36.7 billion; 1.28*sigma = 47.0 billion. I add about 41.3 billion for the recent higher July outlay level, partly offset by stronger customs-duty receipts, yielding 295.0 billion and an 80% interval of 248.0 to 342.0 billion; the half-width is 1.00x the dispersion-based half-width.","The central adjustment reflects the 2025 July deficit of 291.143 billion and elevated recurring outlays. Upside risk is a larger deficit if benefit, health, defense, or interest payments are accelerated into July; downside risk is unusually strong tax or customs collections. A payment-timing shift or a large receipt spike would land outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: I use the 2021-25 July Table 1 deficit reference class (302.0, 211.0, 220.779, 243.741, 291.143 billion) with a level prior of 253.7 billion. For this flow series, sigma is the population standard deviation of the fetched July values: sigma = 36.7 billion; 1.28*sigma = 47.0 billion. I add about 41.3 billion for the recent higher July outlay level, partly offset by stronger customs-duty receipts, yielding 295.0 billion and an 80% interval of 248.0 to 342.0 billion; the half-width is 1.00x the dispersion-based half-width.","The central adjustment reflects the 2025 July deficit of 291.143 billion and elevated recurring outlays. Upside risk is a larger deficit if benefit, health, defense, or interest payments are accelerated into July; downside risk is unusually strong tax or customs collections. A payment-timing shift or a large receipt spike would land outside the interval."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-mts-deficit-july-2026\nrunLabel: Fast rollout 2 of 3\nresolutionDate: 2026-08-17\ntraceLineCount: 12\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-mts-deficit-july-2026.2026-07-10T15-47-25Z.us-mts-deficit-july-2026-thesis-analyst-fast-2026-07-10t15-47-25z.4dbb50509b15ba26","runId":"run.us-mts-deficit-july-2026.2026-07-10T15-47-25Z.us-mts-deficit-july-2026-thesis-analyst-fast-2026-07-10t15-47-25z.4dbb50509b15ba26","predictionId":"us-mts-deficit-july-2026","specId":"spec.us-mts-deficit-july-2026","runLabel":"Fast rollout 3 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.51,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["The base rate/reference class is the same July Table 1 monthly deficit: 211.052, 220.782, 243.741, and 291.000 usd_billions for FY2022–FY2025. The FY2025 $291 billion reading is the most relevant persistence anchor, while the earlier same-month values retain July seasonality.","Prior/update/interval: The model is a same-month seasonal persistence prior using FY2022–FY2025 July Table 1 deficits [211.052, 220.782, 243.741, 291.000]. Their mean is 241.644 and sample sigma = 35.644 usd_billions; 1.28*sigma = 45.624. I update the FY2025 persistence anchor upward for higher interest/program outlays, partly offset by tariff and tax receipts, to 305.0; the resulting 80% bounds are 305.0 ± 45.6 = [259.4, 350.6]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The target is the original first-print July 2026 value in MTS Table 1, “Deficit/Surplus (-),” reported in $ millions and divided by 1,000; deficits are expressed as positive usd_billions here. The Table 1 monthly variant, rather than fiscal-year-to-date receipts, outlays, or a revised table, is the sole target.","Tool call: Fetched Treasury MTS Table 1 July observations from the FY2022/FY2023 statement."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the original first-print July 2026 value in MTS Table 1, “Deficit/Surplus (-),” reported in $ millions and divided by 1,000; deficits are expressed as positive usd_billions here. The Table 1 monthly variant, rather than fiscal-year-to-date receipts, outlays, or a revised table, is the sole target.","Tool result: Treasury states that the MTS is normally released on the 8th workday after the reporting month; its June 2025 Table 1 reports receipts of $526,445 million, outlays of $499,435 million, and a $27,010 million surplus."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 91.2, distribution present, forecast step count 1.","evidence":["Prior/update/interval: The model is a same-month seasonal persistence prior using FY2022–FY2025 July Table 1 deficits [211.052, 220.782, 243.741, 291.000]. Their mean is 241.644 and sample sigma = 35.644 usd_billions; 1.28*sigma = 45.624. I update the FY2025 persistence anchor upward for higher interest/program outlays, partly offset by tariff and tax receipts, to 305.0; the resulting 80% bounds are 305.0 ± 45.6 = [259.4, 350.6].","Upside risk: a larger-than-assumed outlay acceleration or payment shift into July would land above the interval. Downside risk: stronger receipts, including tariff collections, or delayed outlays would land below the interval. A major one-off refund, benefit-payment, or accounting-timing shift is the principal outside the interval scenario."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: The model is a same-month seasonal persistence prior using FY2022–FY2025 July Table 1 deficits [211.052, 220.782, 243.741, 291.000]. Their mean is 241.644 and sample sigma = 35.644 usd_billions; 1.28*sigma = 45.624. I update the FY2025 persistence anchor upward for higher interest/program outlays, partly offset by tariff and tax receipts, to 305.0; the resulting 80% bounds are 305.0 ± 45.6 = [259.4, 350.6].","Upside risk: a larger-than-assumed outlay acceleration or payment shift into July would land above the interval. Downside risk: stronger receipts, including tariff collections, or delayed outlays would land below the interval. A major one-off refund, benefit-payment, or accounting-timing shift is the principal outside the interval scenario."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["July 2026 Treasury monthly deficit forecast","Prior/update/interval: The model is a same-month seasonal persistence prior using FY2022–FY2025 July Table 1 deficits [211.052, 220.782, 243.741, 291.000]. Their mean is 241.644 and sample sigma = 35.644 usd_billions; 1.28*sigma = 45.624. I update the FY2025 persistence anchor upward for higher interest/program outlays, partly offset by tariff and tax receipts, to 305.0; the resulting 80% bounds are 305.0 ± 45.6 = [259.4, 350.6]."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-mts-deficit-july-2026\nrunLabel: Fast rollout 3 of 3\nresolutionDate: 2026-08-17\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-mts-deficit-july-2026.2026-07-10T15-48-42Z.us-mts-deficit-july-2026-thesis-analyst-median3-2026-07-10t15-48-42z.044694690c12d2be","runId":"run.us-mts-deficit-july-2026.2026-07-10T15-48-42Z.us-mts-deficit-july-2026-thesis-analyst-median3-2026-07-10t15-48-42z.044694690c12d2be","predictionId":"us-mts-deficit-july-2026","specId":"spec.us-mts-deficit-july-2026","runLabel":"Median of 3 rollouts","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and implicit outside-view language.","evidence":["Median-of-3 rollout ensemble","Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T15:39:07Z, 2026-07-10T15:43:21Z, 2026-07-10T15:47:25Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 8 source-context item(s), activity log present.","evidence":["Median CDF quantiles: q10 = 247.7, q50 = 295.0, q90 = 342.4. Constituent points [280, 295, 305] with 80% widths [86, 94, 91.2]; the median interval inherits the central rollout mass rather than averaging tails."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 94.7, distribution present, forecast step count 1.","evidence":["Median CDF quantiles: q10 = 247.7, q50 = 295.0, q90 = 342.4. Constituent points [280, 295, 305] with 80% widths [86, 94, 91.2]; the median interval inherits the central rollout mass rather than averaging tails.","Forecast: point 295, 80% interval [247.7, 342.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T15:39:07Z, 2026-07-10T15:43:21Z, 2026-07-10T15:47:25Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T15:39:07Z, 2026-07-10T15:43:21Z, 2026-07-10T15:47:25Z. Drivers and resolver fields mirror the rollout closest to the median.","Tool result: {rollout_points: [280, 295, 305], rollout_widths: [86, 94, 91.2], q10: 247.7, q50: 295.0, q90: 342.4}"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-mts-deficit-july-2026\nrunLabel: Median of 3 rollouts\nresolutionDate: 2026-08-17\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-mts-deficit-july-2026.2026-07-10T16-13-11Z.us-mts-deficit-july-2026-thesis-analyst-ladder-2026-07-10t16-13-11z.d2f182bdd83fc531","runId":"run.us-mts-deficit-july-2026.2026-07-10T16-13-11Z.us-mts-deficit-july-2026-thesis-analyst-ladder-2026-07-10t16-13-11z.d2f182bdd83fc531","predictionId":"us-mts-deficit-july-2026","specId":"spec.us-mts-deficit-july-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Framing and exact resolver: this is the U.S. Treasury Monthly Treasury Statement Table 1 monthly Deficit/Surplus (-), not fiscal-year-to-date deficit, receipts, outlays, refunds, or a revised historical table. The target is first print for July 2026, in $ millions divided by 1000 into usd_billions, with deficits reported positive.","Reference class and base rate: the same-month July deficits immediately before this target were about 221, 244, and 292.8 usd_billions. The base rate is a large July deficit near the high-200s, with a positive trend from debt service and entitlement COLA outlays partly offset by customs receipts."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this is the U.S. Treasury Monthly Treasury Statement Table 1 monthly Deficit/Surplus (-), not fiscal-year-to-date deficit, receipts, outlays, refunds, or a revised historical table. The target is first print for July 2026, in $ millions divided by 1000 into usd_billions, with deficits reported positive.","Tool call: Checked Bureau of the Fiscal Service Monthly Treasury Statement page and FiscalData MTS dataset landing path for the official resolver and table family."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this is the U.S. Treasury Monthly Treasury Statement Table 1 monthly Deficit/Surplus (-), not fiscal-year-to-date deficit, receipts, outlays, refunds, or a revised historical table. The target is first print for July 2026, in $ millions divided by 1000 into usd_billions, with deficits reported positive.","Tool call: Checked official release-calendar target date for the July 2026 MTS first print."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 190, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior and time-series model prior is July 2025 implied 292.8 from the same MTS monthly-deficit reference class; no separate fitted model was used because only same-month July observations were used. Historical sample is July deficits 221, 244, and 292.8, so sigma = 36.7 from the values themselves for this flow series; 1.28*sigma = 47.0. Adjustment components sum to about +26.3 from 292.8 to 319.1: +15 for underlying outlay and interest growth, +10 for tax-law/revenue softness, +0 to -10 for tariff/customs offset, and +0 to +10 for first-print timing noise. The ladder-implied 80% interval is 240 to 430, average half-width about 95, roughly 2.0 times 1.28*sigma; I widened beyond the raw three-July dispersion because the 2026 policy, tariff, debt-service, and appropriations regime is not well represented by only three same-month observations.","Counter-considerations: upside risk for a larger deficit would be a weak July receipts print, faster net-interest accrual, or front-loaded benefit and defense outlays; a deficit above 430 would land above the interval. Downside risk would be another customs-revenue surge, delayed outlays, or unexpectedly strong nonwithheld tax receipts; a deficit below 240 would land outside the interval on the low side."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior and time-series model prior is July 2025 implied 292.8 from the same MTS monthly-deficit reference class; no separate fitted model was used because only same-month July observations were used. Historical sample is July deficits 221, 244, and 292.8, so sigma = 36.7 from the values themselves for this flow series; 1.28*sigma = 47.0. Adjustment components sum to about +26.3 from 292.8 to 319.1: +15 for underlying outlay and interest growth, +10 for tax-law/revenue softness, +0 to -10 for tariff/customs offset, and +0 to +10 for first-print timing noise. The ladder-implied 80% interval is 240 to 430, average half-width about 95, roughly 2.0 times 1.28*sigma; I widened beyond the raw three-July dispersion because the 2026 policy, tariff, debt-service, and appropriations regime is not well represented by only three same-month observations."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Reference class and base rate: the same-month July deficits immediately before this target were about 221, 244, and 292.8 usd_billions. The base rate is a large July deficit near the high-200s, with a positive trend from debt service and entitlement COLA outlays partly offset by customs receipts.","Prior/update/interval: persistence prior and time-series model prior is July 2025 implied 292.8 from the same MTS monthly-deficit reference class; no separate fitted model was used because only same-month July observations were used. Historical sample is July deficits 221, 244, and 292.8, so sigma = 36.7 from the values themselves for this flow series; 1.28*sigma = 47.0. Adjustment components sum to about +26.3 from 292.8 to 319.1: +15 for underlying outlay and interest growth, +10 for tax-law/revenue softness, +0 to -10 for tariff/customs offset, and +0 to +10 for first-print timing noise. The ladder-implied 80% interval is 240 to 430, average half-width about 95, roughly 2.0 times 1.28*sigma; I widened beyond the raw three-July dispersion because the 2026 policy, tariff, debt-service, and appropriations regime is not well represented by only three same-month observations."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for July 2026 Monthly Treasury Statement deficit","Prior/update/interval: persistence prior and time-series model prior is July 2025 implied 292.8 from the same MTS monthly-deficit reference class; no separate fitted model was used because only same-month July observations were used. Historical sample is July deficits 221, 244, and 292.8, so sigma = 36.7 from the values themselves for this flow series; 1.28*sigma = 47.0. Adjustment components sum to about +26.3 from 292.8 to 319.1: +15 for underlying outlay and interest growth, +10 for tax-law/revenue softness, +0 to -10 for tariff/customs offset, and +0 to +10 for first-print timing noise. The ladder-implied 80% interval is 240 to 430, average half-width about 95, roughly 2.0 times 1.28*sigma; I widened beyond the raw three-July dispersion because the 2026 policy, tariff, debt-service, and appropriations regime is not well represented by only three same-month observations."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-mts-deficit-july-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-08-17\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-mts-deficit-july-2026.2026-07-10T16-25-49Z.us-mts-deficit-july-2026-thesis-analyst-fast-2026-07-10t16-25-49z.276f311f3ff3ebb1","runId":"run.us-mts-deficit-july-2026.2026-07-10T16-25-49Z.us-mts-deficit-july-2026-thesis-analyst-fast-2026-07-10t16-25-49z.276f311f3ff3ebb1","predictionId":"us-mts-deficit-july-2026","specId":"spec.us-mts-deficit-july-2026","runLabel":"Fast rollout 1 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: Fetched the prior-year July comparison used to extend the July reference class.","Tool result: The July 2024 deficit of 244 usd_billions was reported as 10% above the prior year, implying July 2023 deficit = 244 / 1.10 = 221.8 usd_billions."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this is the U.S. Treasury FiscalData Monthly Treasury Statement Table 1 current-month Deficit/Surplus (-) for July 2026, first print only. The source table reports dollars in millions; this forecast reports usd_billions with deficits positive and surpluses negative.","Tool result: July 2024 deficit was 244 usd_billions with receipts 330 and outlays 574; July 2025 deficit was reported up 20% year over year, implying 292.8 usd_billions; customs revenue in July 2025 rose by 21 usd_billions and 273% year over year."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this is the U.S. Treasury FiscalData Monthly Treasury Statement Table 1 current-month Deficit/Surplus (-) for July 2026, first print only. The source table reports dollars in millions; this forecast reports usd_billions with deficits positive and surpluses negative.","Tool call: Checked the FiscalData Monthly Treasury Statement series page and the registered MTS release contract for July 2026 Table 1."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 106, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is latest July deficit 292.8 from the 2023-2025 July historical sample, adjusted by +22 for higher net interest and benefit outlays, +15 for broader FY2026 deficit pressure, and -5 for tariff/customs revenue offset, giving 292.8 + 22 + 15 - 5 = 324.8, rounded to 325. For this flow series, size the 80% interval from realized dispersion of the July values themselves: sigma = sample sd(221.8, 244.0, 292.8) = 36.3, so 1.28*sigma = 46.5. I modestly widen to 53 because tariff timing, war-related spending, and first-print month-end payment timing add release-specific uncertainty; 325 +/- 53 gives 272 to 378.","Upside risk: a larger July deficit would land above the interval if defense/emergency outlays or interest payments jump sharply, refunds run high, or tariff collections disappoint. Downside risk: a deficit below the interval would require unusually strong non-withheld receipts, customs revenue materially above recent run-rate, or delayed benefit/vendor payments. A surplus or sub-200 usd_billions deficit would be outside the interval and would imply a July seasonal pattern unlike the recent reference class."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior is latest July deficit 292.8 from the 2023-2025 July historical sample, adjusted by +22 for higher net interest and benefit outlays, +15 for broader FY2026 deficit pressure, and -5 for tariff/customs revenue offset, giving 292.8 + 22 + 15 - 5 = 324.8, rounded to 325. For this flow series, size the 80% interval from realized dispersion of the July values themselves: sigma = sample sd(221.8, 244.0, 292.8) = 36.3, so 1.28*sigma = 46.5. I modestly widen to 53 because tariff timing, war-related spending, and first-print month-end payment timing add release-specific uncertainty; 325 +/- 53 gives 272 to 378."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence prior is latest July deficit 292.8 from the 2023-2025 July historical sample, adjusted by +22 for higher net interest and benefit outlays, +15 for broader FY2026 deficit pressure, and -5 for tariff/customs revenue offset, giving 292.8 + 22 + 15 - 5 = 324.8, rounded to 325. For this flow series, size the 80% interval from realized dispersion of the July values themselves: sigma = sample sd(221.8, 244.0, 292.8) = 36.3, so 1.28*sigma = 46.5. I modestly widen to 53 because tariff timing, war-related spending, and first-print month-end payment timing add release-specific uncertainty; 325 +/- 53 gives 272 to 378.","Upside risk: a larger July deficit would land above the interval if defense/emergency outlays or interest payments jump sharply, refunds run high, or tariff collections disappoint. Downside risk: a deficit below the interval would require unusually strong non-withheld receipts, customs revenue materially above recent run-rate, or delayed benefit/vendor payments. A surplus or sub-200 usd_billions deficit would be outside the interval and would imply a July seasonal pattern unlike the recent reference class."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for U.S. Monthly Treasury Statement July 2026 deficit","Framing and exact resolver: this is the U.S. Treasury FiscalData Monthly Treasury Statement Table 1 current-month Deficit/Surplus (-) for July 2026, first print only. The source table reports dollars in millions; this forecast reports usd_billions with deficits positive and surpluses negative."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-mts-deficit-july-2026\nrunLabel: Fast rollout 1 of 3\nresolutionDate: 2026-08-17\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-mts-deficit-july-2026.2026-07-10T16-48-40Z.us-mts-deficit-july-2026-thesis-analyst-fast-2026-07-10t16-48-40z.da1686c6051cd283","runId":"run.us-mts-deficit-july-2026.2026-07-10T16-48-40Z.us-mts-deficit-july-2026-thesis-analyst-fast-2026-07-10t16-48-40z.da1686c6051cd283","predictionId":"us-mts-deficit-july-2026","specId":"spec.us-mts-deficit-july-2026","runLabel":"Fast rollout 3 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Framing and exact resolver: this targets the first official U.S. Treasury Monthly Treasury Statement Table 1 monthly Deficit/Surplus (-) for July 2026, not fiscal-year-to-date deficit, receipts alone, outlays alone, or later revised historical tables. The table reports $ millions; I convert to usd_billions and keep deficits positive. The ledger URL is the broader MTS dataset page, while the more specific stable Fiscal Data table page used here is the Summary of Receipts, Outlays, and Deficit/Surplus table. The official release-calendar contract for this run shows the July 2026 MTS first print on 2026-08-17.","Base rate/reference class: the same-variant July MTS Table 1 flow values from 2019-2025 average 207.4 usd_billions, but the post-2021 July values cluster much higher: 211.1, 220.8, 243.7, and 291.2. I put more weight on the latest July print because nominal outlays, interest costs, and the annual deficit level are materially above the 2019-2020 regime."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this targets the first official U.S. Treasury Monthly Treasury Statement Table 1 monthly Deficit/Surplus (-) for July 2026, not fiscal-year-to-date deficit, receipts alone, outlays alone, or later revised historical tables. The table reports $ millions; I convert to usd_billions and keep deficits positive. The ledger URL is the broader MTS dataset page, while the more specific stable Fiscal Data table page used here is the Summary of Receipts, Outlays, and Deficit/Surplus table. The official release-calendar contract for this run shows the July 2026 MTS first print on 2026-08-17.","Tool result: Fetched/rounded July monthly deficits: 2025-07 deficit 291.2 usd_billions, 2024-07 deficit 243.7 usd_billions, 2023-07 deficit 220.8 usd_billions; 2024 July receipts were about 330.4 and outlays about 574.1 usd_billions."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this targets the first official U.S. Treasury Monthly Treasury Statement Table 1 monthly Deficit/Surplus (-) for July 2026, not fiscal-year-to-date deficit, receipts alone, outlays alone, or later revised historical tables. The table reports $ millions; I convert to usd_billions and keep deficits positive. The ledger URL is the broader MTS dataset page, while the more specific stable Fiscal Data table page used here is the Summary of Receipts, Outlays, and Deficit/Surplus table. The official release-calendar contract for this run shows the July 2026 MTS first print on 2026-08-17.","Prior/update/interval: persistence prior is 2025-07 first-print deficit of 291.2. Historical sample is July MTS Table 1 monthly deficits for 2019-2025: 119.7, 63.0, 302.0, 211.1, 220.8, 243.7, 291.2. Adjustment components are +20.0 for structural outlay and net-interest drift, -10.0 for elevated customs/tariff receipts, +15.0 for defense/emergency/policy spending pressure, and +8.0 for ordinary July payment-timing skew, giving point = 291.2 + 20.0 - 10.0 + 15.0 + 8.0 = 324.2. For this flow series, sigma = 86.8 from the fetched July values themselves, so the 80 percent half-width is about 1.28*sigma = 111.1; interval = 324.2 +/- 111.1 = [213.1, 435.3]."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 222.2, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is 2025-07 first-print deficit of 291.2. Historical sample is July MTS Table 1 monthly deficits for 2019-2025: 119.7, 63.0, 302.0, 211.1, 220.8, 243.7, 291.2. Adjustment components are +20.0 for structural outlay and net-interest drift, -10.0 for elevated customs/tariff receipts, +15.0 for defense/emergency/policy spending pressure, and +8.0 for ordinary July payment-timing skew, giving point = 291.2 + 20.0 - 10.0 + 15.0 + 8.0 = 324.2. For this flow series, sigma = 86.8 from the fetched July values themselves, so the 80 percent half-width is about 1.28*sigma = 111.1; interval = 324.2 +/- 111.1 = [213.1, 435.3].","Counter-considerations: upside risk is a larger deficit if July benefit, defense, disaster, or interest outlays bunch into the month while tariff receipts fade, which would land above the interval if the deficit exceeds 435.3. Downside risk is stronger-than-expected withheld/income/customs receipts or delayed spending, which would land below the interval if the deficit is under 213.1. A shutdown-style or debt-management timing distortion is the main outside the interval scenario."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate/reference class: the same-variant July MTS Table 1 flow values from 2019-2025 average 207.4 usd_billions, but the post-2021 July values cluster much higher: 211.1, 220.8, 243.7, and 291.2. I put more weight on the latest July print because nominal outlays, interest costs, and the annual deficit level are materially above the 2019-2020 regime.","Prior/update/interval: persistence prior is 2025-07 first-print deficit of 291.2. Historical sample is July MTS Table 1 monthly deficits for 2019-2025: 119.7, 63.0, 302.0, 211.1, 220.8, 243.7, 291.2. Adjustment components are +20.0 for structural outlay and net-interest drift, -10.0 for elevated customs/tariff receipts, +15.0 for defense/emergency/policy spending pressure, and +8.0 for ordinary July payment-timing skew, giving point = 291.2 + 20.0 - 10.0 + 15.0 + 8.0 = 324.2. For this flow series, sigma = 86.8 from the fetched July values themselves, so the 80 percent half-width is about 1.28*sigma = 111.1; interval = 324.2 +/- 111.1 = [213.1, 435.3]."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: the same-variant July MTS Table 1 flow values from 2019-2025 average 207.4 usd_billions, but the post-2021 July values cluster much higher: 211.1, 220.8, 243.7, and 291.2. I put more weight on the latest July print because nominal outlays, interest costs, and the annual deficit level are materially above the 2019-2020 regime.","Counter-considerations: upside risk is a larger deficit if July benefit, defense, disaster, or interest outlays bunch into the month while tariff receipts fade, which would land above the interval if the deficit exceeds 435.3. Downside risk is stronger-than-expected withheld/income/customs receipts or delayed spending, which would land below the interval if the deficit is under 213.1. A shutdown-style or debt-management timing distortion is the main outside the interval scenario."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["U.S. MTS July 2026 Deficit Forecast","Prior/update/interval: persistence prior is 2025-07 first-print deficit of 291.2. Historical sample is July MTS Table 1 monthly deficits for 2019-2025: 119.7, 63.0, 302.0, 211.1, 220.8, 243.7, 291.2. Adjustment components are +20.0 for structural outlay and net-interest drift, -10.0 for elevated customs/tariff receipts, +15.0 for defense/emergency/policy spending pressure, and +8.0 for ordinary July payment-timing skew, giving point = 291.2 + 20.0 - 10.0 + 15.0 + 8.0 = 324.2. For this flow series, sigma = 86.8 from the fetched July values themselves, so the 80 percent half-width is about 1.28*sigma = 111.1; interval = 324.2 +/- 111.1 = [213.1, 435.3]."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-mts-deficit-july-2026\nrunLabel: Fast rollout 3 of 3\nresolutionDate: 2026-08-17\ntraceLineCount: 12\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-mts-deficit-july-2026.2026-07-10T17-12-40Z.us-mts-deficit-july-2026-thesis-analyst-ladder-2026-07-10t17-12-40z.b29d327e2a34a979","runId":"run.us-mts-deficit-july-2026.2026-07-10T17-12-40Z.us-mts-deficit-july-2026-thesis-analyst-ladder-2026-07-10t17-12-40z.b29d327e2a34a979","predictionId":"us-mts-deficit-july-2026","specId":"spec.us-mts-deficit-july-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: Inspect Treasury MTS Table 1 historical monthly results for FY2022 and FY2023.","The reference class is the four same-month July observations for 2022-2025: 211.052, 220.782, 243.741, and 291.143 billion. Their base-rate mean is 241.680 billion, while persistence favors the latest observation because the nominal series has risen in each sampled year."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The target is the first official July 2026 print in MTS Table 1, monthly Deficit/Surplus (-), not fiscal-year-to-date results or financing. Table 1 reports millions of dollars; divide by 1000 and reverse its sign convention so deficits are positive. The resolver allows no correction grace period.","Tool result: Official Table 1 reports July deficits of $211,052 million in 2022 and $220,782 million in 2023."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the first official July 2026 print in MTS Table 1, monthly Deficit/Surplus (-), not fiscal-year-to-date results or financing. Table 1 reports millions of dollars; divide by 1000 and reverse its sign convention so deficits are positive. The resolver allows no correction grace period.","Tool call: Inspect the Treasury MTS series for the July 2025 first print and monthly components."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 118.75, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence model prior = 291.143 billion from July 2025; historical sample = July 2022-2025; adjustment components = no quantified net update because current component measurements and a calendar shift were not verified, so the ladder median is 290. Persistence errors proxied by the three realized year-over-year changes are 9.730, 22.959, and 47.402; sigma = RMSE = sqrt((9.730^2 + 22.959^2 + 47.402^2)/3) = 30.92 billion, and 1.28*sigma = 39.58 billion. Multiplying that half-width by 1.50 for the sparse three-error sample and unresolved payment-timing and policy regime risk gives 59.37 billion. Applied around the approximately 290.6 ladder center, this produces about 231.25 to 350.00; the ladder-implied average half-width is 59.38 billion, essentially equal to the scenario calculation.","Upside risk comes from benefit-payment timing, unexpectedly high interest or defense outlays, or weak receipts; a shock exceeding roughly 60 billion relative to the center would land above the interval. Downside risk comes from stronger customs or income-tax receipts and shifted outlays; a favorable combination exceeding roughly 59 billion would land below the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The reference class is the four same-month July observations for 2022-2025: 211.052, 220.782, 243.741, and 291.143 billion. Their base-rate mean is 241.680 billion, while persistence favors the latest observation because the nominal series has risen in each sampled year.","The center uses a persistence prior rather than unsupported component adjustments. Mandatory, interest, and defense outlays create upward pressure, while customs and tax receipts create downward pressure. No calendar adjustment is applied because a payment-date shift was not independently verified."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence model prior = 291.143 billion from July 2025; historical sample = July 2022-2025; adjustment components = no quantified net update because current component measurements and a calendar shift were not verified, so the ladder median is 290. Persistence errors proxied by the three realized year-over-year changes are 9.730, 22.959, and 47.402; sigma = RMSE = sqrt((9.730^2 + 22.959^2 + 47.402^2)/3) = 30.92 billion, and 1.28*sigma = 39.58 billion. Multiplying that half-width by 1.50 for the sparse three-error sample and unresolved payment-timing and policy regime risk gives 59.37 billion. Applied around the approximately 290.6 ladder center, this produces about 231.25 to 350.00; the ladder-implied average half-width is 59.38 billion, essentially equal to the scenario calculation.","Upside risk comes from benefit-payment timing, unexpectedly high interest or defense outlays, or weak receipts; a shock exceeding roughly 60 billion relative to the center would land above the interval. Downside risk comes from stronger customs or income-tax receipts and shifted outlays; a favorable combination exceeding roughly 59 billion would land below the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for the July 2026 U.S. monthly Treasury deficit","Prior/update/interval: persistence model prior = 291.143 billion from July 2025; historical sample = July 2022-2025; adjustment components = no quantified net update because current component measurements and a calendar shift were not verified, so the ladder median is 290. Persistence errors proxied by the three realized year-over-year changes are 9.730, 22.959, and 47.402; sigma = RMSE = sqrt((9.730^2 + 22.959^2 + 47.402^2)/3) = 30.92 billion, and 1.28*sigma = 39.58 billion. Multiplying that half-width by 1.50 for the sparse three-error sample and unresolved payment-timing and policy regime risk gives 59.37 billion. Applied around the approximately 290.6 ladder center, this produces about 231.25 to 350.00; the ladder-implied average half-width is 59.38 billion, essentially equal to the scenario calculation."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-mts-deficit-july-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-08-17\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-mts-deficit-july-2026.2026-07-10T17-20-49Z.us-mts-deficit-july-2026-thesis-analyst-fast-2026-07-10t17-20-49z.5fea4ff9fc510cc8","runId":"run.us-mts-deficit-july-2026.2026-07-10T17-20-49Z.us-mts-deficit-july-2026-thesis-analyst-fast-2026-07-10t17-20-49z.5fea4ff9fc510cc8","predictionId":"us-mts-deficit-july-2026","specId":"spec.us-mts-deficit-july-2026","runLabel":"Fast rollout 1 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["The base rate is the seven-observation July 2019–2025 reference class, averaging $207.351 billion. The level signal from July 2024–2025 is higher, but FY2026 momentum is better because revenue growth has exceeded outlay growth. Higher customs duties are a downside risk to the deficit, while mandatory spending and net-interest growth are an upside risk. Unusually large payment shifts or a sharp receipts surprise would land outside the interval.","Prior/update/interval: The model is a same-month persistence prior using July 2019–2025. Historical mean = (119.696 + 62.990 + 302.050 + 211.052 + 220.782 + 243.741 + 291.143) / 7 = 207.351. I update toward the recent 2024–2025 average of 267.442, then apply a modest downward adjustment for FY2026 revenue strength and lower year-to-date deficit, yielding 260. For this flow series, dispersion is calculated from the values themselves: sample sigma = 87.589. The 80% half-width is roughly 1.28*sigma = 1.28*87.589 = 112.114, giving 260 - 112 = 148 and 260 + 112 = 372 billion after rounding."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The target is the first-print, nominal, not-seasonally-adjusted total monthly deficit in Treasury MTS Table 1—not fiscal-year-to-date deficit, on-budget deficit, receipts, or outlays. Table 1 reports millions of dollars; I divide by 1000 and reverse the table's deficit sign so deficits are positive. Treasury's official schedule identifies August 17, 2026 as the release date; no later correction or revision is admissible.","Tool call: Fetched Treasury MTS Table 1 July observations from the Fiscal Data dataset/API for the pre-pandemic and pandemic reference class."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The target is the first-print, nominal, not-seasonally-adjusted total monthly deficit in Treasury MTS Table 1—not fiscal-year-to-date deficit, on-budget deficit, receipts, or outlays. Table 1 reports millions of dollars; I divide by 1000 and reverse the table's deficit sign so deficits are positive. Treasury's official schedule identifies August 17, 2026 as the release date; no later correction or revision is admissible.","Tool call: Checked the official Treasury MTS release schedule for the July 2026 accounting month."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 224, distribution present, forecast step count 1.","evidence":["The base rate is the seven-observation July 2019–2025 reference class, averaging $207.351 billion. The level signal from July 2024–2025 is higher, but FY2026 momentum is better because revenue growth has exceeded outlay growth. Higher customs duties are a downside risk to the deficit, while mandatory spending and net-interest growth are an upside risk. Unusually large payment shifts or a sharp receipts surprise would land outside the interval.","Prior/update/interval: The model is a same-month persistence prior using July 2019–2025. Historical mean = (119.696 + 62.990 + 302.050 + 211.052 + 220.782 + 243.741 + 291.143) / 7 = 207.351. I update toward the recent 2024–2025 average of 267.442, then apply a modest downward adjustment for FY2026 revenue strength and lower year-to-date deficit, yielding 260. For this flow series, dispersion is calculated from the values themselves: sample sigma = 87.589. The 80% half-width is roughly 1.28*sigma = 1.28*87.589 = 112.114, giving 260 - 112 = 148 and 260 + 112 = 372 billion after rounding."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Checked current fiscal-year momentum in CBO's June 8, 2026 Monthly Budget Review, which uses Treasury budget data.","The base rate is the seven-observation July 2019–2025 reference class, averaging $207.351 billion. The level signal from July 2024–2025 is higher, but FY2026 momentum is better because revenue growth has exceeded outlay growth. Higher customs duties are a downside risk to the deficit, while mandatory spending and net-interest growth are an upside risk. Unusually large payment shifts or a sharp receipts surprise would land outside the interval."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The base rate is the seven-observation July 2019–2025 reference class, averaging $207.351 billion. The level signal from July 2024–2025 is higher, but FY2026 momentum is better because revenue growth has exceeded outlay growth. Higher customs duties are a downside risk to the deficit, while mandatory spending and net-interest growth are an upside risk. Unusually large payment shifts or a sharp receipts surprise would land outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["July 2026 Monthly Treasury Statement deficit forecast","The base rate is the seven-observation July 2019–2025 reference class, averaging $207.351 billion. The level signal from July 2024–2025 is higher, but FY2026 momentum is better because revenue growth has exceeded outlay growth. Higher customs duties are a downside risk to the deficit, while mandatory spending and net-interest growth are an upside risk. Unusually large payment shifts or a sharp receipts surprise would land outside the interval."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-mts-deficit-july-2026\nrunLabel: Fast rollout 1 of 3\nresolutionDate: 2026-08-17\ntraceLineCount: 13\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-mts-deficit-july-2026.2026-07-10T17-26-15Z.us-mts-deficit-july-2026-thesis-analyst-fast-2026-07-10t17-26-15z.ea061c6c369a1703","runId":"run.us-mts-deficit-july-2026.2026-07-10T17-26-15Z.us-mts-deficit-july-2026-thesis-analyst-fast-2026-07-10t17-26-15z.ea061c6c369a1703","predictionId":"us-mts-deficit-july-2026","specId":"spec.us-mts-deficit-july-2026","runLabel":"Fast rollout 2 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["The base rate is the seven-year July reference class: its mean deficit is $207.351 billion, while the three most recent Julys rose from $220.782 billion to $243.741 billion and $291.143 billion. I emphasize the recent same-month observations because fiscal scale and interest costs have risen.","Prior/update/interval: The persistence prior is July 2025's $291.143bn deficit, checked against the 2019-2025 July sample. Adjustments are -$10bn for the improved comparable FY run rate, +$8bn for nominal outlay, benefit, and interest growth, and approximately $0bn net for uncertain receipt, tariff, and payment-timing effects, yielding $289bn. Because this is a flow series, dispersion uses the July values themselves: sample sigma = $87.588bn. The normal 80% half-width is 1.28 × 87.588 = $112.113bn, so $289bn ± $112bn gives rounded bounds of $177bn to $401bn."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The resolver is the first official July 2026 MTS Table 1 monthly Deficit/Surplus (-), a not-seasonally-adjusted nominal flow. Table 1 reports $ millions; I divide by 1000 and reverse the published surplus/deficit sign so deficits are positive.","Tool call: Fetch the recent July reference class for Treasury MTS series MTSDS133FMS, sourced from Fiscal Service and expressed in millions of dollars."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is the first official July 2026 MTS Table 1 monthly Deficit/Surplus (-), a not-seasonally-adjusted nominal flow. Table 1 reports $ millions; I divide by 1000 and reverse the published surplus/deficit sign so deficits are positive.","Tool call: Verify the announced 2026 MTS release timing from the published release calendar and Treasury release convention."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 224, distribution present, forecast step count 1.","evidence":["Prior/update/interval: The persistence prior is July 2025's $291.143bn deficit, checked against the 2019-2025 July sample. Adjustments are -$10bn for the improved comparable FY run rate, +$8bn for nominal outlay, benefit, and interest growth, and approximately $0bn net for uncertain receipt, tariff, and payment-timing effects, yielding $289bn. Because this is a flow series, dispersion uses the July values themselves: sample sigma = $87.588bn. The normal 80% half-width is 1.28 × 87.588 = $112.113bn, so $289bn ± $112bn gives rounded bounds of $177bn to $401bn.","Upside risk to the positive-deficit forecast comes from accelerated outlays, unusually high interest payments, or receipts shifted out of July; a deficit above $401bn would land outside the interval. Downside risk comes from stronger income, corporate, or tariff receipts and payments shifted into other months; a deficit below $177bn, including an unlikely surplus, would land outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The base rate is the seven-year July reference class: its mean deficit is $207.351 billion, while the three most recent Julys rose from $220.782 billion to $243.741 billion and $291.143 billion. I emphasize the recent same-month observations because fiscal scale and interest costs have risen.","Level, momentum, one-off, and policy mechanisms point in different directions: the $291.143bn July 2025 level and rising nominal outlays support a large deficit; the roughly $9.952bn improvement in the January-May comparison supports a small downward adjustment; higher interest and benefit costs push upward, while receipt growth and tariff revenue push downward."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: The persistence prior is July 2025's $291.143bn deficit, checked against the 2019-2025 July sample. Adjustments are -$10bn for the improved comparable FY run rate, +$8bn for nominal outlay, benefit, and interest growth, and approximately $0bn net for uncertain receipt, tariff, and payment-timing effects, yielding $289bn. Because this is a flow series, dispersion uses the July values themselves: sample sigma = $87.588bn. The normal 80% half-width is 1.28 × 87.588 = $112.113bn, so $289bn ± $112bn gives rounded bounds of $177bn to $401bn.","Upside risk to the positive-deficit forecast comes from accelerated outlays, unusually high interest payments, or receipts shifted out of July; a deficit above $401bn would land outside the interval. Downside risk comes from stronger income, corporate, or tariff receipts and payments shifted into other months; a deficit below $177bn, including an unlikely surplus, would land outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["July 2026 Monthly Treasury Statement deficit forecast","Level, momentum, one-off, and policy mechanisms point in different directions: the $291.143bn July 2025 level and rising nominal outlays support a large deficit; the roughly $9.952bn improvement in the January-May comparison supports a small downward adjustment; higher interest and benefit costs push upward, while receipt growth and tariff revenue push downward."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-mts-deficit-july-2026\nrunLabel: Fast rollout 2 of 3\nresolutionDate: 2026-08-17\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-mts-deficit-july-2026.2026-07-10T17-31-59Z.us-mts-deficit-july-2026-thesis-analyst-fast-2026-07-10t17-31-59z.d530fc187be693ab","runId":"run.us-mts-deficit-july-2026.2026-07-10T17-31-59Z.us-mts-deficit-july-2026-thesis-analyst-fast-2026-07-10t17-31-59z.d530fc187be693ab","predictionId":"us-mts-deficit-july-2026","specId":"spec.us-mts-deficit-july-2026","runLabel":"Fast rollout 3 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["The reference class is July monthly flows: the five 2021-2025 deficits are 302.050, 211.052, 220.782, 243.741, and approximately 291.0 billion dollars. Their mean is 253.725 billion, while the recent two-year average is about 267.4 billion. July has historically been overwhelmingly a deficit month.","Prior/update/interval: The model is a same-month persistence prior using the five official July 2021-2025 observations. Historical mean = (302.050 + 211.052 + 220.782 + 243.741 + 291.000)/5 = 253.725. Starting from the more relevant July 2025 level of 291.0, apply +19.0 for nominal and mandatory/interest outlay growth, -15.0 for stronger customs and other receipt growth, and +5.0 for policy and composition effects, yielding 300.0 after rounding. Because this is a flow series, dispersion is computed from the values themselves: sample sigma = sqrt(sum((x-253.725)^2)/4) = 41.0. The 80% half-width is 1.28*sigma = 1.28*41.0 = 52.5, so bounds are 300.0 - 52.5 = 247.5 and 300.0 + 52.5 = 352.5."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["The target is the first-print, nominal, not-seasonally-adjusted monthly Deficit/Surplus (-) in MTS Table 1—not fiscal-year-to-date results, receipts, outlays, or the public-debt statement. The official schedule attached to the target sets release/resolution for 2026-08-17; the Fiscal Service MTS page states that the report covers receipts, outlays, and surplus or deficit. Values are converted from $ millions to USD billions with the ledger sign convention.","Tool call: Fetch Treasury MTS Table 1 July observations for FY2021-FY2022 from the official August 2022 statement."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The target is the first-print, nominal, not-seasonally-adjusted monthly Deficit/Surplus (-) in MTS Table 1—not fiscal-year-to-date results, receipts, outlays, or the public-debt statement. The official schedule attached to the target sets release/resolution for 2026-08-17; the Fiscal Service MTS page states that the report covers receipts, outlays, and surplus or deficit. Values are converted from $ millions to USD billions with the ledger sign convention."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 105, distribution present, forecast step count 1.","evidence":["Level and momentum: the 2025 deficit rose to about $291 billion as outlays reached roughly $630 billion despite about $338 billion of receipts. Structural growth in mandatory programs and debt-service costs points above the five-year mean. Policy mechanism: elevated customs receipts work in the opposite direction, while recently enacted tax and spending provisions create net upward uncertainty for the deficit.","Prior/update/interval: The model is a same-month persistence prior using the five official July 2021-2025 observations. Historical mean = (302.050 + 211.052 + 220.782 + 243.741 + 291.000)/5 = 253.725. Starting from the more relevant July 2025 level of 291.0, apply +19.0 for nominal and mandatory/interest outlay growth, -15.0 for stronger customs and other receipt growth, and +5.0 for policy and composition effects, yielding 300.0 after rounding. Because this is a flow series, dispersion is computed from the values themselves: sample sigma = sqrt(sum((x-253.725)^2)/4) = 41.0. The 80% half-width is 1.28*sigma = 1.28*41.0 = 52.5, so bounds are 300.0 - 52.5 = 247.5 and 300.0 + 52.5 = 352.5."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level and momentum: the 2025 deficit rose to about $291 billion as outlays reached roughly $630 billion despite about $338 billion of receipts. Structural growth in mandatory programs and debt-service costs points above the five-year mean. Policy mechanism: elevated customs receipts work in the opposite direction, while recently enacted tax and spending provisions create net upward uncertainty for the deficit.","Prior/update/interval: The model is a same-month persistence prior using the five official July 2021-2025 observations. Historical mean = (302.050 + 211.052 + 220.782 + 243.741 + 291.000)/5 = 253.725. Starting from the more relevant July 2025 level of 291.0, apply +19.0 for nominal and mandatory/interest outlay growth, -15.0 for stronger customs and other receipt growth, and +5.0 for policy and composition effects, yielding 300.0 after rounding. Because this is a flow series, dispersion is computed from the values themselves: sample sigma = sqrt(sum((x-253.725)^2)/4) = 41.0. The 80% half-width is 1.28*sigma = 1.28*41.0 = 52.5, so bounds are 300.0 - 52.5 = 247.5 and 300.0 + 52.5 = 352.5."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level and momentum: the 2025 deficit rose to about $291 billion as outlays reached roughly $630 billion despite about $338 billion of receipts. Structural growth in mandatory programs and debt-service costs points above the five-year mean. Policy mechanism: elevated customs receipts work in the opposite direction, while recently enacted tax and spending provisions create net upward uncertainty for the deficit.","Counter-considerations: upside risk means a larger positive deficit from payment accelerations, unusually high interest or benefit outlays, or weaker income-tax receipts; a deficit above $352.5 billion would land outside the interval. Downside risk comes from exceptionally strong customs or income-tax receipts, delayed payments, or unusually weak outlays; a deficit below $247.5 billion—or a surplus—would land outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["July 2026 U.S. Monthly Treasury Statement deficit forecast","Level and momentum: the 2025 deficit rose to about $291 billion as outlays reached roughly $630 billion despite about $338 billion of receipts. Structural growth in mandatory programs and debt-service costs points above the five-year mean. Policy mechanism: elevated customs receipts work in the opposite direction, while recently enacted tax and spending provisions create net upward uncertainty for the deficit."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-mts-deficit-july-2026\nrunLabel: Fast rollout 3 of 3\nresolutionDate: 2026-08-17\ntraceLineCount: 13\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-mts-deficit-july-2026.2026-07-10T17-33-54Z.us-mts-deficit-july-2026-thesis-analyst-median3-2026-07-10t17-33-54z.5bb1fb67e1f381f8","runId":"run.us-mts-deficit-july-2026.2026-07-10T17-33-54Z.us-mts-deficit-july-2026-thesis-analyst-median3-2026-07-10t17-33-54z.5bb1fb67e1f381f8","predictionId":"us-mts-deficit-july-2026","specId":"spec.us-mts-deficit-july-2026","runLabel":"Median of 3 rollouts","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and implicit outside-view language.","evidence":["Median-of-3 rollout ensemble","Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T17:20:49Z, 2026-07-10T17:26:15Z, 2026-07-10T17:31:59Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 8 source-context item(s), activity log present.","evidence":["Median CDF quantiles: q10 = 176.1, q50 = 289.0, q90 = 372.9. Constituent points [260, 289, 300.0] with 80% widths [224, 224, 105.0]; the median interval inherits the central rollout mass rather than averaging tails."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 196.8, distribution present, forecast step count 1.","evidence":["Median CDF quantiles: q10 = 176.1, q50 = 289.0, q90 = 372.9. Constituent points [260, 289, 300.0] with 80% widths [224, 224, 105.0]; the median interval inherits the central rollout mass rather than averaging tails.","Forecast: point 289, 80% interval [176.1, 372.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T17:20:49Z, 2026-07-10T17:26:15Z, 2026-07-10T17:31:59Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T17:20:49Z, 2026-07-10T17:26:15Z, 2026-07-10T17:31:59Z. Drivers and resolver fields mirror the rollout closest to the median.","Tool result: {rollout_points: [260, 289, 300.0], rollout_widths: [224, 224, 105.0], q10: 176.1, q50: 289.0, q90: 372.9}"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-mts-deficit-july-2026\nrunLabel: Median of 3 rollouts\nresolutionDate: 2026-08-17\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-mts-deficit-july-2026.2026-07-10T21-22-52Z.us-mts-deficit-july-2026-thesis-analyst-ladder-v2-2026-07-10t21-22-52z.a8f59e77da33c891","runId":"run.us-mts-deficit-july-2026.2026-07-10T21-22-52Z.us-mts-deficit-july-2026-thesis-analyst-ladder-v2-2026-07-10t21-22-52z.a8f59e77da33c891","predictionId":"us-mts-deficit-july-2026","specId":"spec.us-mts-deficit-july-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Reference class/base rate: recent official July MTS prints put the normal range near the low-$200 billions through low-$300 billions, with 2025 at 291.0 and 2021 at 302.1 showing that a July deficit around or above $300 billion is plausible without a crisis, while 2022-2024 anchor the lower-to-middle band.","Prior/update/interval: I start from a persistence prior centered between the recent July sample median and the latest July print, using the fetched July 2022-2025 values of 211.1, 220.8, 244.0, and 291.0 plus the 2021 high of 302.1 to anchor the rung span. I adjust about -35 billion from the July 2025 print for stronger tariff/customs receipts and partial mean reversion from the 20% year-over-year 2025 jump, then add back about +14 billion for higher interest, mandatory outlays, defense, and enacted tax-policy deficit pressure, for a net update near -21 billion to a 270.0 median. The interval method is the threshold ladder below, and the 156.9 billion 80% width reflects recent July dispersion plus monthly cash-timing uncertainty rather than a narrow trend extrapolation, yielding final implied 80% bounds of 201.1 to 358.0."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing: the resolver is the first-print U.S. Treasury Monthly Treasury Statement Table 1 monthly Deficit/Surplus (-) for July 2026, in the same monthly, not fiscal-year-to-date, nominal cash-budget variant. The official release calendar identifies the July 2026 MTS release date as 2026-08-17, and the target uses the first print with no later revisions.","Tool call: Treasury Monthly Treasury Statement Table 1 history for July monthly Deficit/Surplus (-), converted from $ millions to usd_billions and sign-flipped so deficits are positive"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing: the resolver is the first-print U.S. Treasury Monthly Treasury Statement Table 1 monthly Deficit/Surplus (-) for July 2026, in the same monthly, not fiscal-year-to-date, nominal cash-budget variant. The official release calendar identifies the July 2026 MTS release date as 2026-08-17, and the target uses the first print with no later revisions.","Published values are derived from the ladder only: pointEstimate = median = 270.0 usd_billions; ciLow = 10th percentile = 201.1 usd_billions; ciHigh = 90th percentile = 358.0 usd_billions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 156.9, distribution present, forecast step count 1.","evidence":["Prior/update/interval: I start from a persistence prior centered between the recent July sample median and the latest July print, using the fetched July 2022-2025 values of 211.1, 220.8, 244.0, and 291.0 plus the 2021 high of 302.1 to anchor the rung span. I adjust about -35 billion from the July 2025 print for stronger tariff/customs receipts and partial mean reversion from the 20% year-over-year 2025 jump, then add back about +14 billion for higher interest, mandatory outlays, defense, and enacted tax-policy deficit pressure, for a net update near -21 billion to a 270.0 median. The interval method is the threshold ladder below, and the 156.9 billion 80% width reflects recent July dispersion plus monthly cash-timing uncertainty rather than a narrow trend extrapolation, yielding final implied 80% bounds of 201.1 to 358.0.","Upside risk for the deficit is a July outlay bulge from interest, defense, Medicare, or benefit timing that pushes the print toward the 330-370 range. Downside risk is customs receipts and delayed outlays holding the deficit near 200-230. A major calendar shift or unusually large one-off payment would land outside the interval, above 358.0 if outlays bunch heavily or below 201.1 if receipts are unusually strong and payments slip."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: I start from a persistence prior centered between the recent July sample median and the latest July print, using the fetched July 2022-2025 values of 211.1, 220.8, 244.0, and 291.0 plus the 2021 high of 302.1 to anchor the rung span. I adjust about -35 billion from the July 2025 print for stronger tariff/customs receipts and partial mean reversion from the 20% year-over-year 2025 jump, then add back about +14 billion for higher interest, mandatory outlays, defense, and enacted tax-policy deficit pressure, for a net update near -21 billion to a 270.0 median. The interval method is the threshold ladder below, and the 156.9 billion 80% width reflects recent July dispersion plus monthly cash-timing uncertainty rather than a narrow trend extrapolation, yielding final implied 80% bounds of 201.1 to 358.0."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: I start from a persistence prior centered between the recent July sample median and the latest July print, using the fetched July 2022-2025 values of 211.1, 220.8, 244.0, and 291.0 plus the 2021 high of 302.1 to anchor the rung span. I adjust about -35 billion from the July 2025 print for stronger tariff/customs receipts and partial mean reversion from the 20% year-over-year 2025 jump, then add back about +14 billion for higher interest, mandatory outlays, defense, and enacted tax-policy deficit pressure, for a net update near -21 billion to a 270.0 median. The interval method is the threshold ladder below, and the 156.9 billion 80% width reflects recent July dispersion plus monthly cash-timing uncertainty rather than a narrow trend extrapolation, yielding final implied 80% bounds of 201.1 to 358.0.","Upside risk for the deficit is a July outlay bulge from interest, defense, Medicare, or benefit timing that pushes the print toward the 330-370 range. Downside risk is customs receipts and delayed outlays holding the deficit near 200-230. A major calendar shift or unusually large one-off payment would land outside the interval, above 358.0 if outlays bunch heavily or below 201.1 if receipts are unusually strong and payments slip."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["U.S. Monthly Treasury Statement July 2026 Deficit Forecast","Prior/update/interval: I start from a persistence prior centered between the recent July sample median and the latest July print, using the fetched July 2022-2025 values of 211.1, 220.8, 244.0, and 291.0 plus the 2021 high of 302.1 to anchor the rung span. I adjust about -35 billion from the July 2025 print for stronger tariff/customs receipts and partial mean reversion from the 20% year-over-year 2025 jump, then add back about +14 billion for higher interest, mandatory outlays, defense, and enacted tax-policy deficit pressure, for a net update near -21 billion to a 270.0 median. The interval method is the threshold ladder below, and the 156.9 billion 80% width reflects recent July dispersion plus monthly cash-timing uncertainty rather than a narrow trend extrapolation, yielding final implied 80% bounds of 201.1 to 358.0."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-mts-deficit-july-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-08-17\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-mts-deficit-july-2026.2026-07-10T21-45-19Z.us-mts-deficit-july-2026-thesis-analyst-ladder-v2-2026-07-10t21-45-19z.4ba7b1a0cd884ade","runId":"run.us-mts-deficit-july-2026.2026-07-10T21-45-19Z.us-mts-deficit-july-2026-thesis-analyst-ladder-v2-2026-07-10t21-45-19z.4ba7b1a0cd884ade","predictionId":"us-mts-deficit-july-2026","specId":"spec.us-mts-deficit-july-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["The reference class base rate is the three most recent same-month first prints: $220.782B, $243.741B, and $291.143B. A documented recency-weighted persistence model with weights 0.20, 0.30, and 0.50 gives a pre-update prior of 0.20×220.782 + 0.30×243.741 + 0.50×291.143 = $262.850B.","Prior/update/interval: The model prior is $262.850B from the fetched July 2023–2025 sample. I add $28.144B for continuation of the observed July trend, equal to 80% of the fitted three-observation annual slope of $35.181B; add $18.000B because May 2026 outlays of $628.161B remained near July 2025's $629.635B despite July's weaker seasonal receipts; and subtract $3.539B to temper extrapolation for the rise in July receipts through 2025. These adjustments sum to +$42.605B and produce $305.455B. The elicited ladder gives final implied 80% bounds of $210.000B to $400.000B. Its roughly $95B half-width exceeds the historical July range of $70.361B and twice the latest $47.402B year-over-year increase, allowing for payment-timing uncertainty beyond the small reference sample."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The target is the first-print July 2026 monthly Deficit/Surplus (-) in MTS Table 1, not the fiscal-year-to-date balance. Table 1 is denominated in $ millions; I divide by 1000 and reverse the table's sign convention so deficits are positive. Later revisions are excluded.","Tool result: Official Table 1 values were July 2023 receipts $276.161B, outlays $496.943B, deficit $220.782B; July 2024 receipts $330.377B, outlays $574.119B, deficit $243.741B; and July 2025 receipts $338.492B, outlays $629.635B, deficit $291.143B."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the first-print July 2026 monthly Deficit/Surplus (-) in MTS Table 1, not the fiscal-year-to-date balance. Table 1 is denominated in $ millions; I divide by 1000 and reverse the table's sign convention so deficits are positive. Later revisions are excluded.","Tool call: Check the Treasury Fiscal Data release calendar for the July 2026 MTS."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 190, distribution present, forecast step count 1.","evidence":["Prior/update/interval: The model prior is $262.850B from the fetched July 2023–2025 sample. I add $28.144B for continuation of the observed July trend, equal to 80% of the fitted three-observation annual slope of $35.181B; add $18.000B because May 2026 outlays of $628.161B remained near July 2025's $629.635B despite July's weaker seasonal receipts; and subtract $3.539B to temper extrapolation for the rise in July receipts through 2025. These adjustments sum to +$42.605B and produce $305.455B. The elicited ladder gives final implied 80% bounds of $210.000B to $400.000B. Its roughly $95B half-width exceeds the historical July range of $70.361B and twice the latest $47.402B year-over-year increase, allowing for payment-timing uncertainty beyond the small reference sample.","Upside risk to the deficit comes from accelerated benefit or defense payments, weaker individual-income-tax receipts, larger refunds, or unusually high interest outlays; a combined net deterioration exceeding about $95B from the median would land above the interval at more than $400B. Downside risk comes from strong withheld taxes, customs receipts, delayed payments, or unusually large offsetting receipts; a favorable timing shift exceeding about $95B would land below the interval at less than $210B."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Read the May 2026 MTS Table 1 for current-fiscal-year momentum.","Prior/update/interval: The model prior is $262.850B from the fetched July 2023–2025 sample. I add $28.144B for continuation of the observed July trend, equal to 80% of the fitted three-observation annual slope of $35.181B; add $18.000B because May 2026 outlays of $628.161B remained near July 2025's $629.635B despite July's weaker seasonal receipts; and subtract $3.539B to temper extrapolation for the rise in July receipts through 2025. These adjustments sum to +$42.605B and produce $305.455B. The elicited ladder gives final implied 80% bounds of $210.000B to $400.000B. Its roughly $95B half-width exceeds the historical July range of $70.361B and twice the latest $47.402B year-over-year increase, allowing for payment-timing uncertainty beyond the small reference sample."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: The model prior is $262.850B from the fetched July 2023–2025 sample. I add $28.144B for continuation of the observed July trend, equal to 80% of the fitted three-observation annual slope of $35.181B; add $18.000B because May 2026 outlays of $628.161B remained near July 2025's $629.635B despite July's weaker seasonal receipts; and subtract $3.539B to temper extrapolation for the rise in July receipts through 2025. These adjustments sum to +$42.605B and produce $305.455B. The elicited ladder gives final implied 80% bounds of $210.000B to $400.000B. Its roughly $95B half-width exceeds the historical July range of $70.361B and twice the latest $47.402B year-over-year increase, allowing for payment-timing uncertainty beyond the small reference sample.","Upside risk to the deficit comes from accelerated benefit or defense payments, weaker individual-income-tax receipts, larger refunds, or unusually high interest outlays; a combined net deterioration exceeding about $95B from the median would land above the interval at more than $400B. Downside risk comes from strong withheld taxes, customs receipts, delayed payments, or unusually large offsetting receipts; a favorable timing shift exceeding about $95B would land below the interval at less than $210B."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["July 2026 Monthly Treasury Statement deficit forecast","Prior/update/interval: The model prior is $262.850B from the fetched July 2023–2025 sample. I add $28.144B for continuation of the observed July trend, equal to 80% of the fitted three-observation annual slope of $35.181B; add $18.000B because May 2026 outlays of $628.161B remained near July 2025's $629.635B despite July's weaker seasonal receipts; and subtract $3.539B to temper extrapolation for the rise in July receipts through 2025. These adjustments sum to +$42.605B and produce $305.455B. The elicited ladder gives final implied 80% bounds of $210.000B to $400.000B. Its roughly $95B half-width exceeds the historical July range of $70.361B and twice the latest $47.402B year-over-year increase, allowing for payment-timing uncertainty beyond the small reference sample."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-mts-deficit-july-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-08-17\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-mts-deficit-july-2026.2026-07-10T22-04-30Z.us-mts-deficit-july-2026-thesis-analyst-ladder-v2-2026-07-10t22-04-30z.11fb60ca9945cc92","runId":"run.us-mts-deficit-july-2026.2026-07-10T22-04-30Z.us-mts-deficit-july-2026-thesis-analyst-ladder-v2-2026-07-10t22-04-30z.11fb60ca9945cc92","predictionId":"us-mts-deficit-july-2026","specId":"spec.us-mts-deficit-july-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.51,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["The resolver is the first official July 2026 MTS Table 1 print: monthly Deficit/Surplus (-), in $ millions divided by 1,000, with deficits positive. This is the unadjusted monthly Table 1 variant, not fiscal-year-to-date receipts, outlays, financing, or a revised historical value. Treasury's official MTS release calendar was checked for the August 17, 2026 release date.","Tool call: Fetched Treasury's June 2025 Monthly Treasury Statement Table 1, containing the prior July row in the same unadjusted monthly series."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The resolver is the first official July 2026 MTS Table 1 print: monthly Deficit/Surplus (-), in $ millions divided by 1,000, with deficits positive. This is the unadjusted monthly Table 1 variant, not fiscal-year-to-date receipts, outlays, financing, or a revised historical value. Treasury's official MTS release calendar was checked for the August 17, 2026 release date.","Tool call: Fetched Treasury's Monthly Treasury Statement Table 1 historical reports for the remaining July reference observations."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The resolver is the first official July 2026 MTS Table 1 print: monthly Deficit/Surplus (-), in $ millions divided by 1,000, with deficits positive. This is the unadjusted monthly Table 1 variant, not fiscal-year-to-date receipts, outlays, financing, or a revised historical value. Treasury's official MTS release calendar was checked for the August 17, 2026 release date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 160, distribution present, forecast step count 1.","evidence":["Prior/update/interval: I use the equal-weight 2021-2025 July-only Table 1 persistence prior, mean $253.741 billion, rounded through the ladder to a $255 billion median. I apply no unsupported current-month update: the earlier non-comparable May balance and non-official mirror are excluded. The interval method starts with the fetched July sample's $211.000-$302.050 billion range, then assigns tail mass below and above that range for month-specific benefit, interest, refund, and agency-payment timing; this yields ladder-derived $190 billion and $350 billion 10th/90th bounds rather than a default band.","Upside risk is unusually large benefit, interest, refund, or agency-payment timing that lifts the deficit above $350 billion. Downside risk is unusually strong receipts or delayed outlays that reduce it below $190 billion. An exceptional payment-timing or receipt event would land outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Upside risk is unusually large benefit, interest, refund, or agency-payment timing that lifts the deficit above $350 billion. Downside risk is unusually strong receipts or delayed outlays that reduce it below $190 billion. An exceptional payment-timing or receipt event would land outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: I use the equal-weight 2021-2025 July-only Table 1 persistence prior, mean $253.741 billion, rounded through the ladder to a $255 billion median. I apply no unsupported current-month update: the earlier non-comparable May balance and non-official mirror are excluded. The interval method starts with the fetched July sample's $211.000-$302.050 billion range, then assigns tail mass below and above that range for month-specific benefit, interest, refund, and agency-payment timing; this yields ladder-derived $190 billion and $350 billion 10th/90th bounds rather than a default band.","Upside risk is unusually large benefit, interest, refund, or agency-payment timing that lifts the deficit above $350 billion. Downside risk is unusually strong receipts or delayed outlays that reduce it below $190 billion. An exceptional payment-timing or receipt event would land outside the interval."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-mts-deficit-july-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-08-17\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-mts-deficit-july-2026.2026-07-10T22-22-08Z.us-mts-deficit-july-2026-thesis-analyst-ladder-v2-2026-07-10t22-22-08z.daf3a43616ba4484","runId":"run.us-mts-deficit-july-2026.2026-07-10T22-22-08Z.us-mts-deficit-july-2026-thesis-analyst-ladder-v2-2026-07-10t22-22-08z.daf3a43616ba4484","predictionId":"us-mts-deficit-july-2026","specId":"spec.us-mts-deficit-july-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["The target is the first official July 2026 Monthly Treasury Statement print, Table 1, monthly Deficit/Surplus (-), expressed in usd_billions with deficits positive. The canonical ledger contract gives resolutionDate 2026-08-17, and the target is the gross, non-seasonally-adjusted monthly amount rather than fiscal-year-to-date totals or a revised historical value.","Tool call: Fetched the prior July first-print reference from Treasury release coverage; the FRED series was used only as a history mirror, not as the resolver."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The target is the first official July 2026 Monthly Treasury Statement print, Table 1, monthly Deficit/Surplus (-), expressed in usd_billions with deficits positive. The canonical ledger contract gives resolutionDate 2026-08-17, and the target is the gross, non-seasonally-adjusted monthly amount rather than fiscal-year-to-date totals or a revised historical value.","Tool call: Fetched official Treasury MTS Table 1 observations from published reports, including July reference months."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the first official July 2026 Monthly Treasury Statement print, Table 1, monthly Deficit/Surplus (-), expressed in usd_billions with deficits positive. The canonical ledger contract gives resolutionDate 2026-08-17, and the target is the gross, non-seasonally-adjusted monthly amount rather than fiscal-year-to-date totals or a revised historical value.","Tool call: Fetched official Treasury MTS Table 1 observations from published reports, including July reference months."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 167, distribution present, forecast step count 1.","evidence":["The base rate is the July 2023-2025 reference class of 220.782, 243.741, and approximately 291 usd_billions, with a simple center near 252. The latest sequence supports an upward update: persistent interest and entitlement outlays contribute approximately +18 billion, the recent deficit-heavy run-rate contributes approximately +16 billion, and July timing uncertainty contributes approximately +10 billion, producing a roughly +44 billion judgmental adjustment from 252 to 296.","Prior/update/interval: The persistence prior is approximately 252 usd_billions from the three fetched July observations. The approximately +44 billion update reflects +18 billion for persistent interest and benefit outlays, +16 billion for the recent February-May deficit pattern, and +10 billion for July cash-flow timing. The 80% ladder is calibrated to include the fetched July span of 220.782-291, the broader latest-month swing of -215.024 to 307.501, and additional first-print timing and receipt uncertainty; the fetched July values anchor the central rungs while the broader monthly swing supports the 200-400 outer span."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["July is typically a deficit month because large benefit, interest, and other federal outlays continue while receipts are less concentrated than in April and June. Monthly cash-flow timing can nevertheless dominate the signal, as shown by the latest five-month sequence ranging from a $215.024 billion surplus to a $307.501 billion deficit."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The base rate is the July 2023-2025 reference class of 220.782, 243.741, and approximately 291 usd_billions, with a simple center near 252. The latest sequence supports an upward update: persistent interest and entitlement outlays contribute approximately +18 billion, the recent deficit-heavy run-rate contributes approximately +16 billion, and July timing uncertainty contributes approximately +10 billion, producing a roughly +44 billion judgmental adjustment from 252 to 296.","Prior/update/interval: The persistence prior is approximately 252 usd_billions from the three fetched July observations. The approximately +44 billion update reflects +18 billion for persistent interest and benefit outlays, +16 billion for the recent February-May deficit pattern, and +10 billion for July cash-flow timing. The 80% ladder is calibrated to include the fetched July span of 220.782-291, the broader latest-month swing of -215.024 to 307.501, and additional first-print timing and receipt uncertainty; the fetched July values anchor the central rungs while the broader monthly swing supports the 200-400 outer span."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: The persistence prior is approximately 252 usd_billions from the three fetched July observations. The approximately +44 billion update reflects +18 billion for persistent interest and benefit outlays, +16 billion for the recent February-May deficit pattern, and +10 billion for July cash-flow timing. The 80% ladder is calibrated to include the fetched July span of 220.782-291, the broader latest-month swing of -215.024 to 307.501, and additional first-print timing and receipt uncertainty; the fetched July values anchor the central rungs while the broader monthly swing supports the 200-400 outer span.","Downside risk would be a receipt-heavy July, including unusually early tariff or other cash receipts, combined with benefit payments landing outside the month, pushing the deficit below 213 billion. Upside risk would be concentrated interest or benefit payments and weaker-than-expected receipts arriving in July, pushing the deficit above 380 billion. A major one-off fiscal transaction or exceptional payment-timing shift would land outside the interval."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-mts-deficit-july-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-08-17\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T05-16-48Z.dbc38714bea91c3c","runId":"run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T05-16-48Z.dbc38714bea91c3c","predictionId":"canada-ei-regular-beneficiaries-june-2026","specId":"spec.canada-ei-regular-beneficiaries-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: for a two-month-ahead level forecast of a seasonally adjusted EI beneficiary count, the base rate is persistence from the latest available level with recent official monthly changes. Same-variant anchors are all Canada regular EI beneficiaries, seasonally adjusted, from the same Statistics Canada EI series, not gross claims, LFS unemployment, or unadjusted counts.","Prior/update/interval: persistence prior starts at April 2026 = 544.44 thousand. Recent official EI changes used for dispersion are January -17.0 thousand, February -8.7 thousand, March +2.3 thousand, and April about -2.7 thousand from -0.5% of roughly 547.2 thousand; mean change = -6.5 thousand and sample sigma = 8.3 thousand. Base two-month trend prior is 544.4 - 2*6.5 = 531.4 thousand. I add +5.6 thousand for March-April stabilization and EI benefit duration lag, then subtract 2.0 thousand for the strong May LFS signal lowering expected inflows, for a net +3.6 thousand adjustment and point = 535.0 thousand. The short four-change volatility sample is narrow but same-variant and recent, so I use it as a base and widen for horizon. The one-month 80% half-width is 1.28*sigma = 1.28*8.3 = 10.6 thousand; because June is two unpublished EI months beyond April, I widen to about 16.0 thousand, within 1.5x the one-month half-width, so interval = 535.0 +/- 16.0 = [519.0, 551.0]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this targets Statistics Canada Table 14-10-0011-01, Canada, regular Employment Insurance beneficiaries, monthly, seasonally adjusted, June 2026, first print, converted from persons to thousands. The ledger table description mentions The Daily release for May 2026, but the catalog slug, dataPointId, expected release window, and question period identify June 2026, so I keep the forecast tied to the June 2026 target.","Tool result: Fetched latest same-series values: April 2026 regular EI beneficiaries Canada = 544,440 persons = 544.44 thousand; monthly change = -0.5%; year-over-year change = +3.5%; The Daily states May 2026 EI data will be released 2026-07-23."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Canada regular EI beneficiaries, June 2026 first print","Framing and exact resolver: this targets Statistics Canada Table 14-10-0011-01, Canada, regular Employment Insurance beneficiaries, monthly, seasonally adjusted, June 2026, first print, converted from persons to thousands. The ledger table description mentions The Daily release for May 2026, but the catalog slug, dataPointId, expected release window, and question period identify June 2026, so I keep the forecast tied to the June 2026 target."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 32, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior starts at April 2026 = 544.44 thousand. Recent official EI changes used for dispersion are January -17.0 thousand, February -8.7 thousand, March +2.3 thousand, and April about -2.7 thousand from -0.5% of roughly 547.2 thousand; mean change = -6.5 thousand and sample sigma = 8.3 thousand. Base two-month trend prior is 544.4 - 2*6.5 = 531.4 thousand. I add +5.6 thousand for March-April stabilization and EI benefit duration lag, then subtract 2.0 thousand for the strong May LFS signal lowering expected inflows, for a net +3.6 thousand adjustment and point = 535.0 thousand. The short four-change volatility sample is narrow but same-variant and recent, so I use it as a base and widen for horizon. The one-month 80% half-width is 1.28*sigma = 1.28*8.3 = 10.6 thousand; because June is two unpublished EI months beyond April, I widen to about 16.0 thousand, within 1.5x the one-month half-width, so interval = 535.0 +/- 16.0 = [519.0, 551.0].","Upside risk: tariff-sensitive layoffs, administrative backlogs, or slower exits from regular benefits would land above the interval if the first-print June 2026 Table 14-10-0011-01 value exceeds 551 thousand. Downside risk: a broad job-finding improvement after the May LFS rebound would land below the interval if the first-print June 2026 value falls below 519 thousand. Outside the interval would be most plausible if the May LFS employment gain carries directly into EI exits or if a sudden sectoral shock reverses it before the June EI reference week."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior starts at April 2026 = 544.44 thousand. Recent official EI changes used for dispersion are January -17.0 thousand, February -8.7 thousand, March +2.3 thousand, and April about -2.7 thousand from -0.5% of roughly 547.2 thousand; mean change = -6.5 thousand and sample sigma = 8.3 thousand. Base two-month trend prior is 544.4 - 2*6.5 = 531.4 thousand. I add +5.6 thousand for March-April stabilization and EI benefit duration lag, then subtract 2.0 thousand for the strong May LFS signal lowering expected inflows, for a net +3.6 thousand adjustment and point = 535.0 thousand. The short four-change volatility sample is narrow but same-variant and recent, so I use it as a base and widen for horizon. The one-month 80% half-width is 1.28*sigma = 1.28*8.3 = 10.6 thousand; because June is two unpublished EI months beyond April, I widen to about 16.0 thousand, within 1.5x the one-month half-width, so interval = 535.0 +/- 16.0 = [519.0, 551.0]."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Framing and exact resolver: this targets Statistics Canada Table 14-10-0011-01, Canada, regular Employment Insurance beneficiaries, monthly, seasonally adjusted, June 2026, first print, converted from persons to thousands. The ledger table description mentions The Daily release for May 2026, but the catalog slug, dataPointId, expected release window, and question period identify June 2026, so I keep the forecast tied to the June 2026 target.","Prior/update/interval: persistence prior starts at April 2026 = 544.44 thousand. Recent official EI changes used for dispersion are January -17.0 thousand, February -8.7 thousand, March +2.3 thousand, and April about -2.7 thousand from -0.5% of roughly 547.2 thousand; mean change = -6.5 thousand and sample sigma = 8.3 thousand. Base two-month trend prior is 544.4 - 2*6.5 = 531.4 thousand. I add +5.6 thousand for March-April stabilization and EI benefit duration lag, then subtract 2.0 thousand for the strong May LFS signal lowering expected inflows, for a net +3.6 thousand adjustment and point = 535.0 thousand. The short four-change volatility sample is narrow but same-variant and recent, so I use it as a base and widen for horizon. The one-month 80% half-width is 1.28*sigma = 1.28*8.3 = 10.6 thousand; because June is two unpublished EI months beyond April, I widen to about 16.0 thousand, within 1.5x the one-month half-width, so interval = 535.0 +/- 16.0 = [519.0, 551.0]."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Framing and exact resolver: this targets Statistics Canada Table 14-10-0011-01, Canada, regular Employment Insurance beneficiaries, monthly, seasonally adjusted, June 2026, first print, converted from persons to thousands. The ledger table description mentions The Daily release for May 2026, but the catalog slug, dataPointId, expected release window, and question period identify June 2026, so I keep the forecast tied to the June 2026 target.","Tool result: Fetched May 2026 Canada employment = 21,122,000; employment monthly change = +0.4%; unemployment rate = 6.6%; unemployment rate monthly change = -0.3 percentage points; highlights say employment increased by 88,000 in May after a net decline of 112,000 over January-April 2026."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-ei-regular-beneficiaries-june-2026\nrunLabel: Headline\nresolutionDate: 2026-08-20\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T15-38-24Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-fast-2026-07-10t15-38-24z.f6af2f546f676625","runId":"run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T15-38-24Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-fast-2026-07-10t15-38-24z.f6af2f546f676625","predictionId":"canada-ei-regular-beneficiaries-june-2026","specId":"spec.canada-ei-regular-beneficiaries-june-2026","runLabel":"Fast rollout 1 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the 2025-June through 2026-April SA level sequence is elevated but its recent movement has been mixed, with the late-2025 high followed by a January-February decline and a partial March rebound. The outside-view forecast therefore begins near the latest level rather than extrapolating either the December peak or the one-month April fall.","Prior/update/interval: persistence prior is April's 544.44 thousand; the historical sample is the 10 official successive SA changes from June 2025 through April 2026; adjustments are a small mean-reversion offset after the recent January-February drop, tempered by April's -0.5% decline and two unobserved monthly steps; sigma = 7.93, so the interval method uses 1.28*sigma = 10.15 thousand, rounded to 10.2; final implied bounds are 534.3 to 554.7 thousand around 544.5."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The resolver is the Canada, seasonally adjusted regular-beneficiary total in Statistics Canada table 14-10-0011-01, converted from persons to thousands. This uses the same SA variant for every anchor; it resolves only to the first June 2026 print, not later table revisions.","Tool call: Fetched the official Statistics Canada chart history for table 14-10-0011-01."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Canada regular Employment Insurance beneficiaries — June 2026 first print","The resolver is the Canada, seasonally adjusted regular-beneficiary total in Statistics Canada table 14-10-0011-01, converted from persons to thousands. This uses the same SA variant for every anchor; it resolves only to the first June 2026 print, not later table revisions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 20.4, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is April's 544.44 thousand; the historical sample is the 10 official successive SA changes from June 2025 through April 2026; adjustments are a small mean-reversion offset after the recent January-February drop, tempered by April's -0.5% decline and two unobserved monthly steps; sigma = 7.93, so the interval method uses 1.28*sigma = 10.15 thousand, rounded to 10.2; final implied bounds are 534.3 to 554.7 thousand around 544.5.","upside risk: renewed job loss or unusually large new claims could push beneficiaries above 554.7 thousand. downside risk: a stronger return-to-work flow or benefit exhaustion could push the result below 534.3 thousand. A monthly move larger than the recent historical dispersion would land outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: the 2025-June through 2026-April SA level sequence is elevated but its recent movement has been mixed, with the late-2025 high followed by a January-February decline and a partial March rebound. The outside-view forecast therefore begins near the latest level rather than extrapolating either the December peak or the one-month April fall.","Prior/update/interval: persistence prior is April's 544.44 thousand; the historical sample is the 10 official successive SA changes from June 2025 through April 2026; adjustments are a small mean-reversion offset after the recent January-February drop, tempered by April's -0.5% decline and two unobserved monthly steps; sigma = 7.93, so the interval method uses 1.28*sigma = 10.15 thousand, rounded to 10.2; final implied bounds are 534.3 to 554.7 thousand around 544.5."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Base rate/reference class: the 2025-June through 2026-April SA level sequence is elevated but its recent movement has been mixed, with the late-2025 high followed by a January-February decline and a partial March rebound. The outside-view forecast therefore begins near the latest level rather than extrapolating either the December peak or the one-month April fall.","Prior/update/interval: persistence prior is April's 544.44 thousand; the historical sample is the 10 official successive SA changes from June 2025 through April 2026; adjustments are a small mean-reversion offset after the recent January-February drop, tempered by April's -0.5% decline and two unobserved monthly steps; sigma = 7.93, so the interval method uses 1.28*sigma = 10.15 thousand, rounded to 10.2; final implied bounds are 534.3 to 554.7 thousand around 544.5."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-ei-regular-beneficiaries-june-2026\nrunLabel: Fast rollout 1 of 3\nresolutionDate: 2026-08-20\ntraceLineCount: 13\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T15-42-29Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-fast-2026-07-10t15-42-29z.cea980f648acfdb4","runId":"run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T15-42-29Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-fast-2026-07-10t15-42-29z.cea980f648acfdb4","predictionId":"canada-ei-regular-beneficiaries-june-2026","specId":"spec.canada-ei-regular-beneficiaries-june-2026","runLabel":"Fast rollout 2 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["The resolver is Statistics Canada table 14-10-0011-01: Canada, regular benefits, both sexes, age 15 years and over, seasonally adjusted. Every level anchor below uses that same SA regular-beneficiary variant. The registered target specifies the first June print on 2026-08-20; the official Daily schedule consulted in this run is a rolling two-week calendar, while the prior EI release explicitly announced the May release for 2026-07-23.","Base rate: the relevant reference class is the latest four monthly changes in the same SA level series: -8.60, -8.67, -2.91, and -3.00 thousand. The near-term base case is continued but slower decline after the sharp January-February falls; stronger May employment and a lower unemployment rate modestly reinforce a lower June EI-beneficiary level."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The resolver is Statistics Canada table 14-10-0011-01: Canada, regular benefits, both sexes, age 15 years and over, seasonally adjusted. Every level anchor below uses that same SA regular-beneficiary variant. The registered target specifies the first June print on 2026-08-20; the official Daily schedule consulted in this run is a rolling two-week calendar, while the prior EI release explicitly announced the May release for 2026-07-23.","Tool result: Fetched persons: December 2025 567,620; January 2026 559,020; February 2026 550,350; March 2026 547,440; April 2026 544,440. Converted to thousands: 567.62, 559.02, 550.35, 547.44, 544.44."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Canada regular EI beneficiaries: June 2026 first print","The resolver is Statistics Canada table 14-10-0011-01: Canada, regular benefits, both sexes, age 15 years and over, seasonally adjusted. Every level anchor below uses that same SA regular-beneficiary variant. The registered target specifies the first June print on 2026-08-20; the official Daily schedule consulted in this run is a rolling two-week calendar, while the prior EI release explicitly announced the May release for 2026-07-23."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 8.4, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior uses the mean of the latest two changes, (-2.91 - 3.00)/2 = -2.955 thousand per month; two-step persistence from April gives 544.44 - 2×2.955 = 538.53. I apply a -1.03 thousand labour-market update from May's 88,000 employment gain and 0.3-point unemployment-rate fall, giving 537.50. Using the four fetched successive changes, sample sigma = 3.27 thousand; 1.28×sigma = 4.19 thousand, rounded to a 4.20-thousand 80% half-width. Final implied bounds are 537.50 - 4.20 = 533.30 and 537.50 + 4.20 = 541.70 thousand.","Upside risk: renewed layoffs or a reversal of May's employment gain would raise regular beneficiaries above the interval. Downside risk: unusually rapid job finding or benefit exits would push the print below the interval. An administrative or eligibility-policy change affecting receipt counts would be outside the interval because it is not captured by recent SA month-to-month dispersion."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Upside risk: renewed layoffs or a reversal of May's employment gain would raise regular beneficiaries above the interval. Downside risk: unusually rapid job finding or benefit exits would push the print below the interval. An administrative or eligibility-policy change affecting receipt counts would be outside the interval because it is not captured by recent SA month-to-month dispersion."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate: the relevant reference class is the latest four monthly changes in the same SA level series: -8.60, -8.67, -2.91, and -3.00 thousand. The near-term base case is continued but slower decline after the sharp January-February falls; stronger May employment and a lower unemployment rate modestly reinforce a lower June EI-beneficiary level.","Upside risk: renewed layoffs or a reversal of May's employment gain would raise regular beneficiaries above the interval. Downside risk: unusually rapid job finding or benefit exits would push the print below the interval. An administrative or eligibility-policy change affecting receipt counts would be outside the interval because it is not captured by recent SA month-to-month dispersion."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Fetched May 2026 employment of 21,122,000, up 88,000 month over month, and an unemployment rate of 6.6%, down 0.3 percentage points from April.","Prior/update/interval: persistence prior uses the mean of the latest two changes, (-2.91 - 3.00)/2 = -2.955 thousand per month; two-step persistence from April gives 544.44 - 2×2.955 = 538.53. I apply a -1.03 thousand labour-market update from May's 88,000 employment gain and 0.3-point unemployment-rate fall, giving 537.50. Using the four fetched successive changes, sample sigma = 3.27 thousand; 1.28×sigma = 4.19 thousand, rounded to a 4.20-thousand 80% half-width. Final implied bounds are 537.50 - 4.20 = 533.30 and 537.50 + 4.20 = 541.70 thousand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-ei-regular-beneficiaries-june-2026\nrunLabel: Fast rollout 2 of 3\nresolutionDate: 2026-08-20\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T15-46-34Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-fast-2026-07-10t15-46-34z.22d59dbf07a5c6ff","runId":"run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T15-46-34Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-fast-2026-07-10t15-46-34z.22d59dbf07a5c6ff","predictionId":"canada-ei-regular-beneficiaries-june-2026","specId":"spec.canada-ei-regular-beneficiaries-june-2026","runLabel":"Fast rollout 3 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the near-term reference class is the four latest matching seasonally adjusted Canada totals, 554.4, 545.7, 548.0, and 544.44 thousand. The April level and the May labour-market improvement favour a small decline rather than a return to the November 2025 peak of 569.0 thousand.","Prior/update/interval: persistence prior is April's 544.44 thousand, using the January-April 2026 matching-variant historical sample (554.4, 545.7, 548.0, 544.44). Successive changes are -8.7, +2.3, and -3.56 thousand; sample sigma = 5.5 thousand, so 1.28*sigma = 7.0 thousand. I apply a -3.4 thousand combined adjustment for recent level/momentum (slightly negative), the May employment and unemployment improvement (negative), and offsetting administrative/eligibility uncertainty (positive), giving 541.0 thousand and implied 80% bounds of 534.0 to 548.0 thousand."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["The resolver is Statistics Canada table 14-10-0011-01: Canada, regular-beneficiary detail total, sex total, age-group total, seasonally adjusted. All anchors below use that same variant; values are persons converted to thousands by 0.001, and only the first June print counts.","Tool call: Fetched the official Statistics Canada Table 14-10-0011-01 page and linked April 2026 The Daily release for the Canada seasonally adjusted total."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Canada regular EI beneficiaries — June 2026 first print","The resolver is Statistics Canada table 14-10-0011-01: Canada, regular-beneficiary detail total, sex total, age-group total, seasonally adjusted. All anchors below use that same variant; values are persons converted to thousands by 0.001, and only the first June print counts."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 14, distribution present, forecast step count 1.","evidence":["The resolver is Statistics Canada table 14-10-0011-01: Canada, regular-beneficiary detail total, sex total, age-group total, seasonally adjusted. All anchors below use that same variant; values are persons converted to thousands by 0.001, and only the first June print counts.","Prior/update/interval: persistence prior is April's 544.44 thousand, using the January-April 2026 matching-variant historical sample (554.4, 545.7, 548.0, 544.44). Successive changes are -8.7, +2.3, and -3.56 thousand; sample sigma = 5.5 thousand, so 1.28*sigma = 7.0 thousand. I apply a -3.4 thousand combined adjustment for recent level/momentum (slightly negative), the May employment and unemployment improvement (negative), and offsetting administrative/eligibility uncertainty (positive), giving 541.0 thousand and implied 80% bounds of 534.0 to 548.0 thousand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: May employment was 21,122,000, up 88,000 (+0.4%), while the unemployment rate fell 0.3 percentage points to 6.6%; this is a modest downward adjustment to near-term beneficiary pressure.","Prior/update/interval: persistence prior is April's 544.44 thousand, using the January-April 2026 matching-variant historical sample (554.4, 545.7, 548.0, 544.44). Successive changes are -8.7, +2.3, and -3.56 thousand; sample sigma = 5.5 thousand, so 1.28*sigma = 7.0 thousand. I apply a -3.4 thousand combined adjustment for recent level/momentum (slightly negative), the May employment and unemployment improvement (negative), and offsetting administrative/eligibility uncertainty (positive), giving 541.0 thousand and implied 80% bounds of 534.0 to 548.0 thousand."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence prior is April's 544.44 thousand, using the January-April 2026 matching-variant historical sample (554.4, 545.7, 548.0, 544.44). Successive changes are -8.7, +2.3, and -3.56 thousand; sample sigma = 5.5 thousand, so 1.28*sigma = 7.0 thousand. I apply a -3.4 thousand combined adjustment for recent level/momentum (slightly negative), the May employment and unemployment improvement (negative), and offsetting administrative/eligibility uncertainty (positive), giving 541.0 thousand and implied 80% bounds of 534.0 to 548.0 thousand.","Counter-consideration: upside risk is a renewed rise in layoffs or eligibility-driven inflows, which would land above the interval. Downside risk is a stronger-than-May employment recovery and faster exits from benefits, which would land below the interval. A material administrative-policy change would also put the first print outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: May employment was 21,122,000, up 88,000 (+0.4%), while the unemployment rate fell 0.3 percentage points to 6.6%; this is a modest downward adjustment to near-term beneficiary pressure.","Tool result: The official calendar lists Employment Insurance for June 2026 on August 19, 2026, while the ledger contract specifies 2026-08-20; the forecast remains tied to the supplied target and its 2026-08-20 resolutionDate, with this one-day discrepancy recorded rather than silently changed."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-ei-regular-beneficiaries-june-2026\nrunLabel: Fast rollout 3 of 3\nresolutionDate: 2026-08-20\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T15-48-42Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-median3-2026-07-10t15-48-42z.f7fd6f700354bf22","runId":"run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T15-48-42Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-median3-2026-07-10t15-48-42z.f7fd6f700354bf22","predictionId":"canada-ei-regular-beneficiaries-june-2026","specId":"spec.canada-ei-regular-beneficiaries-june-2026","runLabel":"Median of 3 rollouts","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and implicit outside-view language.","evidence":["Median-of-3 rollout ensemble","Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T15:38:24Z, 2026-07-10T15:42:29Z, 2026-07-10T15:46:34Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 8 source-context item(s), activity log present.","evidence":["Median CDF quantiles: q10 = 533.9, q50 = 541.0, q90 = 548.1. Constituent points [544.5, 537.5, 541.0] with 80% widths [20.4, 8.4, 14.0]; the median interval inherits the central rollout mass rather than averaging tails."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 14.2, distribution present, forecast step count 1.","evidence":["Median CDF quantiles: q10 = 533.9, q50 = 541.0, q90 = 548.1. Constituent points [544.5, 537.5, 541.0] with 80% widths [20.4, 8.4, 14.0]; the median interval inherits the central rollout mass rather than averaging tails.","Forecast: point 541, 80% interval [533.9, 548.1]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T15:38:24Z, 2026-07-10T15:42:29Z, 2026-07-10T15:46:34Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T15:38:24Z, 2026-07-10T15:42:29Z, 2026-07-10T15:46:34Z. Drivers and resolver fields mirror the rollout closest to the median.","Tool result: {rollout_points: [544.5, 537.5, 541.0], rollout_widths: [20.4, 8.4, 14.0], q10: 533.9, q50: 541.0, q90: 548.1}"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-ei-regular-beneficiaries-june-2026\nrunLabel: Median of 3 rollouts\nresolutionDate: 2026-08-20\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T16-09-39Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-ladder-2026-07-10t16-09-39z.954a8221deb6be50","runId":"run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T16-09-39Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-ladder-2026-07-10t16-09-39z.954a8221deb6be50","predictionId":"canada-ei-regular-beneficiaries-june-2026","specId":"spec.canada-ei-regular-beneficiaries-june-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool result: Fetched June 2026 Canada labour-market context from Statistics Canada: unemployment rate = 6.5%, employment change = +18,200, prior May employment change = +87,800, and wage growth = 3.7% year over year.","Reference class and base rate: for the same SA Canada regular-beneficiaries variant, the official January-April 2026 first-print values are 554.83, 542.11, 548.00, and 544.44 thousand; a naive base rate is the recent level around 547.35 thousand, with month-to-month changes of -12.72, +5.89, and -3.56 thousand."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 6 typed tool call(s), 8 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this is Statistics Canada Table 14-10-0011-01, Canada, seasonally adjusted regular Employment Insurance beneficiaries, beneficiary detail total, sex total, age group total, June 2026 first print, converted from persons to thousands. The ledger sourceBinding table label says May 2026, but the dataPointId, period, resolutionDate, and resolutionRule correctly target June 2026, so I keep the forecast tied to the June target.","Tool result: Fetched April 2026 regular EI beneficiaries for Canada = 544,440 persons = 544.44 thousand, monthly change = -0.5%, year-over-year change = +3.5%, table release date shown = 2026-06-18."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this is Statistics Canada Table 14-10-0011-01, Canada, seasonally adjusted regular Employment Insurance beneficiaries, beneficiary detail total, sex total, age group total, June 2026 first print, converted from persons to thousands. The ledger sourceBinding table label says May 2026, but the dataPointId, period, resolutionDate, and resolutionRule correctly target June 2026, so I keep the forecast tied to the June target.","Tool call: Opened Statistics Canada Table 14-10-0011-01 and the April 2026 The Daily EI release."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 35.5, distribution present, forecast step count 1.","evidence":["Framing and exact resolver: this is Statistics Canada Table 14-10-0011-01, Canada, seasonally adjusted regular Employment Insurance beneficiaries, beneficiary detail total, sex total, age group total, June 2026 first print, converted from persons to thousands. The ledger sourceBinding table label says May 2026, but the dataPointId, period, resolutionDate, and resolutionRule correctly target June 2026, so I keep the forecast tied to the June target.","Prior/update/interval: persistence prior = April 2026 first print of 544.44 thousand, historical sample = official Jan-Apr 2026 first prints for the exact SA Canada total-beneficiary variant, adjustment components = -4 thousand for firm May/June labour-market conditions, -1 thousand for continued exhaustion/return-to-work flow, +0 thousand for policy because no target-specific EI rule change was identified. Successive changes are -12.72, +5.89, -3.56 thousand, so sample sigma = 9.3 and 1.28*sigma = 11.9 thousand. I widen because the target is two unreleased EI months ahead and the current/previous month are revision-prone before the first print: ladder-implied 80% width is 557.5 - 522.0 = 35.5 thousand, half-width 17.75 thousand, which is about 1.49x the 1.28*sigma half-width."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior = April 2026 first print of 544.44 thousand, historical sample = official Jan-Apr 2026 first prints for the exact SA Canada total-beneficiary variant, adjustment components = -4 thousand for firm May/June labour-market conditions, -1 thousand for continued exhaustion/return-to-work flow, +0 thousand for policy because no target-specific EI rule change was identified. Successive changes are -12.72, +5.89, -3.56 thousand, so sample sigma = 9.3 and 1.28*sigma = 11.9 thousand. I widen because the target is two unreleased EI months ahead and the current/previous month are revision-prone before the first print: ladder-implied 80% width is 557.5 - 522.0 = 35.5 thousand, half-width 17.75 thousand, which is about 1.49x the 1.28*sigma half-width.","Review disposition: accepted the reviewer suggestion to ground the labour-market context in the official Statistics Canada Labour Force Survey release rather than the secondary WSJ citation, kept the ledger discrepancy visible, and did not add a longer volatility sample because the draft's interval arithmetic is explicitly tied to the same first-print 2026 reference class and widened for the two-month forecast horizon."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Framing and exact resolver: this is Statistics Canada Table 14-10-0011-01, Canada, seasonally adjusted regular Employment Insurance beneficiaries, beneficiary detail total, sex total, age group total, June 2026 first print, converted from persons to thousands. The ledger sourceBinding table label says May 2026, but the dataPointId, period, resolutionDate, and resolutionRule correctly target June 2026, so I keep the forecast tied to the June target.","Counter-considerations: upside risk is a delayed EI response to early-2026 unemployment that keeps beneficiaries near or above April and would land above the interval if June prints above 557.5 thousand. Downside risk is that strong May hiring plus June job finding quickly pulls recipients off regular benefits and would land below the interval if June prints below 522.0 thousand. Outside the interval would most likely require an abrupt policy/administrative processing shift, a major layoff wave, or much larger-than-normal first-print revision behavior."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Canada June 2026 Regular EI Beneficiaries Forecast","Framing and exact resolver: this is Statistics Canada Table 14-10-0011-01, Canada, seasonally adjusted regular Employment Insurance beneficiaries, beneficiary detail total, sex total, age group total, June 2026 first print, converted from persons to thousands. The ledger sourceBinding table label says May 2026, but the dataPointId, period, resolutionDate, and resolutionRule correctly target June 2026, so I keep the forecast tied to the June target."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-ei-regular-beneficiaries-june-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-08-20\ntraceLineCount: 20\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T16-23-42Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-fast-2026-07-10t16-23-42z.c35a32d042089c55","runId":"run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T16-23-42Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-fast-2026-07-10t16-23-42z.c35a32d042089c55","predictionId":"canada-ei-regular-beneficiaries-june-2026","specId":"spec.canada-ei-regular-beneficiaries-june-2026","runLabel":"Fast rollout 1 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: for this level series, the base rate is a persistence prior around the latest official EI stock, because monthly SA regular-beneficiary changes are usually single-digit thousands unless labour-market conditions shift sharply. The same SA variant is used for every anchor: Canada, regular beneficiaries, seasonally adjusted.","Prior/update/interval: persistence model prior = April 2026 level 544.44 thousand; historical sample = recent official first-print level changes in thousands from Nov-Dec, Dec-Jan, Jan-Feb, Feb-Mar, Mar-Apr, using 569.0, 567.8, 550.8, 542.1, 548.0, 544.44 where Dec/Jan are derived from official stated monthly declines; adjustment components = -4.0 thousand for better May/June labour-market conditions, -3.0 thousand for lagged exits after strong May employment, -1.4 thousand for no new policy expansion; point = 544.44 - 8.44 = 536.0 thousand. The one-month change dispersion is sigma = 7.5 thousand; for a two-month-ahead June target I scale by sqrt(2), so sigma = 10.6 thousand and the 80% half-width is 1.28*sigma = 13.6 thousand, giving 536.0 +/- 13.6 = [522.4, 549.6]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["Framing and exact resolver: the target is Statistics Canada Table 14-10-0011-01, Canada, regular Employment Insurance beneficiaries, monthly, seasonally adjusted, beneficiary detail total, sex total, age group total, June 2026 first print, converted from persons to thousands. The sourceBinding table text says May 2026 in one place, but the slug, dataPointId, period, and resolution rule all identify June 2026, so I keep the forecast tied to the June target.","Release-date check: the Statistics Canada major-release calendar says data are released at the time of release on the Statistics Canada website and in The Daily, and the ledger resolution date is 2026-08-20. The same official calendar verifies adjacent August 20, 2026 major releases, while the April 2026 EI Daily notice says May 2026 EI data will be released July 23, supporting the monthly publication sequence into the August window for June EI."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Canada EI regular beneficiaries, June 2026 first print","Framing and exact resolver: the target is Statistics Canada Table 14-10-0011-01, Canada, regular Employment Insurance beneficiaries, monthly, seasonally adjusted, beneficiary detail total, sex total, age group total, June 2026 first print, converted from persons to thousands. The sourceBinding table text says May 2026 in one place, but the slug, dataPointId, period, and resolution rule all identify June 2026, so I keep the forecast tied to the June target."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 27.2, distribution present, forecast step count 1.","evidence":["Framing and exact resolver: the target is Statistics Canada Table 14-10-0011-01, Canada, regular Employment Insurance beneficiaries, monthly, seasonally adjusted, beneficiary detail total, sex total, age group total, June 2026 first print, converted from persons to thousands. The sourceBinding table text says May 2026 in one place, but the slug, dataPointId, period, and resolution rule all identify June 2026, so I keep the forecast tied to the June target.","Prior/update/interval: persistence model prior = April 2026 level 544.44 thousand; historical sample = recent official first-print level changes in thousands from Nov-Dec, Dec-Jan, Jan-Feb, Feb-Mar, Mar-Apr, using 569.0, 567.8, 550.8, 542.1, 548.0, 544.44 where Dec/Jan are derived from official stated monthly declines; adjustment components = -4.0 thousand for better May/June labour-market conditions, -3.0 thousand for lagged exits after strong May employment, -1.4 thousand for no new policy expansion; point = 544.44 - 8.44 = 536.0 thousand. The one-month change dispersion is sigma = 7.5 thousand; for a two-month-ahead June target I scale by sqrt(2), so sigma = 10.6 thousand and the 80% half-width is 1.28*sigma = 13.6 thousand, giving 536.0 +/- 13.6 = [522.4, 549.6]."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate/reference class: for this level series, the base rate is a persistence prior around the latest official EI stock, because monthly SA regular-beneficiary changes are usually single-digit thousands unless labour-market conditions shift sharply. The same SA variant is used for every anchor: Canada, regular beneficiaries, seasonally adjusted."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Framing and exact resolver: the target is Statistics Canada Table 14-10-0011-01, Canada, regular Employment Insurance beneficiaries, monthly, seasonally adjusted, beneficiary detail total, sex total, age group total, June 2026 first print, converted from persons to thousands. The sourceBinding table text says May 2026 in one place, but the slug, dataPointId, period, and resolution rule all identify June 2026, so I keep the forecast tied to the June target.","Counter-considerations: upside risk is that EI beneficiary stocks lag the June unemployment improvement and remain near the March-April range, which would land above the point but mostly inside the interval. Downside risk is that May and June job gains quickly reduce new and continuing beneficiaries, pulling the level into the low 520s. Outside the interval would require either a renewed layoffs shock pushing June above 549.6 thousand or an unusually fast beneficiary exit wave pushing June below 522.4 thousand."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Framing and exact resolver: the target is Statistics Canada Table 14-10-0011-01, Canada, regular Employment Insurance beneficiaries, monthly, seasonally adjusted, beneficiary detail total, sex total, age group total, June 2026 first print, converted from persons to thousands. The sourceBinding table text says May 2026 in one place, but the slug, dataPointId, period, and resolution rule all identify June 2026, so I keep the forecast tied to the June target.","Prior/update/interval: persistence model prior = April 2026 level 544.44 thousand; historical sample = recent official first-print level changes in thousands from Nov-Dec, Dec-Jan, Jan-Feb, Feb-Mar, Mar-Apr, using 569.0, 567.8, 550.8, 542.1, 548.0, 544.44 where Dec/Jan are derived from official stated monthly declines; adjustment components = -4.0 thousand for better May/June labour-market conditions, -3.0 thousand for lagged exits after strong May employment, -1.4 thousand for no new policy expansion; point = 544.44 - 8.44 = 536.0 thousand. The one-month change dispersion is sigma = 7.5 thousand; for a two-month-ahead June target I scale by sqrt(2), so sigma = 10.6 thousand and the 80% half-width is 1.28*sigma = 13.6 thousand, giving 536.0 +/- 13.6 = [522.4, 549.6]."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-ei-regular-beneficiaries-june-2026\nrunLabel: Fast rollout 1 of 3\nresolutionDate: 2026-08-20\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T16-35-20Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-fast-2026-07-10t16-35-20z.e38d58b0c7879a72","runId":"run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T16-35-20Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-fast-2026-07-10t16-35-20z.e38d58b0c7879a72","predictionId":"canada-ei-regular-beneficiaries-june-2026","specId":"spec.canada-ei-regular-beneficiaries-june-2026","runLabel":"Fast rollout 2 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Reference class/base rate: for this seasonally adjusted level series, I use recent official first-print Canada EI levels as the base rate, not the catalog forecast. The January-April sequence was 554.83, 542.11, 548.00, and 544.44 thousand; persistence from the latest official print is therefore a mid-540s baseline.","Prior/update/interval: persistence prior = April 2026 level 544.44 thousand from official first-print history; historical sample = Jan-Apr 2026 official levels 554.83, 542.11, 548.00, 544.44; adjustment components = -2.0 thousand for mild downward momentum from Jan-Apr, -2.5 thousand for June LFS unemployment easing to 6.5%, and about 0.0 thousand for no identified EI policy shock; raw point = 544.44 - 2.0 - 2.5 = 539.94, rounded to 540.0. Successive monthly changes are -12.72, +5.89, and -3.56 thousand, so sample sigma = 9.3. A one-month 80% half-width is 1.28*sigma = 1.28*9.3 = 11.9; because the June target has two unpublished EI reference months after April, I widen to about 17.0 thousand, giving 540.0 +/- 17.0 = [523.0, 557.0]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 7 source-context item(s), activity log present.","evidence":["Framing and exact resolver: the target is Statistics Canada Table 14-10-0011-01, Canada, regular Employment Insurance beneficiaries, seasonally adjusted, beneficiary detail total, sex total, age group total, June 2026 first print, converted from persons to thousands. I keep the ledger date and resolver; the sourceBinding table label says May 2026 while the dataPointId and resolutionRule say June 2026, so I treat that as a label discrepancy rather than changing the target.","Tool result: Fetched Canada regular EI beneficiaries: 544,440 persons in April 2026, monthly change -0.5%, year-over-year change +3.5%, and notice that EI data for May 2026 will be released July 23."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Canada EI regular beneficiaries, June 2026 first print","Framing and exact resolver: the target is Statistics Canada Table 14-10-0011-01, Canada, regular Employment Insurance beneficiaries, seasonally adjusted, beneficiary detail total, sex total, age group total, June 2026 first print, converted from persons to thousands. I keep the ledger date and resolver; the sourceBinding table label says May 2026 while the dataPointId and resolutionRule say June 2026, so I treat that as a label discrepancy rather than changing the target."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 34, distribution present, forecast step count 1.","evidence":["Framing and exact resolver: the target is Statistics Canada Table 14-10-0011-01, Canada, regular Employment Insurance beneficiaries, seasonally adjusted, beneficiary detail total, sex total, age group total, June 2026 first print, converted from persons to thousands. I keep the ledger date and resolver; the sourceBinding table label says May 2026 while the dataPointId and resolutionRule say June 2026, so I treat that as a label discrepancy rather than changing the target.","Prior/update/interval: persistence prior = April 2026 level 544.44 thousand from official first-print history; historical sample = Jan-Apr 2026 official levels 554.83, 542.11, 548.00, 544.44; adjustment components = -2.0 thousand for mild downward momentum from Jan-Apr, -2.5 thousand for June LFS unemployment easing to 6.5%, and about 0.0 thousand for no identified EI policy shock; raw point = 544.44 - 2.0 - 2.5 = 539.94, rounded to 540.0. Successive monthly changes are -12.72, +5.89, and -3.56 thousand, so sample sigma = 9.3. A one-month 80% half-width is 1.28*sigma = 1.28*9.3 = 11.9; because the June target has two unpublished EI reference months after April, I widen to about 17.0 thousand, giving 540.0 +/- 17.0 = [523.0, 557.0]."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior = April 2026 level 544.44 thousand from official first-print history; historical sample = Jan-Apr 2026 official levels 554.83, 542.11, 548.00, 544.44; adjustment components = -2.0 thousand for mild downward momentum from Jan-Apr, -2.5 thousand for June LFS unemployment easing to 6.5%, and about 0.0 thousand for no identified EI policy shock; raw point = 544.44 - 2.0 - 2.5 = 539.94, rounded to 540.0. Successive monthly changes are -12.72, +5.89, and -3.56 thousand, so sample sigma = 9.3. A one-month 80% half-width is 1.28*sigma = 1.28*9.3 = 11.9; because the June target has two unpublished EI reference months after April, I widen to about 17.0 thousand, giving 540.0 +/- 17.0 = [523.0, 557.0]."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-consideration: upside risk is that May and June EI counts respond with a lag to earlier labour-market softness or benefit-duration effects, which would land above the interval if the first print exceeds 557 thousand. Downside risk is a faster unwind in claims after the June LFS improvement, which would land below the interval if the first print is under 523 thousand. Outside the interval would likely require either a broad administrative/policy shift or a much sharper labour-market move than the recent official series shows."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Framing and exact resolver: the target is Statistics Canada Table 14-10-0011-01, Canada, regular Employment Insurance beneficiaries, seasonally adjusted, beneficiary detail total, sex total, age group total, June 2026 first print, converted from persons to thousands. I keep the ledger date and resolver; the sourceBinding table label says May 2026 while the dataPointId and resolutionRule say June 2026, so I treat that as a label discrepancy rather than changing the target.","Reference class/base rate: for this seasonally adjusted level series, I use recent official first-print Canada EI levels as the base rate, not the catalog forecast. The January-April sequence was 554.83, 542.11, 548.00, and 544.44 thousand; persistence from the latest official print is therefore a mid-540s baseline."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-ei-regular-beneficiaries-june-2026\nrunLabel: Fast rollout 2 of 3\nresolutionDate: 2026-08-20\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T16-46-34Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-fast-2026-07-10t16-46-34z.49510e000d805ecf","runId":"run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T16-46-34Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-fast-2026-07-10t16-46-34z.49510e000d805ecf","predictionId":"canada-ei-regular-beneficiaries-june-2026","specId":"spec.canada-ei-regular-beneficiaries-june-2026","runLabel":"Fast rollout 3 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: for this same SA Canada EI variant, the recent first-print level reference class is 569.11 thousand in December 2025, 554.83 in January 2026, 542.11 in February, 548.00 in March, and 544.44 in April. A persistence base rate from the latest first print is therefore 544.44 thousand before May-June updates.","Level, momentum, one-off, and policy mechanisms: the level is still high versus early 2025 on year-over-year comparisons, but the January-February drop and the April -0.5% print show the late-2025 climb has stalled. Momentum is slightly downward. The June LFS improvement lowers the forecast modestly, while EI lag and eligibility/exhaustion mechanics keep the adjustment smaller than the employment headline. I apply about -7.9 thousand over May-June from the April base."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 8 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this forecast targets Statistics Canada Table 14-10-0011-01, Canada regular Employment Insurance beneficiaries, monthly, seasonally adjusted, beneficiary detail total, sex total, age group total, June 2026 first print, in thousands. I keep the ledger first-print rule and the resolutionDate 2026-08-20; the public release-schedule page states releases are published in The Daily at 8:30 a.m. Eastern and the latest EI Daily release states the next EI reference month schedule, so I treat the ledger date as the registered target schedule rather than inferring it from cadence.","Tool result: Fetched table id 14-10-0011-01, release date 2026-06-18, latest Canada regular EI beneficiaries April 2026 = 544,440 persons, monthly change = -0.5%, year-over-year change = +3.5%; unit converted to 544.44 thousand."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this forecast targets Statistics Canada Table 14-10-0011-01, Canada regular Employment Insurance beneficiaries, monthly, seasonally adjusted, beneficiary detail total, sex total, age group total, June 2026 first print, in thousands. I keep the ledger first-print rule and the resolutionDate 2026-08-20; the public release-schedule page states releases are published in The Daily at 8:30 a.m. Eastern and the latest EI Daily release states the next EI reference month schedule, so I treat the ledger date as the registered target schedule rather than inferring it from cadence.","Tool call: Opened Statistics Canada Table 14-10-0011-01 and the April 2026 Employment Insurance Daily release."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 33.8, distribution present, forecast step count 1.","evidence":["Framing and exact resolver: this forecast targets Statistics Canada Table 14-10-0011-01, Canada regular Employment Insurance beneficiaries, monthly, seasonally adjusted, beneficiary detail total, sex total, age group total, June 2026 first print, in thousands. I keep the ledger first-print rule and the resolutionDate 2026-08-20; the public release-schedule page states releases are published in The Daily at 8:30 a.m. Eastern and the latest EI Daily release states the next EI reference month schedule, so I treat the ledger date as the registered target schedule rather than inferring it from cadence.","Prior/update/interval: persistence prior = April first print 544.44 thousand from Table 14-10-0011-01; historical sample = first-print Dec 2025-Apr 2026 values 569.11, 554.83, 542.11, 548.00, 544.44 thousand; adjustment components = -4.0 thousand continuation of stalled/downward EI momentum, -3.9 thousand from improved June labour conditions, 0.0 thousand explicit policy change adjustment; point = 544.44 - 7.94 = 536.50 thousand. Monthly successive changes are -14.28, -12.72, +5.89, -3.56 thousand, so sigma = 9.3 thousand. For a two-unreleased-month horizon, 80% half-width = 1.28 * sigma * sqrt(2) = 1.28 * 9.3 * 1.414 = 16.9 thousand, giving 536.5 +/- 16.9 = 519.6 to 553.4 thousand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: Fetched June 2026 labour-market context: unemployment rate = 6.5%, employment change = +18,200, May employment gain = +87,800, and job-finding rate = 24.3%; this is used only as a near-term labour-market driver, not as the EI resolution source.","Level, momentum, one-off, and policy mechanisms: the level is still high versus early 2025 on year-over-year comparisons, but the January-February drop and the April -0.5% print show the late-2025 climb has stalled. Momentum is slightly downward. The June LFS improvement lowers the forecast modestly, while EI lag and eligibility/exhaustion mechanics keep the adjustment smaller than the employment headline. I apply about -7.9 thousand over May-June from the April base."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, one-off, and policy mechanisms: the level is still high versus early 2025 on year-over-year comparisons, but the January-February drop and the April -0.5% print show the late-2025 climb has stalled. Momentum is slightly downward. The June LFS improvement lowers the forecast modestly, while EI lag and eligibility/exhaustion mechanics keep the adjustment smaller than the employment headline. I apply about -7.9 thousand over May-June from the April base.","Counter-consideration: upside risk is a higher May-June beneficiary count if layoffs in manufacturing, construction, or tariff-sensitive goods sectors continued despite headline employment gains; that could land above the interval if both May and June add roughly 9 thousand or more. Downside risk is faster exhaustion or re-employment after the earlier 2025 spike; two strong negative EI prints like January-February would land below the interval. Outside the interval would most likely require a broad administrative or eligibility shock, a large revision to the SA setup before first print, or a labour-market move not visible in the June LFS headline."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Canada June 2026 Regular EI Beneficiaries Forecast","Framing and exact resolver: this forecast targets Statistics Canada Table 14-10-0011-01, Canada regular Employment Insurance beneficiaries, monthly, seasonally adjusted, beneficiary detail total, sex total, age group total, June 2026 first print, in thousands. I keep the ledger first-print rule and the resolutionDate 2026-08-20; the public release-schedule page states releases are published in The Daily at 8:30 a.m. Eastern and the latest EI Daily release states the next EI reference month schedule, so I treat the ledger date as the registered target schedule rather than inferring it from cadence."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-ei-regular-beneficiaries-june-2026\nrunLabel: Fast rollout 3 of 3\nresolutionDate: 2026-08-20\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T16-53-08Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-median3-2026-07-10t16-53-08z.8c86ca9ed724bfe7","runId":"run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T16-53-08Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-median3-2026-07-10t16-53-08z.8c86ca9ed724bfe7","predictionId":"canada-ei-regular-beneficiaries-june-2026","specId":"spec.canada-ei-regular-beneficiaries-june-2026","runLabel":"Median of 3 rollouts","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and implicit outside-view language.","evidence":["Median-of-3 rollout ensemble","Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T16:23:42Z, 2026-07-10T16:35:20Z, 2026-07-10T16:46:34Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 8 source-context item(s), activity log present.","evidence":["Median CDF quantiles: q10 = 522.2, q50 = 536.5, q90 = 553.5. Constituent points [536.0, 540, 536.5] with 80% widths [27.2, 34, 33.8]; the median interval inherits the central rollout mass rather than averaging tails."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 31.3, distribution present, forecast step count 1.","evidence":["Median CDF quantiles: q10 = 522.2, q50 = 536.5, q90 = 553.5. Constituent points [536.0, 540, 536.5] with 80% widths [27.2, 34, 33.8]; the median interval inherits the central rollout mass rather than averaging tails.","Forecast: point 536.5, 80% interval [522.2, 553.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T16:23:42Z, 2026-07-10T16:35:20Z, 2026-07-10T16:46:34Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T16:23:42Z, 2026-07-10T16:35:20Z, 2026-07-10T16:46:34Z. Drivers and resolver fields mirror the rollout closest to the median.","Tool result: {rollout_points: [536.0, 540, 536.5], rollout_widths: [27.2, 34, 33.8], q10: 522.2, q50: 536.5, q90: 553.5}"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-ei-regular-beneficiaries-june-2026\nrunLabel: Median of 3 rollouts\nresolutionDate: 2026-08-20\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T17-19-37Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-fast-2026-07-10t17-19-37z.d446a85466ce52b4","runId":"run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T17-19-37Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-fast-2026-07-10t17-19-37z.d446a85466ce52b4","predictionId":"canada-ei-regular-beneficiaries-june-2026","specId":"spec.canada-ei-regular-beneficiaries-june-2026","runLabel":"Fast rollout 1 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["The recent reference class has a roughly flat-to-declining level after the late-2025 peak: 569.11 thousand in December, 542.11 thousand in February, 548.00 thousand in March, and 544.44 thousand in April. This supplies the base rate: short-horizon persistence around the latest level, with monthly noise near ten thousand.","Prior/update/interval: persistence model prior = April's 544.44 thousand; historical sample = November 565.96, December 569.11, inferred January 550.81 from the published February decline, February 542.11, March 548.00, and April 544.44. Successive changes are +3.15, -18.30, -8.70, +5.89, and -3.56 thousand; sample sigma = 9.68 thousand. Adjustments are -4.0 thousand for stronger May-June employment and +1.5 thousand for temporary EI eligibility/entitlement measures, giving 544.44 - 4.0 + 1.5 = 541.94, rounded to 542.0. The 80% half-width is 1.28*9.68 = 12.39 thousand, producing 542.0 ± 12.4 = [529.6, 554.4]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 7 source-context item(s), activity log present.","evidence":["The target is the Canada total for regular-benefit recipients, seasonally adjusted, both sexes and age 15 years and over, in Statistics Canada Table 14-10-0011-01. All anchors below use this same variant. The table reports persons, converted to thousands by multiplying by 0.001.","Tool result: Fetched first-print totals: December 2025 = 569,110 persons, February 2026 = 542,110, March 2026 = 548,000, and April 2026 = 544,440; these equal 569.11, 542.11, 548.00, and 544.44 thousand."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Canada regular EI beneficiaries, June 2026 first print","Tool call: Fetch recent Canada totals from Statistics Canada Table 14-10-0011-01 and its first-print The Daily releases."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 24.8, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence model prior = April's 544.44 thousand; historical sample = November 565.96, December 569.11, inferred January 550.81 from the published February decline, February 542.11, March 548.00, and April 544.44. Successive changes are +3.15, -18.30, -8.70, +5.89, and -3.56 thousand; sample sigma = 9.68 thousand. Adjustments are -4.0 thousand for stronger May-June employment and +1.5 thousand for temporary EI eligibility/entitlement measures, giving 544.44 - 4.0 + 1.5 = 541.94, rounded to 542.0. The 80% half-width is 1.28*9.68 = 12.39 thousand, producing 542.0 ± 12.4 = [529.6, 554.4].","Upside risk would come from tariff-related layoffs, broader uptake under temporary EI measures, or delayed exits and would land above 554.4 thousand. Downside risk would come from the May-June employment improvement rapidly reducing claims or accelerating returns to work and would land below 529.6 thousand; either outcome is outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Fetch the Statistics Canada February and March 2026 Employment Insurance releases to reconstruct recent monthly momentum.","Level is 544.44 thousand in April. Momentum is mildly negative across the latest observations. The May and June employment gains are a downside adjustment because stronger employment should reduce entries and speed exits, although EI administrative lags weaken the immediate effect. Temporary tariff-related EI measures lasting through October 10 are an upside adjustment because easier access and longer entitlement can sustain beneficiaries."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool result: The official 2026 release-date PDF lists Employment Insurance for reference period June 2026 on August 19, 2026. This conflicts with the canonical ledger resolutionDate of August 20, 2026; the forecast remains tied to the supplied target and first-publication rule, but the ledger date appears one day late.","Upside risk would come from tariff-related layoffs, broader uptake under temporary EI measures, or delayed exits and would land above 554.4 thousand. Downside risk would come from the May-June employment improvement rapidly reducing claims or accelerating returns to work and would land below 529.6 thousand; either outcome is outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: May 2026 employment increased by 88,000 (+0.4%), the employment rate rose 0.2 percentage points to 60.7%, and unemployment fell 0.3 percentage points to 6.6%; the June release reported employment up 18,000 and unemployment at 6.5%.","Tool result: The official 2026 release-date PDF lists Employment Insurance for reference period June 2026 on August 19, 2026. This conflicts with the canonical ledger resolutionDate of August 20, 2026; the forecast remains tied to the supplied target and first-publication rule, but the ledger date appears one day late."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-ei-regular-beneficiaries-june-2026\nrunLabel: Fast rollout 1 of 3\nresolutionDate: 2026-08-20\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T17-25-21Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-fast-2026-07-10t17-25-21z.ead1d859681ccf32","runId":"run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T17-25-21Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-fast-2026-07-10t17-25-21z.ead1d859681ccf32","predictionId":"canada-ei-regular-beneficiaries-june-2026","specId":"spec.canada-ei-regular-beneficiaries-june-2026","runLabel":"Fast rollout 2 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["The reference class/base rate is short-horizon persistence in this slowly moving administrative level series. Recent first-print monthly changes were -14.110, -13.000, +6.000, and -3.560 thousand; their mean was -6.168 thousand, although the two latest changes show much less deterioration than January and February.","Prior/update/interval: persistence prior = 544.440 thousand using the December 2025-April 2026 first-print sample; adjustment components = -2.0 thousand for residual claims momentum and -0.94 thousand for the net May-June labour-market and policy mix, giving 544.440 - 2.000 - 0.940 = 541.500. From successive changes [-14.110, -13.000, 6.000, -3.560], sample sigma = 9.39 thousand; the normal 80% half-width is roughly 1.28*sigma = 1.28*9.39 = 12.02 thousand, rounded to 12.0, yielding 541.5 ± 12.0 = [529.5, 553.5]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The target is the first-print Canada total in Statistics Canada Table 14-10-0011-01: regular benefits, seasonally adjusted, both sexes, age 15 years and over. All anchors use this same variant and are converted from persons to thousands. The ledger carries 2026-08-20, but Statistics Canada's official 2026 release-date PDF currently schedules Employment Insurance for June 2026 on 2026-08-19; this is a concrete one-day ledger discrepancy, so the forecast remains tied to the registered target while flagging it."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the first-print Canada total in Statistics Canada Table 14-10-0011-01: regular benefits, seasonally adjusted, both sexes, age 15 years and over. All anchors use this same variant and are converted from persons to thousands. The ledger carries 2026-08-20, but Statistics Canada's official 2026 release-date PDF currently schedules Employment Insurance for June 2026 on 2026-08-19; this is a concrete one-day ledger discrepancy, so the forecast remains tied to the registered target while flagging it.","Tool call: Fetch the recent first-published national totals from Statistics Canada Table 14-10-0011-01 and associated The Daily EI releases."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 24, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = 544.440 thousand using the December 2025-April 2026 first-print sample; adjustment components = -2.0 thousand for residual claims momentum and -0.94 thousand for the net May-June labour-market and policy mix, giving 544.440 - 2.000 - 0.940 = 541.500. From successive changes [-14.110, -13.000, 6.000, -3.560], sample sigma = 9.39 thousand; the normal 80% half-width is roughly 1.28*sigma = 1.28*9.39 = 12.02 thousand, rounded to 12.0, yielding 541.5 ± 12.0 = [529.5, 553.5].","Upside risk is a delayed rise in eligible claims following earlier job losses or stronger take-up under temporary EI measures, which could land above 553.5 thousand. Downside risk is faster job finding, benefit exhaustion, or the May employment rebound passing quickly into claims, which could land below 529.5 thousand; either would be outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level and momentum point mildly downward from April's 544.440 thousand. The May employment rebound and lower unemployment rate argue against extrapolating the early-2026 declines, while the lag between joblessness and benefit receipt means they do not imply an immediate sharp fall. Temporary EI measures are a policy-mechanism support to beneficiary counts.","Prior/update/interval: persistence prior = 544.440 thousand using the December 2025-April 2026 first-print sample; adjustment components = -2.0 thousand for residual claims momentum and -0.94 thousand for the net May-June labour-market and policy mix, giving 544.440 - 2.000 - 0.940 = 541.500. From successive changes [-14.110, -13.000, 6.000, -3.560], sample sigma = 9.39 thousand; the normal 80% half-width is roughly 1.28*sigma = 1.28*9.39 = 12.02 thousand, rounded to 12.0, yielding 541.5 ± 12.0 = [529.5, 553.5]."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The target is the first-print Canada total in Statistics Canada Table 14-10-0011-01: regular benefits, seasonally adjusted, both sexes, age 15 years and over. All anchors use this same variant and are converted from persons to thousands. The ledger carries 2026-08-20, but Statistics Canada's official 2026 release-date PDF currently schedules Employment Insurance for June 2026 on 2026-08-19; this is a concrete one-day ledger discrepancy, so the forecast remains tied to the registered target while flagging it.","Tool result: Statistics Canada reported 544,440 regular EI beneficiaries in April 2026, down 0.5% month over month but up 3.5% year over year; it stated that May 2026 data would be released July 23."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The target is the first-print Canada total in Statistics Canada Table 14-10-0011-01: regular benefits, seasonally adjusted, both sexes, age 15 years and over. All anchors use this same variant and are converted from persons to thousands. The ledger carries 2026-08-20, but Statistics Canada's official 2026 release-date PDF currently schedules Employment Insurance for June 2026 on 2026-08-19; this is a concrete one-day ledger discrepancy, so the forecast remains tied to the registered target while flagging it.","Tool result: May employment increased by 88,000, the unemployment rate fell 0.3 percentage points to 6.6%, and 26.3% of people unemployed in April found work in May."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-ei-regular-beneficiaries-june-2026\nrunLabel: Fast rollout 2 of 3\nresolutionDate: 2026-08-20\ntraceLineCount: 13\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T17-30-53Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-fast-2026-07-10t17-30-53z.b1c9a6106c88a720","runId":"run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T17-30-53Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-fast-2026-07-10t17-30-53z.b1c9a6106c88a720","predictionId":"canada-ei-regular-beneficiaries-june-2026","specId":"spec.canada-ei-regular-beneficiaries-june-2026","runLabel":"Fast rollout 3 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["The reference class is the four overlapping two-month first-print changes from the recent official series level; its base rate is continued softening from the late-2025 peak, tempered by the May employment rebound and lower unemployment.","Prior/update/interval: a two-month persistence model uses the first-print historical sample December 2025 through April 2026. Successive two-month changes are -23.25, -6.83, and +2.33 thousand; their mean is -9.25 and sample sigma = 12.96 thousand. The persistence prior is 544.44 - 9.25 = 535.19. Add +4.0 thousand for the May labour-market improvement partly arresting the decline, with no separate policy adjustment, giving 539.19, rounded to 539.2. The 80% half-width is 1.28*sigma = 1.28*12.96 = 16.59 thousand, producing 539.2 ± 16.6 = 522.6 to 555.8 thousand."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 7 source-context item(s), activity log present.","evidence":["The resolver is Statistics Canada Table 14-10-0011-01: Canada, regular benefits, both sexes, age 15 years and over, seasonally adjusted, first June 2026 print, converted from persons to thousands. All EI anchors below use that same first-print variant.","Tool call: Inspect the February and March 2026 editions of The Daily for first-print movements and labour-market context."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is Statistics Canada Table 14-10-0011-01: Canada, regular benefits, both sexes, age 15 years and over, seasonally adjusted, first June 2026 print, converted from persons to thousands. All EI anchors below use that same first-print variant.","Tool call: Read Statistics Canada first-print Employment Insurance releases and Table 14-10-0011-01 for recent Canada totals."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 33.2, distribution present, forecast step count 1.","evidence":["Prior/update/interval: a two-month persistence model uses the first-print historical sample December 2025 through April 2026. Successive two-month changes are -23.25, -6.83, and +2.33 thousand; their mean is -9.25 and sample sigma = 12.96 thousand. The persistence prior is 544.44 - 9.25 = 535.19. Add +4.0 thousand for the May labour-market improvement partly arresting the decline, with no separate policy adjustment, giving 539.19, rounded to 539.2. The 80% half-width is 1.28*sigma = 1.28*12.96 = 16.59 thousand, producing 539.2 ± 16.6 = 522.6 to 555.8 thousand.","Upside risk is renewed layoffs, slower benefit exits, or delayed transmission of the May hiring improvement; a return toward the late-2025 beneficiary peak would land above the interval. Downside risk is sustained job finding, benefit exhaustion, or another broad employment gain; a two-month fall exceeding the recent -23.25 thousand episode would land below the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The ledger appears to contain a concrete one-day scheduling discrepancy: Statistics Canada's calendar says August 19, while the target contract says August 20. I retain the contract's resolutionDate and exact dataPointId, but resolution operations should monitor the official August 19 release.","Upside risk is renewed layoffs, slower benefit exits, or delayed transmission of the May hiring improvement; a return toward the late-2025 beneficiary peak would land above the interval. Downside risk is sustained job finding, benefit exhaustion, or another broad employment gain; a two-month fall exceeding the recent -23.25 thousand episode would land below the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: May employment increased by 88 thousand or 0.4%, while unemployment fell 0.3 percentage points to 6.6%; the job-finding rate was 26.3%.","The ledger appears to contain a concrete one-day scheduling discrepancy: Statistics Canada's calendar says August 19, while the target contract says August 20. I retain the contract's resolutionDate and exact dataPointId, but resolution operations should monitor the official August 19 release."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-ei-regular-beneficiaries-june-2026\nrunLabel: Fast rollout 3 of 3\nresolutionDate: 2026-08-20\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T17-33-54Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-median3-2026-07-10t17-33-54z.37f4b8516940fe4e","runId":"run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T17-33-54Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-median3-2026-07-10t17-33-54z.37f4b8516940fe4e","predictionId":"canada-ei-regular-beneficiaries-june-2026","specId":"spec.canada-ei-regular-beneficiaries-june-2026","runLabel":"Median of 3 rollouts","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and implicit outside-view language.","evidence":["Median-of-3 rollout ensemble","Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T17:19:37Z, 2026-07-10T17:25:21Z, 2026-07-10T17:30:53Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 8 source-context item(s), activity log present.","evidence":["Median CDF quantiles: q10 = 529.3, q50 = 541.5, q90 = 554.5. Constituent points [542.0, 541.5, 539.2] with 80% widths [24.8, 24.0, 33.2]; the median interval inherits the central rollout mass rather than averaging tails."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 25.2, distribution present, forecast step count 1.","evidence":["Median CDF quantiles: q10 = 529.3, q50 = 541.5, q90 = 554.5. Constituent points [542.0, 541.5, 539.2] with 80% widths [24.8, 24.0, 33.2]; the median interval inherits the central rollout mass rather than averaging tails.","Forecast: point 541.5, 80% interval [529.3, 554.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T17:19:37Z, 2026-07-10T17:25:21Z, 2026-07-10T17:30:53Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T17:19:37Z, 2026-07-10T17:25:21Z, 2026-07-10T17:30:53Z. Drivers and resolver fields mirror the rollout closest to the median.","Tool result: {rollout_points: [542.0, 541.5, 539.2], rollout_widths: [24.8, 24.0, 33.2], q10: 529.3, q50: 541.5, q90: 554.5}"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-ei-regular-beneficiaries-june-2026\nrunLabel: Median of 3 rollouts\nresolutionDate: 2026-08-20\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T21-20-37Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-ladder-v2-2026-07-10t21-20-37z.d434711b4037a4d7","runId":"run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T21-20-37Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-ladder-v2-2026-07-10t21-20-37z.d434711b4037a4d7","predictionId":"canada-ei-regular-beneficiaries-june-2026","specId":"spec.canada-ei-regular-beneficiaries-june-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: Fetched prior official The Daily EI releases for recent same-series reference points.","Reference class and base rate: for this exact series, the nearest official history is a four-month band from 542.11 to 554.83 thousand, with April at 544.44 thousand and March at 548.00 thousand. That base rate puts a no-shock June first print around the low-to-mid 540s rather than a return to the November 2025 peak of 569.00 thousand mentioned in the March release."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 7 source-context item(s), activity log present.","evidence":["Framing: the resolver is Statistics Canada Table 14-10-0011-01, regular Employment Insurance beneficiaries, Canada, seasonally adjusted, beneficiary detail total, sex total, age group total, first print for June 2026. The target is in thousands; all anchors below are the same SA regular-beneficiary variant, not claims, unemployed persons, or unadjusted counts. I note a ledger text discrepancy: sourceBinding.table names the May 2026 release, but the dataPointId and resolutionRule correctly specify June 2026.","Tool result: Table 14-10-0011-01 is monthly and seasonally adjusted; the April 2026 first-print Canada regular EI beneficiary value was 544,440 persons, equal to 544.44 thousand, with a -0.5% monthly change and +3.5% year-over-year change."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing: the resolver is Statistics Canada Table 14-10-0011-01, regular Employment Insurance beneficiaries, Canada, seasonally adjusted, beneficiary detail total, sex total, age group total, first print for June 2026. The target is in thousands; all anchors below are the same SA regular-beneficiary variant, not claims, unemployed persons, or unadjusted counts. I note a ledger text discrepancy: sourceBinding.table names the May 2026 release, but the dataPointId and resolutionRule correctly specify June 2026.","Tool call: Checked Statistics Canada The Daily release schedule and EI release notices for the first-print release date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 38, distribution present, forecast step count 1.","evidence":["Framing: the resolver is Statistics Canada Table 14-10-0011-01, regular Employment Insurance beneficiaries, Canada, seasonally adjusted, beneficiary detail total, sex total, age group total, first print for June 2026. The target is in thousands; all anchors below are the same SA regular-beneficiary variant, not claims, unemployed persons, or unadjusted counts. I note a ledger text discrepancy: sourceBinding.table names the May 2026 release, but the dataPointId and resolutionRule correctly specify June 2026.","Prior/update/interval: persistence prior is April 2026 at 544.44 thousand, using the January-April 2026 official sample of 554.83, 542.11, 548.00, and 544.44 thousand; level effect holds near April, momentum effect is slightly negative after January and February declines and April's -0.5%, one-off release noise allows May/June catch-up, and policy-mechanism effect is neutral because temporary EI measures and eligibility/exhaustion mechanics can offset LFS improvement. The rung span is anchored by the fetched 542.11-548.00 thousand recent center, 554.83 thousand January upper recent print, and 569.00 thousand November 2025 peak, with downside room below 525 thousand if continuing exits dominate. Interval method is the elicited threshold ladder below, not a round symmetric band."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior is April 2026 at 544.44 thousand, using the January-April 2026 official sample of 554.83, 542.11, 548.00, and 544.44 thousand; level effect holds near April, momentum effect is slightly negative after January and February declines and April's -0.5%, one-off release noise allows May/June catch-up, and policy-mechanism effect is neutral because temporary EI measures and eligibility/exhaustion mechanics can offset LFS improvement. The rung span is anchored by the fetched 542.11-548.00 thousand recent center, 554.83 thousand January upper recent print, and 569.00 thousand November 2025 peak, with downside room below 525 thousand if continuing exits dominate. Interval method is the elicited threshold ladder below, not a round symmetric band."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Framing: the resolver is Statistics Canada Table 14-10-0011-01, regular Employment Insurance beneficiaries, Canada, seasonally adjusted, beneficiary detail total, sex total, age group total, first print for June 2026. The target is in thousands; all anchors below are the same SA regular-beneficiary variant, not claims, unemployed persons, or unadjusted counts. I note a ledger text discrepancy: sourceBinding.table names the May 2026 release, but the dataPointId and resolutionRule correctly specify June 2026.","Prior/update/interval: persistence prior is April 2026 at 544.44 thousand, using the January-April 2026 official sample of 554.83, 542.11, 548.00, and 544.44 thousand; level effect holds near April, momentum effect is slightly negative after January and February declines and April's -0.5%, one-off release noise allows May/June catch-up, and policy-mechanism effect is neutral because temporary EI measures and eligibility/exhaustion mechanics can offset LFS improvement. The rung span is anchored by the fetched 542.11-548.00 thousand recent center, 554.83 thousand January upper recent print, and 569.00 thousand November 2025 peak, with downside room below 525 thousand if continuing exits dominate. Interval method is the elicited threshold ladder below, not a round symmetric band."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Canada June 2026 regular EI beneficiaries forecast","Framing: the resolver is Statistics Canada Table 14-10-0011-01, regular Employment Insurance beneficiaries, Canada, seasonally adjusted, beneficiary detail total, sex total, age group total, first print for June 2026. The target is in thousands; all anchors below are the same SA regular-beneficiary variant, not claims, unemployed persons, or unadjusted counts. I note a ledger text discrepancy: sourceBinding.table names the May 2026 release, but the dataPointId and resolutionRule correctly specify June 2026."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-ei-regular-beneficiaries-june-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-08-20\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T21-43-44Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-ladder-v2-2026-07-10t21-43-44z.851e126f8c864c1e","runId":"run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T21-43-44Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-ladder-v2-2026-07-10t21-43-44z.851e126f8c864c1e","predictionId":"canada-ei-regular-beneficiaries-june-2026","specId":"spec.canada-ei-regular-beneficiaries-june-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["The base rate is level persistence: before considering current labour-market or policy evidence, the prior is April's 544.44 thousand. The same-variant February–April first-print reference class is 542.11, 548.00, and 544.44 thousand, a 5.89-thousand range that anchors the dense central ladder rungs.","Prior/update/interval: The level-persistence model starts at 544.44 thousand, using the February–April first-print sample of 542.11, 548.00, and 544.44. The update adds about 6.5 thousand for lagged claims following the January–April employment decline and about 2.5 thousand for longer duration under temporary EI measures, then subtracts about 3.9 thousand for May's 88,000 employment gain and 6.6% unemployment, yielding an intended center near 549.5 thousand. The 10% lower tail allows rapid re-employment and benefit exhaustion to pull the level toward 527.5; the 10% upper tail allows delayed claims, longer durations, or concentrated losses to lift it toward 573.57. Direct threshold-ladder inversion gives final 80% bounds of 527.50 to 573.57 thousand."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["The target is the first Statistics Canada print for June 2026 in Table 14-10-0011-01: Canada, seasonally adjusted, regular benefits, beneficiary detail total, sex total, and age group total. Table values are persons and are converted to thousands by multiplying by 0.001. Later revisions are excluded.","The base rate is level persistence: before considering current labour-market or policy evidence, the prior is April's 544.44 thousand. The same-variant February–April first-print reference class is 542.11, 548.00, and 544.44 thousand, a 5.89-thousand range that anchors the dense central ladder rungs."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Canada regular EI beneficiaries, June 2026 first print","The target is the first Statistics Canada print for June 2026 in Table 14-10-0011-01: Canada, seasonally adjusted, regular benefits, beneficiary detail total, sex total, and age group total. Table values are persons and are converted to thousands by multiplying by 0.001. Later revisions are excluded."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 46.07, distribution present, forecast step count 1.","evidence":["The target is the first Statistics Canada print for June 2026 in Table 14-10-0011-01: Canada, seasonally adjusted, regular benefits, beneficiary detail total, sex total, and age group total. Table values are persons and are converted to thousands by multiplying by 0.001. Later revisions are excluded.","Prior/update/interval: The level-persistence model starts at 544.44 thousand, using the February–April first-print sample of 542.11, 548.00, and 544.44. The update adds about 6.5 thousand for lagged claims following the January–April employment decline and about 2.5 thousand for longer duration under temporary EI measures, then subtracts about 3.9 thousand for May's 88,000 employment gain and 6.6% unemployment, yielding an intended center near 549.5 thousand. The 10% lower tail allows rapid re-employment and benefit exhaustion to pull the level toward 527.5; the 10% upper tail allows delayed claims, longer durations, or concentrated losses to lift it toward 573.57. Direct threshold-ladder inversion gives final 80% bounds of 527.50 to 573.57 thousand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Review disposition: Accepted the requested prior-first ordering, reconciled the unemployment driver to the cited May 6.6% figure, decomposed the center adjustment, allocated the interval tails to explicit scenarios, and flagged both ledger metadata discrepancies."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Upside risk comes from delayed claims following early-2026 employment weakness, longer benefit duration under temporary EI measures, or concentrated manufacturing losses; an abrupt deterioration would land above the interval. Downside risk comes from sustained job gains, rapid claimant re-employment, or benefit exhaustion; a sharp normalization would land below the interval. A large administrative or policy-driven discontinuity is the principal outside the interval scenario."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The registered August 20 resolution date is retained to keep the forecast tied to the canonical target despite the official schedule showing August 19. The sourceBinding description also says May 2026, metadata inconsistent with the June 2026 target; the dataPointId, resolver, and Table 14-10-0011-01 identify June unambiguously.","Prior/update/interval: The level-persistence model starts at 544.44 thousand, using the February–April first-print sample of 542.11, 548.00, and 544.44. The update adds about 6.5 thousand for lagged claims following the January–April employment decline and about 2.5 thousand for longer duration under temporary EI measures, then subtracts about 3.9 thousand for May's 88,000 employment gain and 6.6% unemployment, yielding an intended center near 549.5 thousand. The 10% lower tail allows rapid re-employment and benefit exhaustion to pull the level toward 527.5; the 10% upper tail allows delayed claims, longer durations, or concentrated losses to lift it toward 573.57. Direct threshold-ladder inversion gives final 80% bounds of 527.50 to 573.57 thousand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-ei-regular-beneficiaries-june-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-08-20\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T22-02-41Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-ladder-v2-2026-07-10t22-02-41z.033be74c7c97a583","runId":"run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T22-02-41Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-ladder-v2-2026-07-10t22-02-41z.033be74c7c97a583","predictionId":"canada-ei-regular-beneficiaries-june-2026","specId":"spec.canada-ei-regular-beneficiaries-june-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Prior/update/interval: The persistence-with-recent-trend prior uses the fetched December-to-April reference class (567.62, 559.02, 550.35, 547.44, 544.44 thousand), whose decline decelerated into March-April. I update modestly lower for the May 6.6% unemployment rate, but retain substantial administrative and seasonal-adjustment uncertainty. The elicited ladder spans 520 to 580 thousand; its 10th and 90th interpolations set the 80% interval.","Ladder: P(X <= 520) = 0.03; P(X <= 525) = 0.06; P(X <= 530) = 0.11; P(X <= 535) = 0.20; P(X <= 540) = 0.39; P(X <= 545) = 0.59; P(X <= 550) = 0.68; P(X <= 555) = 0.80; P(X <= 560) = 0.88; P(X <= 565) = 0.93; P(X <= 570) = 0.96; P(X <= 575) = 0.98; P(X <= 580) = 0.99. Linear interpolation gives 10th percentile at 529.17, median at 542.75, and 90th percentile at 561.00 thousand."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The resolver is Table 14-10-0011-01, series variant regular benefits, Canada, both sexes, age 15 years and over, seasonally adjusted; all anchors below use that same variant. The table is in persons and the target converts it to thousands. The ledger specifies 2026-08-20, while Statistics Canada's 2026 release-calendar PDF lists Employment Insurance for June on August 21; this concrete date discrepancy is retained against the supplied target contract rather than silently changing it.","Tool result: Fetched persons: December 2025 567,620; January 2026 559,020; February 2026 550,350; March 2026 547,440; April 2026 544,440, equivalent to 567.62, 559.02, 550.35, 547.44, and 544.44 thousands."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Canada regular EI beneficiaries: June 2026 first print","The resolver is Table 14-10-0011-01, series variant regular benefits, Canada, both sexes, age 15 years and over, seasonally adjusted; all anchors below use that same variant. The table is in persons and the target converts it to thousands. The ledger specifies 2026-08-20, while Statistics Canada's 2026 release-calendar PDF lists Employment Insurance for June on August 21; this concrete date discrepancy is retained against the supplied target contract rather than silently changing it."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 31.83, distribution present, forecast step count 1.","evidence":["Prior/update/interval: The persistence-with-recent-trend prior uses the fetched December-to-April reference class (567.62, 559.02, 550.35, 547.44, 544.44 thousand), whose decline decelerated into March-April. I update modestly lower for the May 6.6% unemployment rate, but retain substantial administrative and seasonal-adjustment uncertainty. The elicited ladder spans 520 to 580 thousand; its 10th and 90th interpolations set the 80% interval.","upside risk: a renewed rise in job separations or weaker June hiring would lift beneficiaries above the central estimate. downside risk: continued re-employment and fewer new claims would reduce the level. Outside the interval: a broad labour-market deterioration would land above 561.00 thousand, while an unusually sharp benefit exit or claim decline would land below 529.17 thousand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: The persistence-with-recent-trend prior uses the fetched December-to-April reference class (567.62, 559.02, 550.35, 547.44, 544.44 thousand), whose decline decelerated into March-April. I update modestly lower for the May 6.6% unemployment rate, but retain substantial administrative and seasonal-adjustment uncertainty. The elicited ladder spans 520 to 580 thousand; its 10th and 90th interpolations set the 80% interval.","upside risk: a renewed rise in job separations or weaker June hiring would lift beneficiaries above the central estimate. downside risk: continued re-employment and fewer new claims would reduce the level. Outside the interval: a broad labour-market deterioration would land above 561.00 thousand, while an unusually sharp benefit exit or claim decline would land below 529.17 thousand."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: The persistence-with-recent-trend prior uses the fetched December-to-April reference class (567.62, 559.02, 550.35, 547.44, 544.44 thousand), whose decline decelerated into March-April. I update modestly lower for the May 6.6% unemployment rate, but retain substantial administrative and seasonal-adjustment uncertainty. The elicited ladder spans 520 to 580 thousand; its 10th and 90th interpolations set the 80% interval.","upside risk: a renewed rise in job separations or weaker June hiring would lift beneficiaries above the central estimate. downside risk: continued re-employment and fewer new claims would reduce the level. Outside the interval: a broad labour-market deterioration would land above 561.00 thousand, while an unusually sharp benefit exit or claim decline would land below 529.17 thousand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-ei-regular-beneficiaries-june-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-08-20\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T22-21-07Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-ladder-v2-2026-07-10t22-21-07z.8c528c38122cecc9","runId":"run.canada-ei-regular-beneficiaries-june-2026.2026-07-10T22-21-07Z.canada-ei-regular-beneficiaries-june-2026-thesis-analyst-ladder-v2-2026-07-10t22-21-07z.8c528c38122cecc9","predictionId":"canada-ei-regular-beneficiaries-june-2026","specId":"spec.canada-ei-regular-beneficiaries-june-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: Statistics Canada accessible historical chart for Table 14-10-0011-01","Tool result: Fetched official historical values: June 2024 was 479,800, June 2025 was 547,700, July 2025 was 555,090, August 2025 was 555,270, September 2025 was 554,270, and October 2025 was 561,480."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The target is the seasonally adjusted Canada total for regular benefits, both sexes, age 15 years and over, in Statistics Canada Table 14-10-0011-01. Resolution is tied to the first official June 2026 print on 2026-08-20. The source-binding metadata is corrected here from May 2026 to June 2026 while retaining the canonical June target and first-print rule.","Tool result: Fetched official values: Canada had 567,620 persons in December 2025, 550,840 in January 2026, 542,110 in February 2026, 548,000 in March 2026, and 544,440 in April 2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The target is the seasonally adjusted Canada total for regular benefits, both sexes, age 15 years and over, in Statistics Canada Table 14-10-0011-01. Resolution is tied to the first official June 2026 print on 2026-08-20. The source-binding metadata is corrected here from May 2026 to June 2026 while retaining the canonical June target and first-print rule.","Tool call: Statistics Canada The Daily April 2026 Employment Insurance release"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 23.5, distribution present, forecast step count 1.","evidence":["Prior/update/interval: use a persistence prior centered on the latest official April value of 544.44 thousand, update upward toward the fetched June 2025 value of 547.70 thousand and the 2025 summer values of 555.09, 555.27, and 554.27 thousand, and discount the improved May labour-market signal. The threshold-ladder interval method gives final implied bounds of 537.00 to 560.50 thousand and a median of 548.00 thousand.","Downside risk is faster normalization after improved employment, which would land below the interval near 535 thousand. Upside risk is a stronger seasonal increase or delayed benefit exits, which would land above the interval near 565 thousand. A large unanticipated policy or labour-market shock would be outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The persistence prior is the primary model prior. I considered a simple time-series trend prior, but rejected extrapolating the December-to-April decline because the sequence includes a February low followed by a March rebound and April's smaller easing; a trend-only model would overstate downside. Level is anchored on April's 544.44 thousand, momentum is mixed, the one-off component is summer churn and expiry/re-entry timing, and no fetched source indicates a policy shock."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The persistence prior is the primary model prior. I considered a simple time-series trend prior, but rejected extrapolating the December-to-April decline because the sequence includes a February low followed by a March rebound and April's smaller easing; a trend-only model would overstate downside. Level is anchored on April's 544.44 thousand, momentum is mixed, the one-off component is summer churn and expiry/re-entry timing, and no fetched source indicates a policy shock.","Downside risk is faster normalization after improved employment, which would land below the interval near 535 thousand. Upside risk is a stronger seasonal increase or delayed benefit exits, which would land above the interval near 565 thousand. A large unanticipated policy or labour-market shock would be outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The May labour-market context is consistent with restraint on the upside: Statistics Canada's May 2026 indicators show employment at 21,122,000, up 0.4% monthly, and unemployment at 6.6%, down 0.3 percentage points. This supports a modest June rise rather than a sharp acceleration.","Prior/update/interval: use a persistence prior centered on the latest official April value of 544.44 thousand, update upward toward the fetched June 2025 value of 547.70 thousand and the 2025 summer values of 555.09, 555.27, and 554.27 thousand, and discount the improved May labour-market signal. The threshold-ladder interval method gives final implied bounds of 537.00 to 560.50 thousand and a median of 548.00 thousand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-ei-regular-beneficiaries-june-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-08-20\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-core-pce-mom-july-2026.2026-07-10T05-25-58Z.bb5d5a0dbe46b658","runId":"run.us-core-pce-mom-july-2026.2026-07-10T05-25-58Z.bb5d5a0dbe46b658","predictionId":"us-core-pce-mom-july-2026","specId":"spec.us-core-pce-mom-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Reference class/base rate: because this is a change-rate target, I use recent same-variant seasonally adjusted core PCE monthly percent changes as the base rate rather than year-over-year values or headline PCE. The four observed monthly changes average about 0.315 percent, while the latest BEA page shows the year-over-year rate rising to 3.4 percent, so the outside view is elevated but not clearly accelerating month by month.","Prior/update/interval: persistence prior from recent same-variant BEA/FRED PCEPILFE monthly changes is 0.315 percent using Feb-May 2026. Adjustment components: -0.020 for mild mean reversion from the elevated Feb-May run toward a still-firm but less hot July print, +0.010 for sticky core services and 3.4 percent year-over-year core PCE, -0.005 because the target excludes direct food and energy pass-through, giving 0.300 before display rounding and a final point of 0.29 after allowing for BEA one-decimal style publication risk around the unrounded estimate. Interval method uses the values themselves for this change-rate series: sigma = 0.060 from the four computed monthly changes; 1.28*sigma = 0.077. Because the four-point sample is thin and July is two releases ahead of the latest fetched May value, I widen the half-width to about 0.12, so 0.29 +/- 0.12 gives [0.17, 0.41]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this targets the BEA seasonally adjusted PCE price index excluding food and energy, July 2026, monthly percent change from the preceding month, first print. The relevant BEA account code visible through the public FRED mirror is DPCCRG, and the BEA linked monthly table is Table 2.8.7, Percent Change From Preceding Period in Prices for Personal Consumption Expenditures by Major Type of Product. FRED is used only as a BEA history mirror, not as the resolver.","Counter-considerations: upside risk is a July rebound in core services, portfolio-management fees, medical services, or tariff-sensitive goods that would land above the interval near 0.42 percent or higher. Downside risk is a broad goods deflation month plus cooler rent and medical-service readings that would land below the interval near 0.16 percent or lower. A large one-month methodology or seasonal-factor surprise would be outside the interval, but I do not treat that as the central case."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["US core PCE month-over-month forecast for July 2026 first print","Framing and exact resolver: this targets the BEA seasonally adjusted PCE price index excluding food and energy, July 2026, monthly percent change from the preceding month, first print. The relevant BEA account code visible through the public FRED mirror is DPCCRG, and the BEA linked monthly table is Table 2.8.7, Percent Change From Preceding Period in Prices for Personal Consumption Expenditures by Major Type of Product. FRED is used only as a BEA history mirror, not as the resolver."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.24, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior from recent same-variant BEA/FRED PCEPILFE monthly changes is 0.315 percent using Feb-May 2026. Adjustment components: -0.020 for mild mean reversion from the elevated Feb-May run toward a still-firm but less hot July print, +0.010 for sticky core services and 3.4 percent year-over-year core PCE, -0.005 because the target excludes direct food and energy pass-through, giving 0.300 before display rounding and a final point of 0.29 after allowing for BEA one-decimal style publication risk around the unrounded estimate. Interval method uses the values themselves for this change-rate series: sigma = 0.060 from the four computed monthly changes; 1.28*sigma = 0.077. Because the four-point sample is thin and July is two releases ahead of the latest fetched May value, I widen the half-width to about 0.12, so 0.29 +/- 0.12 gives [0.17, 0.41].","Counter-considerations: upside risk is a July rebound in core services, portfolio-management fees, medical services, or tariff-sensitive goods that would land above the interval near 0.42 percent or higher. Downside risk is a broad goods deflation month plus cooler rent and medical-service readings that would land below the interval near 0.16 percent or lower. A large one-month methodology or seasonal-factor surprise would be outside the interval, but I do not treat that as the central case."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Reference class/base rate: because this is a change-rate target, I use recent same-variant seasonally adjusted core PCE monthly percent changes as the base rate rather than year-over-year values or headline PCE. The four observed monthly changes average about 0.315 percent, while the latest BEA page shows the year-over-year rate rising to 3.4 percent, so the outside view is elevated but not clearly accelerating month by month.","Prior/update/interval: persistence prior from recent same-variant BEA/FRED PCEPILFE monthly changes is 0.315 percent using Feb-May 2026. Adjustment components: -0.020 for mild mean reversion from the elevated Feb-May run toward a still-firm but less hot July print, +0.010 for sticky core services and 3.4 percent year-over-year core PCE, -0.005 because the target excludes direct food and energy pass-through, giving 0.300 before display rounding and a final point of 0.29 after allowing for BEA one-decimal style publication risk around the unrounded estimate. Interval method uses the values themselves for this change-rate series: sigma = 0.060 from the four computed monthly changes; 1.28*sigma = 0.077. Because the four-point sample is thin and July is two releases ahead of the latest fetched May value, I widen the half-width to about 0.12, so 0.29 +/- 0.12 gives [0.17, 0.41]."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Reference class/base rate: because this is a change-rate target, I use recent same-variant seasonally adjusted core PCE monthly percent changes as the base rate rather than year-over-year values or headline PCE. The four observed monthly changes average about 0.315 percent, while the latest BEA page shows the year-over-year rate rising to 3.4 percent, so the outside view is elevated but not clearly accelerating month by month.","Prior/update/interval: persistence prior from recent same-variant BEA/FRED PCEPILFE monthly changes is 0.315 percent using Feb-May 2026. Adjustment components: -0.020 for mild mean reversion from the elevated Feb-May run toward a still-firm but less hot July print, +0.010 for sticky core services and 3.4 percent year-over-year core PCE, -0.005 because the target excludes direct food and energy pass-through, giving 0.300 before display rounding and a final point of 0.29 after allowing for BEA one-decimal style publication risk around the unrounded estimate. Interval method uses the values themselves for this change-rate series: sigma = 0.060 from the four computed monthly changes; 1.28*sigma = 0.077. Because the four-point sample is thin and July is two releases ahead of the latest fetched May value, I widen the half-width to about 0.12, so 0.29 +/- 0.12 gives [0.17, 0.41]."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["US core PCE month-over-month forecast for July 2026 first print","Prior/update/interval: persistence prior from recent same-variant BEA/FRED PCEPILFE monthly changes is 0.315 percent using Feb-May 2026. Adjustment components: -0.020 for mild mean reversion from the elevated Feb-May run toward a still-firm but less hot July print, +0.010 for sticky core services and 3.4 percent year-over-year core PCE, -0.005 because the target excludes direct food and energy pass-through, giving 0.300 before display rounding and a final point of 0.29 after allowing for BEA one-decimal style publication risk around the unrounded estimate. Interval method uses the values themselves for this change-rate series: sigma = 0.060 from the four computed monthly changes; 1.28*sigma = 0.077. Because the four-point sample is thin and July is two releases ahead of the latest fetched May value, I widen the half-width to about 0.12, so 0.29 +/- 0.12 gives [0.17, 0.41]."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-core-pce-mom-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-26\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-annual-rate-july-2026.2026-07-10T05-33-58Z.75b2c78e34a541e0","runId":"run.australia-cpi-annual-rate-july-2026.2026-07-10T05-33-58Z.75b2c78e34a541e0","predictionId":"australia-cpi-annual-rate-july-2026","specId":"spec.australia-cpi-annual-rate-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: for a one-to-two-month-ahead forecast of a monthly year-over-year inflation rate, the outside-view base rate is recent persistence in the same ABS all-groups annual series. The prior is anchored on the latest May 2026 level of 4.0 percent, with the Feb-May mean of about 4.1 percent used as a cross-check rather than as the mechanical starting point.","Level, momentum, one-off, and policy mechanisms: level is still above target because housing and services remain firm; momentum from May is slightly down; temporary fuel and petrol declines depress headline inflation; a partial rebound or base-effect reversal by July argues against projecting May's 4.0 percent mechanically lower. A richer time-series model was not used because this is a short-horizon first-print forecast and the main uncertainty is ordinary monthly movement around recent persistence."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: the target is the ABS Monthly Consumer Price Index Indicator, All groups CPI annual movement for July 2026, original first print, percent, one-decimal published value. This is the monthly indicator variant, not quarterly CPI, not trimmed mean, and not a later revised vintage.","Resolver-source note: the intended resolver page is the future ABS July 2026 Monthly CPI Indicator release at https://www.abs.gov.au/statistics/economy/price-indexes-and-inflation/monthly-consumer-price-index-indicator/july-2026. That URL is used only as the stable first-print resolver location, not as evidence for the unreleased outcome."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: the target is the ABS Monthly Consumer Price Index Indicator, All groups CPI annual movement for July 2026, original first print, percent, one-decimal published value. This is the monthly indicator variant, not quarterly CPI, not trimmed mean, and not a later revised vintage.","Resolver-source note: the intended resolver page is the future ABS July 2026 Monthly CPI Indicator release at https://www.abs.gov.au/statistics/economy/price-indexes-and-inflation/monthly-consumer-price-index-indicator/july-2026. That URL is used only as the stable first-print resolver location, not as evidence for the unreleased outcome."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.8, distribution present, forecast step count 1.","evidence":["Level, momentum, one-off, and policy mechanisms: level is still above target because housing and services remain firm; momentum from May is slightly down; temporary fuel and petrol declines depress headline inflation; a partial rebound or base-effect reversal by July argues against projecting May's 4.0 percent mechanically lower. A richer time-series model was not used because this is a short-horizon first-print forecast and the main uncertainty is ordinary monthly movement around recent persistence.","Prior/update/interval: persistence prior uses the same-series recent historical sample available in the draft: February-May 2026 at 3.7, 4.6, 4.2, 4.0. Adjustment components are +0.1 pp for possible fuel/base-effect rebound by July and 0.0 pp for underlying inflation persistence because trimmed mean at 3.6 is already below headline but still elevated. Successive changes are +0.9, -0.4, -0.2, so sigma = 0.70 using sample standard deviation of those changes; the 80 percent half-width is roughly 1.28*sigma = 0.90. Because this is only a short volatility sample, the interval is judgmental but kept at the direct realized-change width rather than narrowed. Point = 4.0 + 0.1 = 4.1, interval = 4.1 +/- 0.9 = [3.2, 5.0]."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and policy mechanisms: level is still above target because housing and services remain firm; momentum from May is slightly down; temporary fuel and petrol declines depress headline inflation; a partial rebound or base-effect reversal by July argues against projecting May's 4.0 percent mechanically lower. A richer time-series model was not used because this is a short-horizon first-print forecast and the main uncertainty is ordinary monthly movement around recent persistence.","Prior/update/interval: persistence prior uses the same-series recent historical sample available in the draft: February-May 2026 at 3.7, 4.6, 4.2, 4.0. Adjustment components are +0.1 pp for possible fuel/base-effect rebound by July and 0.0 pp for underlying inflation persistence because trimmed mean at 3.6 is already below headline but still elevated. Successive changes are +0.9, -0.4, -0.2, so sigma = 0.70 using sample standard deviation of those changes; the 80 percent half-width is roughly 1.28*sigma = 0.90. Because this is only a short volatility sample, the interval is judgmental but kept at the direct realized-change width rather than narrowed. Point = 4.0 + 0.1 = 4.1, interval = 4.1 +/- 0.9 = [3.2, 5.0]."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, one-off, and policy mechanisms: level is still above target because housing and services remain firm; momentum from May is slightly down; temporary fuel and petrol declines depress headline inflation; a partial rebound or base-effect reversal by July argues against projecting May's 4.0 percent mechanically lower. A richer time-series model was not used because this is a short-horizon first-print forecast and the main uncertainty is ordinary monthly movement around recent persistence.","Prior/update/interval: persistence prior uses the same-series recent historical sample available in the draft: February-May 2026 at 3.7, 4.6, 4.2, 4.0. Adjustment components are +0.1 pp for possible fuel/base-effect rebound by July and 0.0 pp for underlying inflation persistence because trimmed mean at 3.6 is already below headline but still elevated. Successive changes are +0.9, -0.4, -0.2, so sigma = 0.70 using sample standard deviation of those changes; the 80 percent half-width is roughly 1.28*sigma = 0.90. Because this is only a short volatility sample, the interval is judgmental but kept at the direct realized-change width rather than narrowed. Point = 4.0 + 0.1 = 4.1, interval = 4.1 +/- 0.9 = [3.2, 5.0]."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Australia July 2026 monthly CPI indicator forecast","Tool call: ABS recent monthly CPI indicator reference points before April-May"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-annual-rate-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-26\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-annual-rate-july-2026.2026-07-10T13-50-17Z.australia-cpi-annual-rate-july-2026-thesis-analyst-ladder-2026-07-10t13-50-17z.f021fab90b1fb26b","runId":"run.australia-cpi-annual-rate-july-2026.2026-07-10T13-50-17Z.australia-cpi-annual-rate-july-2026-thesis-analyst-ladder-2026-07-10t13-50-17z.f021fab90b1fb26b","predictionId":"australia-cpi-annual-rate-july-2026","specId":"spec.australia-cpi-annual-rate-july-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Framing and exact resolver: forecast the ABS Monthly Consumer Price Index Indicator, Australia, July 2026, All groups CPI annual movement, first print, not seasonally adjusted headline indicator, in percent rounded to one decimal. This is the monthly CPI indicator variant; every anchor and historical value used here is the same All groups CPI annual movement variant, not quarterly CPI, trimmed mean, seasonally adjusted CPI, or a later revision.","Base rate/reference class: for monthly All groups CPI annual-rate targets two months ahead, a persistence prior using the latest official-source headline rate and recent successive changes is a strong base rate because the target is a year-over-year rate with overlapping 11 of 12 months already mostly determined by recent prices. The reference class here is the latest contiguous observed annual movements from February through May 2026: 3.7, 4.6, 4.2, 4.0. June 2026 was not used because it was not available at the run time."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["Framing and exact resolver: forecast the ABS Monthly Consumer Price Index Indicator, Australia, July 2026, All groups CPI annual movement, first print, not seasonally adjusted headline indicator, in percent rounded to one decimal. This is the monthly CPI indicator variant; every anchor and historical value used here is the same All groups CPI annual movement variant, not quarterly CPI, trimmed mean, seasonally adjusted CPI, or a later revision.","Tool call: Check ABS release calendar and ledger target fields for the July 2026 Monthly CPI Indicator release date and resolver identity."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: forecast the ABS Monthly Consumer Price Index Indicator, Australia, July 2026, All groups CPI annual movement, first print, not seasonally adjusted headline indicator, in percent rounded to one decimal. This is the monthly CPI indicator variant; every anchor and historical value used here is the same All groups CPI annual movement variant, not quarterly CPI, trimmed mean, seasonally adjusted CPI, or a later revision.","Tool call: Check ABS release calendar and ledger target fields for the July 2026 Monthly CPI Indicator release date and resolver identity."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.9, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = 4.0 from May 2026 All groups CPI annual movement; historical sample = February-May 2026 annual rates 3.7, 4.6, 4.2, 4.0; adjustment components are deliberately coarse rather than precise: +0.2 for sticky inflation pressure indicated by May trimmed mean at 3.6 percent and home building at 5.6 percent, +0.1 for possible fuel rebound after March automotive fuel was up 32.8 percent year over year and then partly reversed, and -0.1 for the observed May-April/March headline deceleration, giving a 4.2 center before ladder rounding. Successive changes are +0.9, -0.4, -0.2, so sample sigma = 0.70 percentage points and the normal 80 percent half-width is roughly 1.28*sigma = 0.90. This three-change shock-window sample is thin, but it is a conservative realized-volatility anchor for July because the current forecast is explicitly exposed to the same fuel, rebate, and monthly-indicator noise that produced those recent changes. The ladder-implied 80 percent interval is 3.2 to 5.1, half-width about 0.95 around the 4.2 median, very close to the 1.28*sigma width.","Counter-considerations: upside risk is a renewed fuel or import-cost spike, stronger rent and dwelling-price pass-through, or rebate expiry that would land above the interval at more than 5.1 percent. Downside risk is a sharper fuel reversal, broader household-demand weakening, or new price subsidies that would land below the interval at less than 3.2 percent. Outside the interval would require a materially larger one-month shock or policy-price adjustment than seen in the February-May reference window."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate/reference class: for monthly All groups CPI annual-rate targets two months ahead, a persistence prior using the latest official-source headline rate and recent successive changes is a strong base rate because the target is a year-over-year rate with overlapping 11 of 12 months already mostly determined by recent prices. The reference class here is the latest contiguous observed annual movements from February through May 2026: 3.7, 4.6, 4.2, 4.0. June 2026 was not used because it was not available at the run time.","Level, momentum, one-off, and policy mechanisms: level starts from May at 4.0 percent; momentum from March to May is downward after the fuel-shock peak, with changes of +0.9, -0.4, and -0.2 percentage points; one-off fuel volatility can pull July either way; policy-rebate and fuel-excise timing can distort monthly headline CPI; persistent rents, housing, food, and services keep the center above the RBA target band."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence prior = 4.0 from May 2026 All groups CPI annual movement; historical sample = February-May 2026 annual rates 3.7, 4.6, 4.2, 4.0; adjustment components are deliberately coarse rather than precise: +0.2 for sticky inflation pressure indicated by May trimmed mean at 3.6 percent and home building at 5.6 percent, +0.1 for possible fuel rebound after March automotive fuel was up 32.8 percent year over year and then partly reversed, and -0.1 for the observed May-April/March headline deceleration, giving a 4.2 center before ladder rounding. Successive changes are +0.9, -0.4, -0.2, so sample sigma = 0.70 percentage points and the normal 80 percent half-width is roughly 1.28*sigma = 0.90. This three-change shock-window sample is thin, but it is a conservative realized-volatility anchor for July because the current forecast is explicitly exposed to the same fuel, rebate, and monthly-indicator noise that produced those recent changes. The ladder-implied 80 percent interval is 3.2 to 5.1, half-width about 0.95 around the 4.2 median, very close to the 1.28*sigma width.","Counter-considerations: upside risk is a renewed fuel or import-cost spike, stronger rent and dwelling-price pass-through, or rebate expiry that would land above the interval at more than 5.1 percent. Downside risk is a sharper fuel reversal, broader household-demand weakening, or new price subsidies that would land below the interval at less than 3.2 percent. Outside the interval would require a materially larger one-month shock or policy-price adjustment than seen in the February-May reference window."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Australia July 2026 Monthly CPI Indicator Forecast","Framing and exact resolver: forecast the ABS Monthly Consumer Price Index Indicator, Australia, July 2026, All groups CPI annual movement, first print, not seasonally adjusted headline indicator, in percent rounded to one decimal. This is the monthly CPI indicator variant; every anchor and historical value used here is the same All groups CPI annual movement variant, not quarterly CPI, trimmed mean, seasonally adjusted CPI, or a later revision."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-annual-rate-july-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-08-26\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-annual-rate-july-2026.2026-07-10T13-52-30Z.australia-cpi-annual-rate-july-2026-thesis-analyst-fast-2026-07-10t13-52-30z.c8d7b8659608e6ed","runId":"run.australia-cpi-annual-rate-july-2026.2026-07-10T13-52-30Z.australia-cpi-annual-rate-july-2026-thesis-analyst-fast-2026-07-10t13-52-30z.c8d7b8659608e6ed","predictionId":"australia-cpi-annual-rate-july-2026","specId":"spec.australia-cpi-annual-rate-july-2026","runLabel":"Fast rollout 1 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: for the official ABS monthly headline inflation-rate series available on the page, Sep-2021 through Sep-2025 values ranged from 1.9 to 8.4, with the late-2025 run Jul 2.8, Aug 3.0, Sep 3.5 showing renewed upward momentum after the June 2025 trough of 1.9. The reference class therefore supports a persistent monthly annual-rate prior rather than a sharp one-month break.","Prior/update/interval: persistence prior starts from the latest accessible same-variant official headline rate of 3.5, with current-release adjustment +0.4 for the Sep-2025 uptrend and sticky housing/services components, +0.2 for possible ongoing energy/base-effect pressure, and 0.0 net policy/mechanism offset because electricity rebate timing can reverse but rents and services remain firm, giving point 4.1. Historical sample is ABS official monthly all-groups annual movements from Sep-2021 to Sep-2025; using successive monthly changes for this rate series gives sigma = 0.51 percentage points. The normal 80% half-width is roughly 1.28*sigma = 1.28*0.51 = 0.65, rounded and slightly widened to 0.7 because the ledger’s monthly-indicator-versus-complete-monthly-CPI transition raises mapping risk. Final 80% bounds are 4.1-0.7 = 3.4 and 4.1+0.7 = 4.8."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: forecast the first ABS print for the July 2026 All groups CPI annual movement, in percent and rounded to one decimal. I keep the catalog slug, dataPointId, resolutionDate, and first_print policy fixed. The ledger sourceBinding discrepancy is material: it points to the June 2026 quarterly Consumer Price Index page, while the resolver text points to the July 2026 monthly CPI indicator page. I do not change target identity.","Tool call: Opened ABS Monthly Consumer Price Index Indicator latest-release page and read the official headline history table."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: forecast the first ABS print for the July 2026 All groups CPI annual movement, in percent and rounded to one decimal. I keep the catalog slug, dataPointId, resolutionDate, and first_print policy fixed. The ledger sourceBinding discrepancy is material: it points to the June 2026 quarterly Consumer Price Index page, while the resolver text points to the July 2026 monthly CPI indicator page. I do not change target identity.","Tool call: Opened ABS Monthly Consumer Price Index Indicator latest-release page and read the official headline history table."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.4, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior starts from the latest accessible same-variant official headline rate of 3.5, with current-release adjustment +0.4 for the Sep-2025 uptrend and sticky housing/services components, +0.2 for possible ongoing energy/base-effect pressure, and 0.0 net policy/mechanism offset because electricity rebate timing can reverse but rents and services remain firm, giving point 4.1. Historical sample is ABS official monthly all-groups annual movements from Sep-2021 to Sep-2025; using successive monthly changes for this rate series gives sigma = 0.51 percentage points. The normal 80% half-width is roughly 1.28*sigma = 1.28*0.51 = 0.65, rounded and slightly widened to 0.7 because the ledger’s monthly-indicator-versus-complete-monthly-CPI transition raises mapping risk. Final 80% bounds are 4.1-0.7 = 3.4 and 4.1+0.7 = 4.8.","Counter-consideration: upside risk is a renewed electricity, fuel, rent, or insurance shock that keeps annual headline inflation near or above 4.8; downside risk is a reversal of energy-base effects plus weaker goods prices that pulls the first print below 3.4. A print outside the interval would most likely require one of those energy or policy-rebate mechanisms to dominate the broad CPI basket."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate/reference class: for the official ABS monthly headline inflation-rate series available on the page, Sep-2021 through Sep-2025 values ranged from 1.9 to 8.4, with the late-2025 run Jul 2.8, Aug 3.0, Sep 3.5 showing renewed upward momentum after the June 2025 trough of 1.9. The reference class therefore supports a persistent monthly annual-rate prior rather than a sharp one-month break.","Prior/update/interval: persistence prior starts from the latest accessible same-variant official headline rate of 3.5, with current-release adjustment +0.4 for the Sep-2025 uptrend and sticky housing/services components, +0.2 for possible ongoing energy/base-effect pressure, and 0.0 net policy/mechanism offset because electricity rebate timing can reverse but rents and services remain firm, giving point 4.1. Historical sample is ABS official monthly all-groups annual movements from Sep-2021 to Sep-2025; using successive monthly changes for this rate series gives sigma = 0.51 percentage points. The normal 80% half-width is roughly 1.28*sigma = 1.28*0.51 = 0.65, rounded and slightly widened to 0.7 because the ledger’s monthly-indicator-versus-complete-monthly-CPI transition raises mapping risk. Final 80% bounds are 4.1-0.7 = 3.4 and 4.1+0.7 = 4.8."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence prior starts from the latest accessible same-variant official headline rate of 3.5, with current-release adjustment +0.4 for the Sep-2025 uptrend and sticky housing/services components, +0.2 for possible ongoing energy/base-effect pressure, and 0.0 net policy/mechanism offset because electricity rebate timing can reverse but rents and services remain firm, giving point 4.1. Historical sample is ABS official monthly all-groups annual movements from Sep-2021 to Sep-2025; using successive monthly changes for this rate series gives sigma = 0.51 percentage points. The normal 80% half-width is roughly 1.28*sigma = 1.28*0.51 = 0.65, rounded and slightly widened to 0.7 because the ledger’s monthly-indicator-versus-complete-monthly-CPI transition raises mapping risk. Final 80% bounds are 4.1-0.7 = 3.4 and 4.1+0.7 = 4.8.","Counter-consideration: upside risk is a renewed electricity, fuel, rent, or insurance shock that keeps annual headline inflation near or above 4.8; downside risk is a reversal of energy-base effects plus weaker goods prices that pulls the first print below 3.4. A print outside the interval would most likely require one of those energy or policy-rebate mechanisms to dominate the broad CPI basket."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Australia July 2026 headline CPI annual movement forecast","Framing and exact resolver: forecast the first ABS print for the July 2026 All groups CPI annual movement, in percent and rounded to one decimal. I keep the catalog slug, dataPointId, resolutionDate, and first_print policy fixed. The ledger sourceBinding discrepancy is material: it points to the June 2026 quarterly Consumer Price Index page, while the resolver text points to the July 2026 monthly CPI indicator page. I do not change target identity."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-annual-rate-july-2026\nrunLabel: Fast rollout 1 of 3\nresolutionDate: 2026-08-26\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-annual-rate-july-2026.2026-07-10T13-54-35Z.australia-cpi-annual-rate-july-2026-thesis-analyst-fast-2026-07-10t13-54-35z.eba7e6a1b669675c","runId":"run.australia-cpi-annual-rate-july-2026.2026-07-10T13-54-35Z.australia-cpi-annual-rate-july-2026-thesis-analyst-fast-2026-07-10t13-54-35z.eba7e6a1b669675c","predictionId":"australia-cpi-annual-rate-july-2026","specId":"spec.australia-cpi-annual-rate-july-2026","runLabel":"Fast rollout 2 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: Search public reporting citing ABS July 2025 Monthly CPI Indicator base-period figures","Reference class and base rate: for this one-to-two-month-ahead headline annual-rate forecast, the outside view is a random-walk/persistence base rate anchored on the latest same ABS monthly headline series values. The recent path is 3.7% in February, 4.6% in March, 4.2% in April, and 4.0% in May, so the base rate is near 4.0% before July-specific adjustments."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing and exact resolver: forecast the ABS Monthly Consumer Price Index Indicator, Australia, All groups CPI annual movement for July 2026, first print only, rounded to one decimal in percent. This uses the monthly headline indicator variant throughout, not quarterly CPI, trimmed mean, seasonally adjusted components, or later revisions.","Tool call: ABS release-calendar and registered resolver check for the July 2026 Monthly Consumer Price Index Indicator target"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: forecast the ABS Monthly Consumer Price Index Indicator, Australia, All groups CPI annual movement for July 2026, first print only, rounded to one decimal in percent. This uses the monthly headline indicator variant throughout, not quarterly CPI, trimmed mean, seasonally adjusted components, or later revisions.","Tool call: ABS release-calendar and registered resolver check for the July 2026 Monthly Consumer Price Index Indicator target"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.2, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = May 2026 headline annual CPI 4.0% from the ABS monthly headline reference class; historical sample = Feb-May 2026 monthly headline annual rates 3.7, 4.6, 4.2, 4.0; adjustment components = +0.2 for sticky trimmed-mean/domestic services pressure, -0.1 for partial fuel-shock unwind and high July 2025 electricity base, final point = 4.0 + 0.2 - 0.1 = 4.1. Successive changes are +0.9, -0.4, -0.2 percentage points, so sigma = 0.7; one-month 80% half-width is roughly 1.28*sigma = 0.9. I widen to 1.1 for the two-step May-to-July horizon and energy-policy volatility, giving 4.1 +/- 1.1 = 3.0 to 5.2.","Counter-consideration: upside risk is a renewed fuel or electricity price jump plus continued housing and food pressure, which would land above the interval if the July annual print exceeded 5.2%. Downside risk is a sharper reversal of the March fuel shock or a larger temporary policy subsidy effect, which would land below the interval if the July annual print fell under 3.0%."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior = May 2026 headline annual CPI 4.0% from the ABS monthly headline reference class; historical sample = Feb-May 2026 monthly headline annual rates 3.7, 4.6, 4.2, 4.0; adjustment components = +0.2 for sticky trimmed-mean/domestic services pressure, -0.1 for partial fuel-shock unwind and high July 2025 electricity base, final point = 4.0 + 0.2 - 0.1 = 4.1. Successive changes are +0.9, -0.4, -0.2 percentage points, so sigma = 0.7; one-month 80% half-width is roughly 1.28*sigma = 0.9. I widen to 1.1 for the two-step May-to-July horizon and energy-policy volatility, giving 4.1 +/- 1.1 = 3.0 to 5.2.","Counter-consideration: upside risk is a renewed fuel or electricity price jump plus continued housing and food pressure, which would land above the interval if the July annual print exceeded 5.2%. Downside risk is a sharper reversal of the March fuel shock or a larger temporary policy subsidy effect, which would land below the interval if the July annual print fell under 3.0%."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Inside-view update: March's fuel shock has partly faded, pulling the headline rate down from 4.6% to 4.0% by May, but trimmed mean at 3.6% and continued RBA concern argue against a fast return toward the 2-3% band by July. The July 2025 comparison month was already lifted to 2.8% by electricity rebate effects, limiting upside from base effects, but current domestic inflation is still too sticky to forecast a clear drop below May.","Counter-consideration: upside risk is a renewed fuel or electricity price jump plus continued housing and food pressure, which would land above the interval if the July annual print exceeded 5.2%. Downside risk is a sharper reversal of the March fuel shock or a larger temporary policy subsidy effect, which would land below the interval if the July annual print fell under 3.0%."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Australia July 2026 Monthly CPI Indicator Forecast","Framing and exact resolver: forecast the ABS Monthly Consumer Price Index Indicator, Australia, All groups CPI annual movement for July 2026, first print only, rounded to one decimal in percent. This uses the monthly headline indicator variant throughout, not quarterly CPI, trimmed mean, seasonally adjusted components, or later revisions."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-annual-rate-july-2026\nrunLabel: Fast rollout 2 of 3\nresolutionDate: 2026-08-26\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-annual-rate-july-2026.2026-07-10T13-55-57Z.australia-cpi-annual-rate-july-2026-thesis-analyst-fast-2026-07-10t13-55-57z.984f18b4b5ab8e56","runId":"run.australia-cpi-annual-rate-july-2026.2026-07-10T13-55-57Z.australia-cpi-annual-rate-july-2026-thesis-analyst-fast-2026-07-10t13-55-57z.984f18b4b5ab8e56","predictionId":"australia-cpi-annual-rate-july-2026","specId":"spec.australia-cpi-annual-rate-july-2026","runLabel":"Fast rollout 3 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base rate / reference class: for a two-month-ahead forecast of the monthly headline annual rate, the strongest public reference class is the recent same-series path: 3.7, 4.6, 4.2, and 4.0 percent. That says the outside-view anchor should remain near 4 percent rather than reverting quickly to the RBA 2-3 percent target.","Prior/update/interval: persistence prior uses the same-series monthly annual-rate history 2026-02=3.7, 2026-03=4.6, 2026-04=4.2, 2026-05=4.0. Successive changes are +0.9, -0.4, -0.2 percentage points; sample sigma = 0.70. The one-month 80 percent half-width is about 1.28*sigma = 0.90. I widen to 1.10, within 1.75x, because the target is two monthly releases ahead and July has a fuel-policy/base-effect risk. Starting from 4.0, I add +0.2 for underlying inflation near 3.6 and possible fuel-excise reversal, giving point 4.2 and 80 percent bounds 4.2 +/- 1.1 = 3.1 to 5.3."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this is the ABS Monthly Consumer Price Index Indicator, Australia, July 2026, All groups CPI annual movement, not the quarterly CPI and not a seasonally adjusted or trimmed-mean variant. The ledger target resolves on the first ABS print, rounded to one decimal, and the ledger discrepancy is that sourceBinding names a June 2026 quarterly CPI page while the target identity and resolver clearly refer to the July 2026 Monthly CPI Indicator page.","Tool call: Checked the ABS release-calendar target for Monthly Consumer Price Index Indicator, Australia, July 2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this is the ABS Monthly Consumer Price Index Indicator, Australia, July 2026, All groups CPI annual movement, not the quarterly CPI and not a seasonally adjusted or trimmed-mean variant. The ledger target resolves on the first ABS print, rounded to one decimal, and the ledger discrepancy is that sourceBinding names a June 2026 quarterly CPI page while the target identity and resolver clearly refer to the July 2026 Monthly CPI Indicator page.","Tool call: Checked the ABS release-calendar target for Monthly Consumer Price Index Indicator, Australia, July 2026."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.2, distribution present, forecast step count 1.","evidence":["Tool call: Checked April 2026 monthly CPI indicator details for the same annual headline variant.","Tool call: Checked May 2026 monthly CPI indicator details and current underlying-inflation context."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and policy mechanisms: the level is still elevated at 4.0 percent in May; short-run momentum is down from the March fuel spike; the March one-off fuel shock has partly unwound; the July expiry or reversal of temporary fuel-excise relief is an upside mechanism, while tighter rates and weak demand are downside mechanisms.","Prior/update/interval: persistence prior uses the same-series monthly annual-rate history 2026-02=3.7, 2026-03=4.6, 2026-04=4.2, 2026-05=4.0. Successive changes are +0.9, -0.4, -0.2 percentage points; sample sigma = 0.70. The one-month 80 percent half-width is about 1.28*sigma = 0.90. I widen to 1.10, within 1.75x, because the target is two monthly releases ahead and July has a fuel-policy/base-effect risk. Starting from 4.0, I add +0.2 for underlying inflation near 3.6 and possible fuel-excise reversal, giving point 4.2 and 80 percent bounds 4.2 +/- 1.1 = 3.1 to 5.3."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool result: Fetched 2026-04 All groups CPI annual movement = 4.2 percent, down from 4.6 percent in March; automotive fuel fell 7.0 percent from March to April but remained 23.5 percent above February.","Prior/update/interval: persistence prior uses the same-series monthly annual-rate history 2026-02=3.7, 2026-03=4.6, 2026-04=4.2, 2026-05=4.0. Successive changes are +0.9, -0.4, -0.2 percentage points; sample sigma = 0.70. The one-month 80 percent half-width is about 1.28*sigma = 0.90. I widen to 1.10, within 1.75x, because the target is two monthly releases ahead and July has a fuel-policy/base-effect risk. Starting from 4.0, I add +0.2 for underlying inflation near 3.6 and possible fuel-excise reversal, giving point 4.2 and 80 percent bounds 4.2 +/- 1.1 = 3.1 to 5.3."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Australia Monthly CPI Indicator July 2026 Forecast","Base rate / reference class: for a two-month-ahead forecast of the monthly headline annual rate, the strongest public reference class is the recent same-series path: 3.7, 4.6, 4.2, and 4.0 percent. That says the outside-view anchor should remain near 4 percent rather than reverting quickly to the RBA 2-3 percent target."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-annual-rate-july-2026\nrunLabel: Fast rollout 3 of 3\nresolutionDate: 2026-08-26\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-annual-rate-july-2026.2026-07-10T13-55-57Z.australia-cpi-annual-rate-july-2026-thesis-analyst-median3-2026-07-10t13-55-57z.29545999bf7cb9df","runId":"run.australia-cpi-annual-rate-july-2026.2026-07-10T13-55-57Z.australia-cpi-annual-rate-july-2026-thesis-analyst-median3-2026-07-10t13-55-57z.29545999bf7cb9df","predictionId":"australia-cpi-annual-rate-july-2026","specId":"spec.australia-cpi-annual-rate-july-2026","runLabel":"Median of 3 rollouts","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and implicit outside-view language.","evidence":["Median-of-3 rollout ensemble","Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T13:52:30Z, 2026-07-10T13:54:35Z, 2026-07-10T13:55:57Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 8 source-context item(s), activity log present.","evidence":["Median CDF quantiles: q10 = 3.1, q50 = 4.1, q90 = 5.2. Constituent points [4.1, 4.1, 4.2] with 80% widths [1.4, 2.2, 2.2]; the median interval inherits the central rollout mass rather than averaging tails."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.1, distribution present, forecast step count 1.","evidence":["Median CDF quantiles: q10 = 3.1, q50 = 4.1, q90 = 5.2. Constituent points [4.1, 4.1, 4.2] with 80% widths [1.4, 2.2, 2.2]; the median interval inherits the central rollout mass rather than averaging tails.","Forecast: point 4.1, 80% interval [3.1, 5.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T13:52:30Z, 2026-07-10T13:54:35Z, 2026-07-10T13:55:57Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T13:52:30Z, 2026-07-10T13:54:35Z, 2026-07-10T13:55:57Z. Drivers and resolver fields mirror the rollout closest to the median.","Tool result: {rollout_points: [4.1, 4.1, 4.2], rollout_widths: [1.4, 2.2, 2.2], q10: 3.1, q50: 4.1, q90: 5.2}"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-annual-rate-july-2026\nrunLabel: Median of 3 rollouts\nresolutionDate: 2026-08-26\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-annual-rate-july-2026.2026-07-10T15-37-10Z.australia-cpi-annual-rate-july-2026-thesis-analyst-fast-2026-07-10t15-37-10z.157a47b9826ef6fe","runId":"run.australia-cpi-annual-rate-july-2026.2026-07-10T15-37-10Z.australia-cpi-annual-rate-july-2026-thesis-analyst-fast-2026-07-10t15-37-10z.157a47b9826ef6fe","predictionId":"australia-cpi-annual-rate-july-2026","specId":"spec.australia-cpi-annual-rate-july-2026","runLabel":"Fast rollout 1 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["The reference class/base rate is the recent complete-monthly All groups annual-CPI sequence, centred near 3.9% over December-May. July 2025's unusually large 1.3% monthly increase is the dominant mechanical comparison effect, so a lower July 2026 annual rate is more likely even if underlying housing pressure persists.","Prior/update/interval: Persistence prior is the December 2025-May 2026 All groups annual-rate mean of 4.02%; the historical sample is April 2025-May 2026 annual rates, whose successive changes have sample sigma = 0.46 percentage points. The base-effect adjustment for July 2025's +1.3% monthly print is -0.7pp after allowing a positive July 2026 monthly print, while persistent Housing (+6.5%) and trimmed mean (+3.6%) add +0.0pp net versus the recent level, implying 3.3%. The ordinary 80% half-width is 1.28*0.46 = 0.59pp; I use 0.8pp (1.36x) because a large July base month makes the annual-rate mapping unusually sensitive to the unobserved July monthly print, giving 2.5% to 4.1%."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The target is the ABS first-print All groups CPI annual movement for July 2026, rounded to one decimal. All anchors use the same national weighted-average-of-eight-capital-cities All groups annual CPI variant; the ledger sourceBinding points to the June 2026 Consumer Price Index page rather than the July monthly-indicator page, but the forecast remains tied to abs.cpi.all_groups.yoy.2026-07.first_print.","Tool result: The ABS calendar lists Consumer Price Index, Australia for reference period July 2026 at 11:30am AEST on Wednesday 26 August 2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The target is the ABS first-print All groups CPI annual movement for July 2026, rounded to one decimal. All anchors use the same national weighted-average-of-eight-capital-cities All groups annual CPI variant; the ledger sourceBinding points to the June 2026 Consumer Price Index page rather than the July monthly-indicator page, but the forecast remains tied to abs.cpi.all_groups.yoy.2026-07.first_print.","Tool call: ABS future-release calendar lookup for the target publication date and reference period."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.6, distribution present, forecast step count 1.","evidence":["Prior/update/interval: Persistence prior is the December 2025-May 2026 All groups annual-rate mean of 4.02%; the historical sample is April 2025-May 2026 annual rates, whose successive changes have sample sigma = 0.46 percentage points. The base-effect adjustment for July 2025's +1.3% monthly print is -0.7pp after allowing a positive July 2026 monthly print, while persistent Housing (+6.5%) and trimmed mean (+3.6%) add +0.0pp net versus the recent level, implying 3.3%. The ordinary 80% half-width is 1.28*0.46 = 0.59pp; I use 0.8pp (1.36x) because a large July base month makes the annual-rate mapping unusually sensitive to the unobserved July monthly print, giving 2.5% to 4.1%.","Upside risk is a renewed energy or housing-price jump that produces a July monthly increase well above the assumed positive print; downside risk is another transport-led fall combined with weak discretionary prices. Either would land outside the interval: a July monthly rise near or above the July 2025 1.3% would land above 4.1%, while a material monthly fall would land below 2.5%."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The reference class/base rate is the recent complete-monthly All groups annual-CPI sequence, centred near 3.9% over December-May. July 2025's unusually large 1.3% monthly increase is the dominant mechanical comparison effect, so a lower July 2026 annual rate is more likely even if underlying housing pressure persists.","Prior/update/interval: Persistence prior is the December 2025-May 2026 All groups annual-rate mean of 4.02%; the historical sample is April 2025-May 2026 annual rates, whose successive changes have sample sigma = 0.46 percentage points. The base-effect adjustment for July 2025's +1.3% monthly print is -0.7pp after allowing a positive July 2026 monthly print, while persistent Housing (+6.5%) and trimmed mean (+3.6%) add +0.0pp net versus the recent level, implying 3.3%. The ordinary 80% half-width is 1.28*0.46 = 0.59pp; I use 0.8pp (1.36x) because a large July base month makes the annual-rate mapping unusually sensitive to the unobserved July monthly print, giving 2.5% to 4.1%."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The target is the ABS first-print All groups CPI annual movement for July 2026, rounded to one decimal. All anchors use the same national weighted-average-of-eight-capital-cities All groups annual CPI variant; the ledger sourceBinding points to the June 2026 Consumer Price Index page rather than the July monthly-indicator page, but the forecast remains tied to abs.cpi.all_groups.yoy.2026-07.first_print.","Upside risk is a renewed energy or housing-price jump that produces a July monthly increase well above the assumed positive print; downside risk is another transport-led fall combined with weak discretionary prices. Either would land outside the interval: a July monthly rise near or above the July 2025 1.3% would land above 4.1%, while a material monthly fall would land below 2.5%."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The target is the ABS first-print All groups CPI annual movement for July 2026, rounded to one decimal. All anchors use the same national weighted-average-of-eight-capital-cities All groups annual CPI variant; the ledger sourceBinding points to the June 2026 Consumer Price Index page rather than the July monthly-indicator page, but the forecast remains tied to abs.cpi.all_groups.yoy.2026-07.first_print.","Prior/update/interval: Persistence prior is the December 2025-May 2026 All groups annual-rate mean of 4.02%; the historical sample is April 2025-May 2026 annual rates, whose successive changes have sample sigma = 0.46 percentage points. The base-effect adjustment for July 2025's +1.3% monthly print is -0.7pp after allowing a positive July 2026 monthly print, while persistent Housing (+6.5%) and trimmed mean (+3.6%) add +0.0pp net versus the recent level, implying 3.3%. The ordinary 80% half-width is 1.28*0.46 = 0.59pp; I use 0.8pp (1.36x) because a large July base month makes the annual-rate mapping unusually sensitive to the unobserved July monthly print, giving 2.5% to 4.1%."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-annual-rate-july-2026\nrunLabel: Fast rollout 1 of 3\nresolutionDate: 2026-08-26\ntraceLineCount: 12\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-annual-rate-july-2026.2026-07-10T15-40-54Z.australia-cpi-annual-rate-july-2026-thesis-analyst-fast-2026-07-10t15-40-54z.c8d7b8659608e6ed","runId":"run.australia-cpi-annual-rate-july-2026.2026-07-10T15-40-54Z.australia-cpi-annual-rate-july-2026-thesis-analyst-fast-2026-07-10t15-40-54z.c8d7b8659608e6ed","predictionId":"australia-cpi-annual-rate-july-2026","specId":"spec.australia-cpi-annual-rate-july-2026","runLabel":"Fast rollout 2 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the recent complete-monthly-CPI annual-rate sample from Apr-25 through May-26 rose from 2.4% to 4.0%, with the latest three prints 4.6%, 4.2%, and 4.0%. I use persistence around the current 4% regime rather than the earlier low-inflation 2025 level.","Prior/update/interval: Persistence prior is May's 4.0% annual rate; the 14-print Apr-25–May-26 historical sample is 2.4, 2.1, 1.9, 3.0, 3.2, 3.6, 3.8, 3.4, 3.8, 3.8, 3.7, 4.6, 4.2, 4.0. Its 13 successive changes have sample standard deviation sigma = 0.46 percentage points, so 1.28*sigma = 0.59 points. I add a 0.1-point persistence/energy-and-housing update to 4.1%, then widen the half-width to 0.7 points (1.19x) because the July 2025 monthly comparison was +1.3% and July seasonal price movements make the annual base effect unusually consequential; implied 80% bounds are 3.4% to 4.8%."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["This is the original, not-seasonally-adjusted All groups CPI annual movement for the weighted average of eight capital cities. The matching ABS release table is TABLE 1, CPI: All Groups, Index numbers and Percentage change. The ledger remains tied to abs.cpi.all_groups.yoy.2026-07.first_print: its sourceBinding points to a June 2026 CPI page, while the resolver specifies the July 2026 Monthly CPI Indicator release.","Tool call: Fetched the ABS May 2026 Consumer Price Index release table for the original All groups CPI monthly and annual movements."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Australia All groups CPI annual movement — July 2026 first print","This is the original, not-seasonally-adjusted All groups CPI annual movement for the weighted average of eight capital cities. The matching ABS release table is TABLE 1, CPI: All Groups, Index numbers and Percentage change. The ledger remains tied to abs.cpi.all_groups.yoy.2026-07.first_print: its sourceBinding points to a June 2026 CPI page, while the resolver specifies the July 2026 Monthly CPI Indicator release."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.4, distribution present, forecast step count 1.","evidence":["Prior/update/interval: Persistence prior is May's 4.0% annual rate; the 14-print Apr-25–May-26 historical sample is 2.4, 2.1, 1.9, 3.0, 3.2, 3.6, 3.8, 3.4, 3.8, 3.8, 3.7, 4.6, 4.2, 4.0. Its 13 successive changes have sample standard deviation sigma = 0.46 percentage points, so 1.28*sigma = 0.59 points. I add a 0.1-point persistence/energy-and-housing update to 4.1%, then widen the half-width to 0.7 points (1.19x) because the July 2025 monthly comparison was +1.3% and July seasonal price movements make the annual base effect unusually consequential; implied 80% bounds are 3.4% to 4.8%.","Counter-consideration: upside risk is a renewed electricity or fuel increase combined with a stronger-than-July-2025 monthly rise, which could land above the interval. Downside risk is a larger fall in fuel prices or a weak seasonal clothing/travel outcome; a monthly rise far below July 2025's 1.3% would land below the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: Persistence prior is May's 4.0% annual rate; the 14-print Apr-25–May-26 historical sample is 2.4, 2.1, 1.9, 3.0, 3.2, 3.6, 3.8, 3.4, 3.8, 3.8, 3.7, 4.6, 4.2, 4.0. Its 13 successive changes have sample standard deviation sigma = 0.46 percentage points, so 1.28*sigma = 0.59 points. I add a 0.1-point persistence/energy-and-housing update to 4.1%, then widen the half-width to 0.7 points (1.19x) because the July 2025 monthly comparison was +1.3% and July seasonal price movements make the annual base effect unusually consequential; implied 80% bounds are 3.4% to 4.8%."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-consideration: upside risk is a renewed electricity or fuel increase combined with a stronger-than-July-2025 monthly rise, which could land above the interval. Downside risk is a larger fall in fuel prices or a weak seasonal clothing/travel outcome; a monthly rise far below July 2025's 1.3% would land below the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["This is the original, not-seasonally-adjusted All groups CPI annual movement for the weighted average of eight capital cities. The matching ABS release table is TABLE 1, CPI: All Groups, Index numbers and Percentage change. The ledger remains tied to abs.cpi.all_groups.yoy.2026-07.first_print: its sourceBinding points to a June 2026 CPI page, while the resolver specifies the July 2026 Monthly CPI Indicator release.","Prior/update/interval: Persistence prior is May's 4.0% annual rate; the 14-print Apr-25–May-26 historical sample is 2.4, 2.1, 1.9, 3.0, 3.2, 3.6, 3.8, 3.4, 3.8, 3.8, 3.7, 4.6, 4.2, 4.0. Its 13 successive changes have sample standard deviation sigma = 0.46 percentage points, so 1.28*sigma = 0.59 points. I add a 0.1-point persistence/energy-and-housing update to 4.1%, then widen the half-width to 0.7 points (1.19x) because the July 2025 monthly comparison was +1.3% and July seasonal price movements make the annual base effect unusually consequential; implied 80% bounds are 3.4% to 4.8%."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-annual-rate-july-2026\nrunLabel: Fast rollout 2 of 3\nresolutionDate: 2026-08-26\ntraceLineCount: 12\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-annual-rate-july-2026.2026-07-10T15-45-17Z.australia-cpi-annual-rate-july-2026-thesis-analyst-fast-2026-07-10t15-45-17z.4b5f00c5ac0e5a6f","runId":"run.australia-cpi-annual-rate-july-2026.2026-07-10T15-45-17Z.australia-cpi-annual-rate-july-2026-thesis-analyst-fast-2026-07-10t15-45-17z.4b5f00c5ac0e5a6f","predictionId":"australia-cpi-annual-rate-july-2026","specId":"spec.australia-cpi-annual-rate-july-2026","runLabel":"Fast rollout 3 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base rate: the matching ABS All groups annual-movement reference class ran 2.4%, 2.1%, 1.9%, 3.0%, 3.2%, 3.6%, 3.8%, 3.4%, 3.8%, 3.8%, 3.7%, 4.6%, 4.2%, and 4.0% from April 2025 through May 2026. July 2025's 1.3% monthly rise creates a substantial favorable year-ago comparison for July 2026.","Prior/update/interval: persistence prior is May's 4.0% matching headline rate; historical sample is the 14 ABS annual rates from April 2025-May 2026; successive annual-rate changes give sigma = 0.476 percentage points, so 1.28*sigma = 0.609. I apply a -0.4pp July base-effect adjustment, partly offset by persistent housing and underlying inflation, for 3.6%; rounding the 0.609pp half-width to the published 0.1-point precision gives 3.0% to 4.2%."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The target is the ABS All groups CPI, Australia, annual movement headline series, not trimmed mean or a seasonally adjusted analytical series. The resolver is strict original first print; the ledger's June-page sourceBinding discrepancy is documented but does not alter the target identity or first-print policy.","Tool result: ABS lists Consumer Price Index, Australia for reference period July 2026 at 11:30am AEST on Wednesday 26 August 2026; the calendar also lists the adjacent June 2026 construction release at 11:30am on the same date."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the ABS All groups CPI, Australia, annual movement headline series, not trimmed mean or a seasonally adjusted analytical series. The resolver is strict original first print; the ledger's June-page sourceBinding discrepancy is documented but does not alter the target identity or first-print policy.","Tool call: ABS future-release calendar lookup for the July 2026 CPI release date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.2, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is May's 4.0% matching headline rate; historical sample is the 14 ABS annual rates from April 2025-May 2026; successive annual-rate changes give sigma = 0.476 percentage points, so 1.28*sigma = 0.609. I apply a -0.4pp July base-effect adjustment, partly offset by persistent housing and underlying inflation, for 3.6%; rounding the 0.609pp half-width to the published 0.1-point precision gives 3.0% to 4.2%.","Counter-consideration: upside risk is a renewed energy or administered-price jump combined with sticky housing, which could land above the interval. Downside risk is a stronger-than-expected July reversal after the 1.3% July 2025 base; a broad goods-price decline would land below the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The target is the ABS All groups CPI, Australia, annual movement headline series, not trimmed mean or a seasonally adjusted analytical series. The resolver is strict original first print; the ledger's June-page sourceBinding discrepancy is documented but does not alter the target identity or first-print policy.","Prior/update/interval: persistence prior is May's 4.0% matching headline rate; historical sample is the 14 ABS annual rates from April 2025-May 2026; successive annual-rate changes give sigma = 0.476 percentage points, so 1.28*sigma = 0.609. I apply a -0.4pp July base-effect adjustment, partly offset by persistent housing and underlying inflation, for 3.6%; rounding the 0.609pp half-width to the published 0.1-point precision gives 3.0% to 4.2%."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: persistence prior is May's 4.0% matching headline rate; historical sample is the 14 ABS annual rates from April 2025-May 2026; successive annual-rate changes give sigma = 0.476 percentage points, so 1.28*sigma = 0.609. I apply a -0.4pp July base-effect adjustment, partly offset by persistent housing and underlying inflation, for 3.6%; rounding the 0.609pp half-width to the published 0.1-point precision gives 3.0% to 4.2%.","Counter-consideration: upside risk is a renewed energy or administered-price jump combined with sticky housing, which could land above the interval. Downside risk is a stronger-than-expected July reversal after the 1.3% July 2025 base; a broad goods-price decline would land below the interval."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-annual-rate-july-2026\nrunLabel: Fast rollout 3 of 3\nresolutionDate: 2026-08-26\ntraceLineCount: 12\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-annual-rate-july-2026.2026-07-10T15-48-42Z.australia-cpi-annual-rate-july-2026-thesis-analyst-median3-2026-07-10t15-48-42z.1fb041aadde1e41b","runId":"run.australia-cpi-annual-rate-july-2026.2026-07-10T15-48-42Z.australia-cpi-annual-rate-july-2026-thesis-analyst-median3-2026-07-10t15-48-42z.1fb041aadde1e41b","predictionId":"australia-cpi-annual-rate-july-2026","specId":"spec.australia-cpi-annual-rate-july-2026","runLabel":"Median of 3 rollouts","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and implicit outside-view language.","evidence":["Median-of-3 rollout ensemble","Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T15:37:10Z, 2026-07-10T15:40:54Z, 2026-07-10T15:45:17Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 7 source-context item(s), activity log present.","evidence":["Median CDF quantiles: q10 = 3.0, q50 = 3.6, q90 = 4.2. Constituent points [3.3, 4.1, 3.6] with 80% widths [1.6, 1.4, 1.2]; the median interval inherits the central rollout mass rather than averaging tails."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.2, distribution present, forecast step count 1.","evidence":["Median CDF quantiles: q10 = 3.0, q50 = 3.6, q90 = 4.2. Constituent points [3.3, 4.1, 3.6] with 80% widths [1.6, 1.4, 1.2]; the median interval inherits the central rollout mass rather than averaging tails.","Forecast: point 3.6, 80% interval [3, 4.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T15:37:10Z, 2026-07-10T15:40:54Z, 2026-07-10T15:45:17Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T15:37:10Z, 2026-07-10T15:40:54Z, 2026-07-10T15:45:17Z. Drivers and resolver fields mirror the rollout closest to the median.","Tool result: {rollout_points: [3.3, 4.1, 3.6], rollout_widths: [1.6, 1.4, 1.2], q10: 3.0, q50: 3.6, q90: 4.2}"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-annual-rate-july-2026\nrunLabel: Median of 3 rollouts\nresolutionDate: 2026-08-26\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-annual-rate-july-2026.2026-07-10T16-02-52Z.australia-cpi-annual-rate-july-2026-thesis-analyst-ladder-2026-07-10t16-02-52z.18ab130abc022b51","runId":"run.australia-cpi-annual-rate-july-2026.2026-07-10T16-02-52Z.australia-cpi-annual-rate-july-2026-thesis-analyst-ladder-2026-07-10t16-02-52z.18ab130abc022b51","predictionId":"australia-cpi-annual-rate-july-2026","specId":"spec.australia-cpi-annual-rate-july-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Prior/update/interval: base rate/reference class prior is persistence in the complete Monthly CPI annual rate from Apr-25 to May-26. The latest annual rate is 4.0%; the high Jul-25 base month (+1.3% m/m after Jun-25 +0.1%) mechanically pulls July 2026 annual inflation down unless Jun-Jul 2026 monthly gains repeat the rebate/fuel spike, while sticky trimmed mean at 3.6%, housing at 6.5%, and broad services pressure offset some downside. Successive annual-rate changes from Apr-25..May-26 were -0.3, -0.2, +1.1, +0.2, +0.4, +0.2, -0.4, +0.4, 0.0, -0.1, +0.9, -0.4, -0.2 percentage points; sample sigma = 0.48, so 1.28*sigma = 0.62 percentage points. I widen to a ladder-implied 80% half-width of 0.8 points, about 1.29x the sigma half-width, because June and July are both still unknown and July base/rebate effects are unusually lumpy; final implied bounds are 3.0% to 4.6% around a 3.8% median.","Review disposition: accepted the blocking resolver critique by restoring the canonical ledger resolutionSource, resolutionSourceUrl, and resolutionRule exactly, while keeping the ABS naming transition and sourceBinding discrepancy as reasoning context. Kept the ladder, base-rate arithmetic, and 80% interval because the critique did not identify an evidence or calibration error."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["Framing and exact resolver: the target is the ABS first print for the July 2026 Monthly Consumer Price Index Indicator All groups CPI annual movement, rounded to one decimal, tied to dataPointId abs.cpi.all_groups.yoy.2026-07.first_print. The ledger also documents that the registered sourceBinding URL appears to point to a June 2026 CPI page; I keep the canonical ledger resolver fields unchanged.","Tool call: ABS Consumer Price Index, Australia latest release page and future-release schedule lookup"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: the target is the ABS first print for the July 2026 Monthly Consumer Price Index Indicator All groups CPI annual movement, rounded to one decimal, tied to dataPointId abs.cpi.all_groups.yoy.2026-07.first_print. The ledger also documents that the registered sourceBinding URL appears to point to a June 2026 CPI page; I keep the canonical ledger resolver fields unchanged.","Tool call: ABS Consumer Price Index, Australia latest release page and future-release schedule lookup"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.6, distribution present, forecast step count 1.","evidence":["Prior/update/interval: base rate/reference class prior is persistence in the complete Monthly CPI annual rate from Apr-25 to May-26. The latest annual rate is 4.0%; the high Jul-25 base month (+1.3% m/m after Jun-25 +0.1%) mechanically pulls July 2026 annual inflation down unless Jun-Jul 2026 monthly gains repeat the rebate/fuel spike, while sticky trimmed mean at 3.6%, housing at 6.5%, and broad services pressure offset some downside. Successive annual-rate changes from Apr-25..May-26 were -0.3, -0.2, +1.1, +0.2, +0.4, +0.2, -0.4, +0.4, 0.0, -0.1, +0.9, -0.4, -0.2 percentage points; sample sigma = 0.48, so 1.28*sigma = 0.62 percentage points. I widen to a ladder-implied 80% half-width of 0.8 points, about 1.29x the sigma half-width, because June and July are both still unknown and July base/rebate effects are unusually lumpy; final implied bounds are 3.0% to 4.6% around a 3.8% median.","Counter-considerations: upside risk is a renewed fuel or electricity/rebate shock plus sticky housing that would land above the interval. Downside risk is further fuel reversal and weak discretionary prices pushing the July print toward the low 3s. Outside the interval below 3.0 would likely require very soft June-July monthly CPI despite the known sticky components; outside the interval above 4.6 would likely require another March-like energy or administered-price jump."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: ABS CPI groups and contributions tables for current-release drivers","Prior/update/interval: base rate/reference class prior is persistence in the complete Monthly CPI annual rate from Apr-25 to May-26. The latest annual rate is 4.0%; the high Jul-25 base month (+1.3% m/m after Jun-25 +0.1%) mechanically pulls July 2026 annual inflation down unless Jun-Jul 2026 monthly gains repeat the rebate/fuel spike, while sticky trimmed mean at 3.6%, housing at 6.5%, and broad services pressure offset some downside. Successive annual-rate changes from Apr-25..May-26 were -0.3, -0.2, +1.1, +0.2, +0.4, +0.2, -0.4, +0.4, 0.0, -0.1, +0.9, -0.4, -0.2 percentage points; sample sigma = 0.48, so 1.28*sigma = 0.62 percentage points. I widen to a ladder-implied 80% half-width of 0.8 points, about 1.29x the sigma half-width, because June and July are both still unknown and July base/rebate effects are unusually lumpy; final implied bounds are 3.0% to 4.6% around a 3.8% median."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool call: ABS CPI groups and contributions tables for current-release drivers","Tool result: Fetched May 2026 group annual rates: Housing 6.5%, Food and non-alcoholic beverages 3.3%, Transport 3.3%, Clothing and footwear 5.0%, Education 4.8%; contribution table showed May 2026 Housing contribution 1.4071 percentage points and Transport contribution 0.3722 percentage points."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Framing and exact resolver: the target is the ABS first print for the July 2026 Monthly Consumer Price Index Indicator All groups CPI annual movement, rounded to one decimal, tied to dataPointId abs.cpi.all_groups.yoy.2026-07.first_print. The ledger also documents that the registered sourceBinding URL appears to point to a June 2026 CPI page; I keep the canonical ledger resolver fields unchanged.","Tool result: Fetched May 2026 group annual rates: Housing 6.5%, Food and non-alcoholic beverages 3.3%, Transport 3.3%, Clothing and footwear 5.0%, Education 4.8%; contribution table showed May 2026 Housing contribution 1.4071 percentage points and Transport contribution 0.3722 percentage points."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-annual-rate-july-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-08-26\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-annual-rate-july-2026.2026-07-10T16-19-40Z.australia-cpi-annual-rate-july-2026-thesis-analyst-fast-2026-07-10t16-19-40z.4397d25c9eb74486","runId":"run.australia-cpi-annual-rate-july-2026.2026-07-10T16-19-40Z.australia-cpi-annual-rate-july-2026-thesis-analyst-fast-2026-07-10t16-19-40z.4397d25c9eb74486","predictionId":"australia-cpi-annual-rate-july-2026","specId":"spec.australia-cpi-annual-rate-july-2026","runLabel":"Fast rollout 1 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: the relevant reference class is month-to-month changes in the annual All groups CPI rate from the ABS monthly CPI publication since the complete monthly history begins printing annual rates. The base rate is persistence from the latest 4.0% annual print, adjusted by expected June-July 2026 monthly price growth relative to the 1.4% combined monthly rise in June-July 2025.","Prior/update/interval: persistence prior is May 2026 annual CPI = 4.0 using the ABS Apr-25 through May-26 annual-rate sample. Adjustment components: expected Jun-26 plus Jul-26 headline monthly CPI about 1.2% versus Jun-25 plus Jul-25 base of 1.4%, subtracting about 0.2 percentage points from the annual rate; housing and trimmed-mean persistence add back about 0.0 to 0.1, leaving point 3.8 after one-decimal rounding. Interval method uses realized dispersion of successive annual-rate changes: differences are -0.3, -0.2, 1.1, 0.2, 0.4, 0.2, -0.4, 0.4, 0.0, -0.1, 0.9, -0.4, -0.2; monthly-difference sample sd is about 0.48, two-step sigma = sqrt(2)*0.48 = 0.68, so sigma = 0.68 and 1.28*sigma = 0.87. Rounded 80% interval is 3.8 +/- 0.9, or 2.9 to 4.7."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: I forecast the first ABS print for July 2026 All groups CPI annual movement, rounded to one decimal percent. The target ledger names the old Monthly Consumer Price Index Indicator URL, but the ABS current public release and future calendar now label the relevant product Consumer Price Index, Australia; I keep the forecast tied to the provided slug, dataPointId, resolutionDate, and first-print rule rather than changing target identity.","Tool result: Fetched ABS calendar entry: Wednesday 26 August 2026 11:30am AEST, Consumer Price Index, Australia, reference period July 2026; this verifies resolutionDate 2026-08-26."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: I forecast the first ABS print for July 2026 All groups CPI annual movement, rounded to one decimal percent. The target ledger names the old Monthly Consumer Price Index Indicator URL, but the ABS current public release and future calendar now label the relevant product Consumer Price Index, Australia; I keep the forecast tied to the provided slug, dataPointId, resolutionDate, and first-print rule rather than changing target identity.","Tool call: ABS future release calendar for August 2026"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.8, distribution present, forecast step count 1.","evidence":["Tool call: ABS May 2026 group detail and analytical series","Tool result: Fetched group detail for May 2026: Housing annual inflation 6.5%, Food and non-alcoholic beverages 3.3%, Transport 3.3%, Education 4.8%, Insurance and financial services 3.2%, and All groups seasonally adjusted annual inflation 4.0%."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Momentum assessment: May headline fell on the month but that was after a large March rise; trimmed mean rose to 3.6% and housing inflation remained 6.5%, so a forecast materially below 3.5 would require softer June and July prints than the underlying measures currently imply."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Framing and exact resolver: I forecast the first ABS print for July 2026 All groups CPI annual movement, rounded to one decimal percent. The target ledger names the old Monthly Consumer Price Index Indicator URL, but the ABS current public release and future calendar now label the relevant product Consumer Price Index, Australia; I keep the forecast tied to the provided slug, dataPointId, resolutionDate, and first-print rule rather than changing target identity.","Momentum assessment: May headline fell on the month but that was after a large March rise; trimmed mean rose to 3.6% and housing inflation remained 6.5%, so a forecast materially below 3.5 would require softer June and July prints than the underlying measures currently imply."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Australia July 2026 All Groups CPI Annual Inflation Forecast","Framing and exact resolver: I forecast the first ABS print for July 2026 All groups CPI annual movement, rounded to one decimal percent. The target ledger names the old Monthly Consumer Price Index Indicator URL, but the ABS current public release and future calendar now label the relevant product Consumer Price Index, Australia; I keep the forecast tied to the provided slug, dataPointId, resolutionDate, and first-print rule rather than changing target identity."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-annual-rate-july-2026\nrunLabel: Fast rollout 1 of 3\nresolutionDate: 2026-08-26\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-annual-rate-july-2026.2026-07-10T16-30-43Z.australia-cpi-annual-rate-july-2026-thesis-analyst-fast-2026-07-10t16-30-43z.c7aa8d4b3ade58d0","runId":"run.australia-cpi-annual-rate-july-2026.2026-07-10T16-30-43Z.australia-cpi-annual-rate-july-2026-thesis-analyst-fast-2026-07-10t16-30-43z.c7aa8d4b3ade58d0","predictionId":"australia-cpi-annual-rate-july-2026","specId":"spec.australia-cpi-annual-rate-july-2026","runLabel":"Fast rollout 2 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base rate / reference class: for this same ABS monthly All groups annual-rate series, the short-run reference class is the recent monthly annual-rate sequence itself. A persistence prior from the latest official 4.0 percent is preferred over a long-run 2-3 percent target because the July print is only two monthly observations ahead and the annual rate still reflects earlier fuel, housing, and services shocks.","Prior/update/interval: persistence prior = May 2026 All groups annual CPI at 4.0. Historical sample for realized dispersion = successive changes in Feb-May annual rates: 4.6-3.7 = 0.9, 4.2-4.6 = -0.4, 4.0-4.2 = -0.2. Sample sigma = 0.70 percentage points; 80 percent normal half-width is about 1.28*sigma = 0.90. Adjustment components: +0.25 for possible July fuel-excise and energy rebound, +0.15 for sticky housing/services and trimmed mean at 3.6, net roughly +0.40 from the 4.0 prior. Final point = 4.4; 80 percent interval = 4.4 +/- 0.9 = 3.5 to 5.3."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this is the ABS Monthly Consumer Price Index Indicator, All groups CPI annual movement for July 2026, first print only, percent rounded to one decimal. The ledger sourceBinding discrepancy is noted: the target resolves from the July 2026 Monthly CPI Indicator page, not the June 2026 quarterly CPI page.","Tool call: Checked ABS release-calendar target for Monthly Consumer Price Index Indicator, Australia, July 2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this is the ABS Monthly Consumer Price Index Indicator, All groups CPI annual movement for July 2026, first print only, percent rounded to one decimal. The ledger sourceBinding discrepancy is noted: the target resolves from the July 2026 Monthly CPI Indicator page, not the June 2026 quarterly CPI page.","Tool call: Checked ABS release-calendar target for Monthly Consumer Price Index Indicator, Australia, July 2026."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.8, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = May 2026 All groups annual CPI at 4.0. Historical sample for realized dispersion = successive changes in Feb-May annual rates: 4.6-3.7 = 0.9, 4.2-4.6 = -0.4, 4.0-4.2 = -0.2. Sample sigma = 0.70 percentage points; 80 percent normal half-width is about 1.28*sigma = 0.90. Adjustment components: +0.25 for possible July fuel-excise and energy rebound, +0.15 for sticky housing/services and trimmed mean at 3.6, net roughly +0.40 from the 4.0 prior. Final point = 4.4; 80 percent interval = 4.4 +/- 0.9 = 3.5 to 5.3.","Counter-consideration: upside risk is a renewed fuel or electricity jump after temporary relief fades, which would land above the interval if July All groups annual inflation prints above 5.3. Downside risk is a faster petrol reversal plus weak discretionary demand and housing-cost cooling, which would land below the interval if the first print is under 3.5."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate / reference class: for this same ABS monthly All groups annual-rate series, the short-run reference class is the recent monthly annual-rate sequence itself. A persistence prior from the latest official 4.0 percent is preferred over a long-run 2-3 percent target because the July print is only two monthly observations ahead and the annual rate still reflects earlier fuel, housing, and services shocks.","Variant control: anchors and dispersion use the monthly CPI indicator All groups annual movement, not quarterly CPI, not seasonally adjusted monthly change, and not trimmed mean except as context for underlying pressure."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool result: Fetched values: April 2026 headline CPI 4.2 percent after March 2026 4.6 percent; April transport costs fell 2.7 percent in the month but were still up 6.6 percent over the year; cash rate context reported at 4.35 percent.","Counter-consideration: upside risk is a renewed fuel or electricity jump after temporary relief fades, which would land above the interval if July All groups annual inflation prints above 5.3. Downside risk is a faster petrol reversal plus weak discretionary demand and housing-cost cooling, which would land below the interval if the first print is under 3.5."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Australia July 2026 Monthly CPI Indicator Forecast","Tool call: Fetched latest monthly CPI indicator reference points from ABS-reported public release coverage for the same All groups CPI annual movement variant."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-annual-rate-july-2026\nrunLabel: Fast rollout 2 of 3\nresolutionDate: 2026-08-26\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-annual-rate-july-2026.2026-07-10T16-42-38Z.australia-cpi-annual-rate-july-2026-thesis-analyst-fast-2026-07-10t16-42-38z.4b5f00c5ac0e5a6f","runId":"run.australia-cpi-annual-rate-july-2026.2026-07-10T16-42-38Z.australia-cpi-annual-rate-july-2026-thesis-analyst-fast-2026-07-10t16-42-38z.4b5f00c5ac0e5a6f","predictionId":"australia-cpi-annual-rate-july-2026","specId":"spec.australia-cpi-annual-rate-july-2026","runLabel":"Fast rollout 3 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: for this rate series I used the ABS monthly annual All groups CPI history since monthly annual movements begin in April 2025 as the reference class, with May 2026 at 4.0 as the persistence base rate. The recent annual-rate sequence is elevated but volatile: 3.8 in January, 3.7 in February, 4.6 in March, 4.2 in April, and 4.0 in May.","Prior/update/interval: persistence prior/model is May 2026 annual CPI at 4.0, historical sample is ABS Apr 2025-May 2026 monthly annual All groups CPI, adjustment components are high July 2025 base month (+1.3 monthly) lowering the July 2026 annual rate, assumed Jun-Jul 2026 original monthly CPI of about +0.4 and +0.6 partly offsetting that base effect, sticky housing/services/trimmed-mean pressure adding upside, and May fuel weakness adding uncertainty. Mechanics: July annual approx 1.040*(1.004*1.006)/(1.001*1.013)-1 = 0.0359, rounded to 3.6. Successive annual-rate changes are -0.3, -0.2, +1.1, +0.2, +0.4, +0.2, -0.4, +0.4, 0.0, -0.1, +0.9, -0.4, -0.2, so sigma = 0.47 from RMS successive changes and 1.28*sigma = 0.61; final implied 80% bounds are 3.6 +/- 0.61, rounded to 3.0 to 4.2."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this targets the ABS first-print July 2026 All groups CPI annual movement, percent, weighted average of eight capital cities, original annual movement, rounded to one decimal. The ABS current-release path now shows Consumer Price Index, Australia rather than the older Monthly Consumer Price Index Indicator wording, but I keep the ledger target identity and resolver text unchanged and note the sourceBinding discrepancy rather than changing the target.","Tool result: ABS release calendar lists Consumer Price Index, Australia on Wednesday 26 August 2026 at 11:30am AEST with reference period July 2026; the same ABS current release lists next releases 29/07/2026 for June 2026 and 26/08/2026 for July 2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this targets the ABS first-print July 2026 All groups CPI annual movement, percent, weighted average of eight capital cities, original annual movement, rounded to one decimal. The ABS current-release path now shows Consumer Price Index, Australia rather than the older Monthly Consumer Price Index Indicator wording, but I keep the ledger target identity and resolver text unchanged and note the sourceBinding discrepancy rather than changing the target.","Tool call: Opened ABS future releases for August 2026 and checked the CPI entry for the July 2026 reference period."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.2, distribution present, forecast step count 1.","evidence":["Tool call: Read ABS May 2026 group and analytical series details for current-release drivers.","Prior/update/interval: persistence prior/model is May 2026 annual CPI at 4.0, historical sample is ABS Apr 2025-May 2026 monthly annual All groups CPI, adjustment components are high July 2025 base month (+1.3 monthly) lowering the July 2026 annual rate, assumed Jun-Jul 2026 original monthly CPI of about +0.4 and +0.6 partly offsetting that base effect, sticky housing/services/trimmed-mean pressure adding upside, and May fuel weakness adding uncertainty. Mechanics: July annual approx 1.040*(1.004*1.006)/(1.001*1.013)-1 = 0.0359, rounded to 3.6. Successive annual-rate changes are -0.3, -0.2, +1.1, +0.2, +0.4, +0.2, -0.4, +0.4, 0.0, -0.1, +0.9, -0.4, -0.2, so sigma = 0.47 from RMS successive changes and 1.28*sigma = 0.61; final implied 80% bounds are 3.6 +/- 0.61, rounded to 3.0 to 4.2."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Read ABS May 2026 group and analytical series details for current-release drivers.","Tool result: Fetched May 2026 annual drivers: Housing 6.5%, Food and non-alcoholic beverages 3.3%, Transport 3.3%, Goods 4.2%, Services 3.7%, Automotive fuel 7.7%, Electricity 21.1%, New dwellings 5.6%, Rents 3.6%, and May original Transport monthly movement -3.9%."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Framing and exact resolver: this targets the ABS first-print July 2026 All groups CPI annual movement, percent, weighted average of eight capital cities, original annual movement, rounded to one decimal. The ABS current-release path now shows Consumer Price Index, Australia rather than the older Monthly Consumer Price Index Indicator wording, but I keep the ledger target identity and resolver text unchanged and note the sourceBinding discrepancy rather than changing the target.","Reference class and base rate: for this rate series I used the ABS monthly annual All groups CPI history since monthly annual movements begin in April 2025 as the reference class, with May 2026 at 4.0 as the persistence base rate. The recent annual-rate sequence is elevated but volatile: 3.8 in January, 3.7 in February, 4.6 in March, 4.2 in April, and 4.0 in May."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: persistence prior/model is May 2026 annual CPI at 4.0, historical sample is ABS Apr 2025-May 2026 monthly annual All groups CPI, adjustment components are high July 2025 base month (+1.3 monthly) lowering the July 2026 annual rate, assumed Jun-Jul 2026 original monthly CPI of about +0.4 and +0.6 partly offsetting that base effect, sticky housing/services/trimmed-mean pressure adding upside, and May fuel weakness adding uncertainty. Mechanics: July annual approx 1.040*(1.004*1.006)/(1.001*1.013)-1 = 0.0359, rounded to 3.6. Successive annual-rate changes are -0.3, -0.2, +1.1, +0.2, +0.4, +0.2, -0.4, +0.4, 0.0, -0.1, +0.9, -0.4, -0.2, so sigma = 0.47 from RMS successive changes and 1.28*sigma = 0.61; final implied 80% bounds are 3.6 +/- 0.61, rounded to 3.0 to 4.2.","Counter-considerations: upside risk is a rebound in fuel/transport after May's -3.9 original monthly transport fall plus still-high electricity or rent inflation, which would land above the interval if June and July monthly CPI together exceed roughly 1.7%. Downside risk is another energy-price fall or faster goods disinflation, which would land below the interval if June and July combined monthly CPI is near flat or negative despite services persistence."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-annual-rate-july-2026\nrunLabel: Fast rollout 3 of 3\nresolutionDate: 2026-08-26\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-annual-rate-july-2026.2026-07-10T16-53-08Z.australia-cpi-annual-rate-july-2026-thesis-analyst-median3-2026-07-10t16-53-08z.d03cf722412b52d3","runId":"run.australia-cpi-annual-rate-july-2026.2026-07-10T16-53-08Z.australia-cpi-annual-rate-july-2026-thesis-analyst-median3-2026-07-10t16-53-08z.d03cf722412b52d3","predictionId":"australia-cpi-annual-rate-july-2026","specId":"spec.australia-cpi-annual-rate-july-2026","runLabel":"Median of 3 rollouts","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and implicit outside-view language.","evidence":["Median-of-3 rollout ensemble","Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T16:19:40Z, 2026-07-10T16:30:43Z, 2026-07-10T16:42:38Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 8 source-context item(s), activity log present.","evidence":["Median CDF quantiles: q10 = 3.0, q50 = 3.8, q90 = 4.7. Constituent points [3.8, 4.4, 3.6] with 80% widths [1.8, 1.8, 1.2]; the median interval inherits the central rollout mass rather than averaging tails."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.7, distribution present, forecast step count 1.","evidence":["Median CDF quantiles: q10 = 3.0, q50 = 3.8, q90 = 4.7. Constituent points [3.8, 4.4, 3.6] with 80% widths [1.8, 1.8, 1.2]; the median interval inherits the central rollout mass rather than averaging tails.","Forecast: point 3.8, 80% interval [3, 4.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T16:19:40Z, 2026-07-10T16:30:43Z, 2026-07-10T16:42:38Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T16:19:40Z, 2026-07-10T16:30:43Z, 2026-07-10T16:42:38Z. Drivers and resolver fields mirror the rollout closest to the median.","Tool result: {rollout_points: [3.8, 4.4, 3.6], rollout_widths: [1.8, 1.8, 1.2], q10: 3.0, q50: 3.8, q90: 4.7}"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-annual-rate-july-2026\nrunLabel: Median of 3 rollouts\nresolutionDate: 2026-08-26\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-annual-rate-july-2026.2026-07-10T17-06-28Z.australia-cpi-annual-rate-july-2026-thesis-analyst-ladder-2026-07-10t17-06-28z.66723123db9355fa","runId":"run.australia-cpi-annual-rate-july-2026.2026-07-10T17-06-28Z.australia-cpi-annual-rate-july-2026-thesis-analyst-ladder-2026-07-10t17-06-28z.66723123db9355fa","predictionId":"australia-cpi-annual-rate-july-2026","specId":"spec.australia-cpi-annual-rate-july-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["The reference class/base rate is the six first-published annual observations from December 2025 through May 2026: 3.8%, 3.8%, 3.7%, 4.6%, 4.2%, and 4.0%. Persistence around the latest 4.0% is the outside-view anchor; the six-observation median is also 4.0%.","Prior/update/interval: persistence prior = May annual CPI of 4.0%, using the December-May historical sample 3.8, 3.8, 3.7, 4.6, 4.2, 4.0. Successive changes are 0.0, -0.1, +0.9, -0.4, and -0.2 percentage point; their sample sigma = 0.50. Because only five changes were available in the fetched pre-resolution history, 1.28*sigma = 1.28*0.50 = 0.64 point is a short-sample normal-approximation half-width, not an empirical 80% quantile. Adjustments are -0.1 for recent easing, +0.1 for persistent Housing/electricity pressure, and 0.0 net for other one-offs, leaving 4.0%. The ladder implies bounds of 3.3% and 4.8%, total width 1.5 points versus the sigma-based 1.28 points; the 1.17x widening is judgmental allowance for rebate and base-effect volatility."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["The canonical target is the first July 2026 Monthly Consumer Price Index Indicator All groups CPI annual movement, printed to one decimal, not trimmed mean, a seasonally adjusted monthly change, or a later replacement value. The registered sourceBinding points to a June 2026 Consumer Price Index page; this discrepancy is documented without changing the ledger target or resolver.","Tool call: Fetch the ABS January and February 2026 Consumer Price Index releases for the headline All groups annual series."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The canonical target is the first July 2026 Monthly Consumer Price Index Indicator All groups CPI annual movement, printed to one decimal, not trimmed mean, a seasonally adjusted monthly change, or a later replacement value. The registered sourceBinding points to a June 2026 Consumer Price Index page; this discrepancy is documented without changing the ledger target or resolver.","Tool call: Fetch the ABS January and February 2026 Consumer Price Index releases for the headline All groups annual series."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.5, distribution present, forecast step count 1.","evidence":["Tool call: Fetch May 2026 ABS component details for current-release mechanisms.","Prior/update/interval: persistence prior = May annual CPI of 4.0%, using the December-May historical sample 3.8, 3.8, 3.7, 4.6, 4.2, 4.0. Successive changes are 0.0, -0.1, +0.9, -0.4, and -0.2 percentage point; their sample sigma = 0.50. Because only five changes were available in the fetched pre-resolution history, 1.28*sigma = 1.28*0.50 = 0.64 point is a short-sample normal-approximation half-width, not an empirical 80% quantile. Adjustments are -0.1 for recent easing, +0.1 for persistent Housing/electricity pressure, and 0.0 net for other one-offs, leaving 4.0%. The ladder implies bounds of 3.3% and 4.8%, total width 1.5 points versus the sigma-based 1.28 points; the 1.17x widening is judgmental allowance for rebate and base-effect volatility."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and policy mechanisms are separated as follows: the level remains near 4%; momentum eased by 0.6 percentage point from March to May; volatile fuel, travel, and food can move individual months; and electricity-rebate exhaustion keeps Housing inflation elevated. These effects support a central value near 4.0% without extrapolating March's spike.","Prior/update/interval: persistence prior = May annual CPI of 4.0%, using the December-May historical sample 3.8, 3.8, 3.7, 4.6, 4.2, 4.0. Successive changes are 0.0, -0.1, +0.9, -0.4, and -0.2 percentage point; their sample sigma = 0.50. Because only five changes were available in the fetched pre-resolution history, 1.28*sigma = 1.28*0.50 = 0.64 point is a short-sample normal-approximation half-width, not an empirical 80% quantile. Adjustments are -0.1 for recent easing, +0.1 for persistent Housing/electricity pressure, and 0.0 net for other one-offs, leaving 4.0%. The ladder implies bounds of 3.3% and 4.8%, total width 1.5 points versus the sigma-based 1.28 points; the 1.17x widening is judgmental allowance for rebate and base-effect volatility."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Upside risk comes from further electricity-rebate unwinding, fuel disruption, or unusually strong rents and services; a combined shock would land above the interval. Downside risk comes from fuel reversal, discounting, or favorable July base effects; synchronized declines across volatile and core components would land below the interval. Outside the interval therefore requires a broader or larger shock than ordinary month-to-month variation."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Australia July 2026 annual CPI forecast","The canonical target is the first July 2026 Monthly Consumer Price Index Indicator All groups CPI annual movement, printed to one decimal, not trimmed mean, a seasonally adjusted monthly change, or a later replacement value. The registered sourceBinding points to a June 2026 Consumer Price Index page; this discrepancy is documented without changing the ledger target or resolver."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-annual-rate-july-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-08-26\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-annual-rate-july-2026.2026-07-10T17-17-18Z.australia-cpi-annual-rate-july-2026-thesis-analyst-fast-2026-07-10t17-17-18z.6d4282426def9243","runId":"run.australia-cpi-annual-rate-july-2026.2026-07-10T17-17-18Z.australia-cpi-annual-rate-july-2026-thesis-analyst-fast-2026-07-10t17-17-18z.6d4282426def9243","predictionId":"australia-cpi-annual-rate-july-2026","specId":"spec.australia-cpi-annual-rate-july-2026","runLabel":"Fast rollout 1 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["The reference class is the 14 official annual prints from April 2025 through May 2026. Its simple persistence base rate is the latest 4.0% print, but July 2025's unusually large 1.3% monthly increase will leave the twelve-month comparison. Assuming roughly 0.3% monthly inflation in both June and July 2026, June 2025's 0.1% base adds about 0.2 point before July 2025's 1.3% base subtracts about 1.0 point, implying approximately 3.2%.","Level and momentum remain firm because May annual CPI was 4.0% and Housing was 6.5%. The principal one-off is the July 2025 base effect; easing Transport inflation reinforces the decline. Policy works only with a lag over this horizon, so no separate large policy adjustment is imposed."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The target is the first-print July 2026 ABS All groups CPI annual movement for Australia, rounded to one decimal. All anchors use the same headline, not-seasonally-adjusted All groups variant. The ledger calls the release the Monthly CPI Indicator and supplies a future indicator URL, while the official ABS calendar labels it Consumer Price Index, Australia; the sourceBinding also incorrectly points to the June release, so the forecast retains the registered target and records the discrepancy.","Tool call: Fetch the ABS May 2026 Consumer Price Index, Australia release and its All groups history table."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The target is the first-print July 2026 ABS All groups CPI annual movement for Australia, rounded to one decimal. All anchors use the same headline, not-seasonally-adjusted All groups variant. The ledger calls the release the Monthly CPI Indicator and supplies a future indicator URL, while the official ABS calendar labels it Consumer Price Index, Australia; the sourceBinding also incorrectly points to the June release, so the forecast retains the registered target and records the discrepancy.","Tool call: Fetch the ABS May 2026 Consumer Price Index, Australia release and its All groups history table."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.2, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence model prior = 4.0%, using the 14-print April 2025–May 2026 official history. Adjustment components are +0.2 percentage point for replacing June 2025's 0.1% monthly rise with an assumed 0.3%, then -1.0 point for replacing July 2025's 1.3% rise with an assumed 0.3%: 4.0 + 0.2 - 1.0 = 3.2%. Successive annual-rate changes are -0.3, -0.2, +1.1, +0.2, +0.4, +0.2, -0.4, +0.4, 0.0, -0.1, +0.9, -0.4, and -0.2 percentage point; their sample standard deviation is sigma = 0.476. The empirical 80% half-width is 1.28*sigma = 0.610, giving 3.2 ± 0.61 = [2.59, 3.81], rounded to [2.6%, 3.8%].","Upside risk comes from another unusually large July price increase, persistent Housing inflation, or renewed fuel pressure and would land above the interval. Downside risk comes from a flat or negative July monthly print combined with broader goods disinflation and could land below the interval. An annual print outside the interval would require the two-month June–July price change to differ materially from the roughly 0.6% central assumption."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level and momentum remain firm because May annual CPI was 4.0% and Housing was 6.5%. The principal one-off is the July 2025 base effect; easing Transport inflation reinforces the decline. Policy works only with a lag over this horizon, so no separate large policy adjustment is imposed.","Upside risk comes from another unusually large July price increase, persistent Housing inflation, or renewed fuel pressure and would land above the interval. Downside risk comes from a flat or negative July monthly print combined with broader goods disinflation and could land below the interval. An annual print outside the interval would require the two-month June–July price change to differ materially from the roughly 0.6% central assumption."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool call: Inspect the ABS group contributions and recent headline components in the May 2026 release.","The reference class is the 14 official annual prints from April 2025 through May 2026. Its simple persistence base rate is the latest 4.0% print, but July 2025's unusually large 1.3% monthly increase will leave the twelve-month comparison. Assuming roughly 0.3% monthly inflation in both June and July 2026, June 2025's 0.1% base adds about 0.2 point before July 2025's 1.3% base subtracts about 1.0 point, implying approximately 3.2%."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Australia July 2026 headline CPI forecast","The target is the first-print July 2026 ABS All groups CPI annual movement for Australia, rounded to one decimal. All anchors use the same headline, not-seasonally-adjusted All groups variant. The ledger calls the release the Monthly CPI Indicator and supplies a future indicator URL, while the official ABS calendar labels it Consumer Price Index, Australia; the sourceBinding also incorrectly points to the June release, so the forecast retains the registered target and records the discrepancy."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-annual-rate-july-2026\nrunLabel: Fast rollout 1 of 3\nresolutionDate: 2026-08-26\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-annual-rate-july-2026.2026-07-10T17-23-36Z.australia-cpi-annual-rate-july-2026-thesis-analyst-fast-2026-07-10t17-23-36z.3ebbb1e01ca37f82","runId":"run.australia-cpi-annual-rate-july-2026.2026-07-10T17-23-36Z.australia-cpi-annual-rate-july-2026-thesis-analyst-fast-2026-07-10t17-23-36z.3ebbb1e01ca37f82","predictionId":"australia-cpi-annual-rate-july-2026","specId":"spec.australia-cpi-annual-rate-july-2026","runLabel":"Fast rollout 2 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["The reference class and base rate are short-horizon monthly annual-CPI persistence. The same-series path from January through May was 3.8%, 3.7%, 4.6%, 4.2%, and 4.0%. Persistence anchors July near 4.0%, while the RBA's 4.8% June-quarter projection and fuel/raw-material pass-through argue for an upward adjustment.","Prior/update/interval: persistence prior = May annual CPI 4.0%; historical sample = January-May annual rates 3.8, 3.7, 4.6, 4.2, 4.0; adjustments = +0.5 percentage point for the RBA near-term energy/cost path and -0.1 for easing momentum plus July's strong base, giving 4.0 + 0.5 - 0.1 = 4.4%. Successive changes are -0.1, +0.9, -0.4, -0.2 percentage point; their sample standard deviation is sigma = 0.50. The Gaussian 80% half-width is roughly 1.28*sigma = 1.28*0.50 = 0.64 percentage point; rounding bounds to the ABS one-decimal print grid gives 4.4 - 0.6 = 3.8 and 4.4 + 0.6 = 5.0."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["The resolver is the first July 2026 ABS All groups CPI annual movement, national weighted average of eight capital cities, original headline series, printed to one decimal. ABS now labels the release Consumer Price Index, Australia rather than Monthly CPI Indicator. The ledger's June-page sourceBinding is discrepant; target identity and first-print policy are unchanged.","Tool result: The ABS calendar schedules Consumer Price Index, Australia, reference period July 2026, for Wednesday 26 August 2026 at 11:30am AEST."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The resolver is the first July 2026 ABS All groups CPI annual movement, national weighted average of eight capital cities, original headline series, printed to one decimal. ABS now labels the release Consumer Price Index, Australia rather than Monthly CPI Indicator. The ledger's June-page sourceBinding is discrepant; target identity and first-print policy are unchanged.","Tool call: Inspect ABS January and February 2026 CPI releases for the same All groups annual series."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.2, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = May annual CPI 4.0%; historical sample = January-May annual rates 3.8, 3.7, 4.6, 4.2, 4.0; adjustments = +0.5 percentage point for the RBA near-term energy/cost path and -0.1 for easing momentum plus July's strong base, giving 4.0 + 0.5 - 0.1 = 4.4%. Successive changes are -0.1, +0.9, -0.4, -0.2 percentage point; their sample standard deviation is sigma = 0.50. The Gaussian 80% half-width is roughly 1.28*sigma = 1.28*0.50 = 0.64 percentage point; rounding bounds to the ABS one-decimal print grid gives 4.4 - 0.6 = 3.8 and 4.4 + 0.6 = 5.0.","Upside risk comes from persistent fuel disruption, second-round transport and materials pass-through, or another electricity-price increase and would land above the interval at 5.1% or more. Downside risk comes from a rapid fuel reversal combined with the large July 2025 base effect and would land below the interval at 3.7% or less."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and policy mechanisms point in different directions: the May level was 4.0% and recent momentum eased; fuel and electricity-rebate effects lift the level; July rolls over a large 1.3% July 2025 monthly increase, restraining annual inflation; tighter monetary policy mainly weighs on subsequent months.","Prior/update/interval: persistence prior = May annual CPI 4.0%; historical sample = January-May annual rates 3.8, 3.7, 4.6, 4.2, 4.0; adjustments = +0.5 percentage point for the RBA near-term energy/cost path and -0.1 for easing momentum plus July's strong base, giving 4.0 + 0.5 - 0.1 = 4.4%. Successive changes are -0.1, +0.9, -0.4, -0.2 percentage point; their sample standard deviation is sigma = 0.50. The Gaussian 80% half-width is roughly 1.28*sigma = 1.28*0.50 = 0.64 percentage point; rounding bounds to the ABS one-decimal print grid gives 4.4 - 0.6 = 3.8 and 4.4 + 0.6 = 5.0."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool result: The RBA forecast headline CPI inflation at 4.8% year-ended June 2026 and 4.0% year-ended December 2026, with trimmed mean inflation at 3.8% and 3.5% respectively; it reported March headline inflation of 4.6%, including a 0.8 percentage-point fuel contribution.","Upside risk comes from persistent fuel disruption, second-round transport and materials pass-through, or another electricity-price increase and would land above the interval at 5.1% or more. Downside risk comes from a rapid fuel reversal combined with the large July 2025 base effect and would land below the interval at 3.7% or less."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Australia July 2026 annual CPI forecast","Tool result: The RBA forecast headline CPI inflation at 4.8% year-ended June 2026 and 4.0% year-ended December 2026, with trimmed mean inflation at 3.8% and 3.5% respectively; it reported March headline inflation of 4.6%, including a 0.8 percentage-point fuel contribution."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-annual-rate-july-2026\nrunLabel: Fast rollout 2 of 3\nresolutionDate: 2026-08-26\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-annual-rate-july-2026.2026-07-10T17-29-16Z.australia-cpi-annual-rate-july-2026-thesis-analyst-fast-2026-07-10t17-29-16z.d3d78148cb58b5a9","runId":"run.australia-cpi-annual-rate-july-2026.2026-07-10T17-29-16Z.australia-cpi-annual-rate-july-2026-thesis-analyst-fast-2026-07-10t17-29-16z.d3d78148cb58b5a9","predictionId":"australia-cpi-annual-rate-july-2026","specId":"spec.australia-cpi-annual-rate-july-2026","runLabel":"Fast rollout 3 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: Read the ABS historical All groups monthly and annual movements in the April 2026 release.","The reference class or base rate is monthly annual-CPI persistence since monthly annual observations began in April 2025: 2.4%, 2.1%, 1.9%, 3.0%, 3.2%, 3.6%, 3.8%, 3.4%, 3.8%, 3.8%, 3.7%, 4.6%, 4.2%, and 4.0%. Persistence alone anchors July near 4.0%, but the unusually large July 2025 monthly increase creates a strong adverse base effect."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The target is the first-print ABS All groups CPI annual movement for July 2026, printed to one decimal. All anchors use this same original, not seasonally adjusted, All groups variant. ABS now labels the publication Consumer Price Index, Australia; the ledger's generic sourceBinding incorrectly points to the June page, while the exact July release page is the substantive resolver.","Tool call: Read the ABS Consumer Price Index, Australia, May 2026 release and its All groups annual-movement table."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The target is the first-print ABS All groups CPI annual movement for July 2026, printed to one decimal. All anchors use this same original, not seasonally adjusted, All groups variant. ABS now labels the publication Consumer Price Index, Australia; the ledger's generic sourceBinding incorrectly points to the June page, while the exact July release page is the substantive resolver.","Tool call: Read the ABS Consumer Price Index, Australia, May 2026 release and its All groups annual-movement table."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.2, distribution present, forecast step count 1.","evidence":["Prior/update/interval: The persistence prior is May's 4.0%, using the 14 monthly annual observations from April 2025 through May 2026. Adjustments are approximately -0.5 percentage point for July 2025's 1.3% monthly rise leaving the annual comparison, +0.2 for firm housing/electricity and underlying inflation, and 0.0 net for softer fuel and other momentum, yielding 4.0 - 0.5 + 0.2 = 3.7%. Across the 13 successive annual-rate changes, sample sigma = 0.48 percentage point; 1.28*sigma = 0.61, so the rounded 80% half-width is 0.6 and the implied bounds are 3.1% to 4.3%.","Upside risk comes from another large electricity-tariff step, persistent rents, or renewed fuel inflation and would land above the interval if July prints above 4.3%. Downside risk comes from a weak July monthly print combined with the 1.3% July 2025 base rolling out; a broad goods or fuel decline could put the result outside the interval below 3.1%."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level and momentum effects point in different directions. Headline annual inflation eased from 4.6% to 4.2% to 4.0%, while May trimmed mean rose to 3.6% from 3.4%. Housing inflation was 6.5%, including electricity at 21.1%, but goods inflation slowed to 4.2% and automotive-fuel inflation fell to 7.7% from 18.6%.","Prior/update/interval: The persistence prior is May's 4.0%, using the 14 monthly annual observations from April 2025 through May 2026. Adjustments are approximately -0.5 percentage point for July 2025's 1.3% monthly rise leaving the annual comparison, +0.2 for firm housing/electricity and underlying inflation, and 0.0 net for softer fuel and other momentum, yielding 4.0 - 0.5 + 0.2 = 3.7%. Across the 13 successive annual-rate changes, sample sigma = 0.48 percentage point; 1.28*sigma = 0.61, so the rounded 80% half-width is 0.6 and the implied bounds are 3.1% to 4.3%."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The reference class or base rate is monthly annual-CPI persistence since monthly annual observations began in April 2025: 2.4%, 2.1%, 1.9%, 3.0%, 3.2%, 3.6%, 3.8%, 3.4%, 3.8%, 3.8%, 3.7%, 4.6%, 4.2%, and 4.0%. Persistence alone anchors July near 4.0%, but the unusually large July 2025 monthly increase creates a strong adverse base effect.","Level and momentum effects point in different directions. Headline annual inflation eased from 4.6% to 4.2% to 4.0%, while May trimmed mean rose to 3.6% from 3.4%. Housing inflation was 6.5%, including electricity at 21.1%, but goods inflation slowed to 4.2% and automotive-fuel inflation fell to 7.7% from 18.6%."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Australia July 2026 All groups CPI annual-rate forecast","The target is the first-print ABS All groups CPI annual movement for July 2026, printed to one decimal. All anchors use this same original, not seasonally adjusted, All groups variant. ABS now labels the publication Consumer Price Index, Australia; the ledger's generic sourceBinding incorrectly points to the June page, while the exact July release page is the substantive resolver."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-annual-rate-july-2026\nrunLabel: Fast rollout 3 of 3\nresolutionDate: 2026-08-26\ntraceLineCount: 13\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-annual-rate-july-2026.2026-07-10T17-33-53Z.australia-cpi-annual-rate-july-2026-thesis-analyst-median3-2026-07-10t17-33-53z.58b868e0852b13dc","runId":"run.australia-cpi-annual-rate-july-2026.2026-07-10T17-33-53Z.australia-cpi-annual-rate-july-2026-thesis-analyst-median3-2026-07-10t17-33-53z.58b868e0852b13dc","predictionId":"australia-cpi-annual-rate-july-2026","specId":"spec.australia-cpi-annual-rate-july-2026","runLabel":"Median of 3 rollouts","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and implicit outside-view language.","evidence":["Median-of-3 rollout ensemble","Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T17:17:18Z, 2026-07-10T17:23:36Z, 2026-07-10T17:29:16Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 8 source-context item(s), activity log present.","evidence":["Median CDF quantiles: q10 = 3.1, q50 = 3.7, q90 = 4.3. Constituent points [3.2, 4.4, 3.7] with 80% widths [1.2, 1.2, 1.2]; the median interval inherits the central rollout mass rather than averaging tails."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.2, distribution present, forecast step count 1.","evidence":["Median CDF quantiles: q10 = 3.1, q50 = 3.7, q90 = 4.3. Constituent points [3.2, 4.4, 3.7] with 80% widths [1.2, 1.2, 1.2]; the median interval inherits the central rollout mass rather than averaging tails.","Forecast: point 3.7, 80% interval [3.1, 4.3]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T17:17:18Z, 2026-07-10T17:23:36Z, 2026-07-10T17:29:16Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-10T17:17:18Z, 2026-07-10T17:23:36Z, 2026-07-10T17:29:16Z. Drivers and resolver fields mirror the rollout closest to the median.","Tool result: {rollout_points: [3.2, 4.4, 3.7], rollout_widths: [1.2, 1.2, 1.2], q10: 3.1, q50: 3.7, q90: 4.3}"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-annual-rate-july-2026\nrunLabel: Median of 3 rollouts\nresolutionDate: 2026-08-26\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-annual-rate-july-2026.2026-07-10T21-15-57Z.australia-cpi-annual-rate-july-2026-thesis-analyst-ladder-v2-2026-07-10t21-15-57z.0389c7ce36711253","runId":"run.australia-cpi-annual-rate-july-2026.2026-07-10T21-15-57Z.australia-cpi-annual-rate-july-2026-thesis-analyst-ladder-v2-2026-07-10t21-15-57z.0389c7ce36711253","predictionId":"australia-cpi-annual-rate-july-2026","specId":"spec.australia-cpi-annual-rate-july-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: for near-term Australian monthly CPI indicator all-groups annual forecasts, the strongest public reference class is recent same-series persistence plus one- to three-month shock reversal. The fetched same-variant sequence 3.7%, 4.6%, 4.2%, 4.0% anchors the ladder span: most mass stays in the high-3s to high-4s, with a meaningful right tail if fuel or housing re-accelerates.","Prior/update/interval: persistence prior is the recent same-series All groups CPI annual movement centered around the May 2026 4.0% print, using the February-May 2026 sample of 3.7%, 4.6%, 4.2%, and 4.0%; I apply a judgmental +0.3pp central update, roughly +0.15pp for July fuel-excise/oil pass-through risk, +0.10pp for sticky housing and rents, and +0.05pp for monthly-indicator sampling and momentum risk, limited by likely normalization from the March fuel spike. The interval method is a threshold ladder grounded on the fetched 3.7%-4.6% recent range, widened for two unknown monthly prints before July and one-off fuel-policy effects; the 10th-90th percentile 80% interval is 3.5 to 5.2 with median 4.3."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing: the resolver is the ABS Monthly Consumer Price Index Indicator, Australia, July 2026 release, All groups CPI annual movement, first print, in percent rounded to one decimal. I use the same monthly-indicator all-groups annual variant for anchors; I do not mix in quarterly CPI, seasonally adjusted variants, trimmed mean, or later revisions.","Tool call: Check ABS release calendar and target page contract for the July 2026 Monthly Consumer Price Index Indicator release."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing: the resolver is the ABS Monthly Consumer Price Index Indicator, Australia, July 2026 release, All groups CPI annual movement, first print, in percent rounded to one decimal. I use the same monthly-indicator all-groups annual variant for anchors; I do not mix in quarterly CPI, seasonally adjusted variants, trimmed mean, or later revisions.","Tool call: Check ABS release calendar and target page contract for the July 2026 Monthly Consumer Price Index Indicator release."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.7, distribution present, forecast step count 1.","evidence":["Reference class and base rate: for near-term Australian monthly CPI indicator all-groups annual forecasts, the strongest public reference class is recent same-series persistence plus one- to three-month shock reversal. The fetched same-variant sequence 3.7%, 4.6%, 4.2%, 4.0% anchors the ladder span: most mass stays in the high-3s to high-4s, with a meaningful right tail if fuel or housing re-accelerates.","Prior/update/interval: persistence prior is the recent same-series All groups CPI annual movement centered around the May 2026 4.0% print, using the February-May 2026 sample of 3.7%, 4.6%, 4.2%, and 4.0%; I apply a judgmental +0.3pp central update, roughly +0.15pp for July fuel-excise/oil pass-through risk, +0.10pp for sticky housing and rents, and +0.05pp for monthly-indicator sampling and momentum risk, limited by likely normalization from the March fuel spike. The interval method is a threshold ladder grounded on the fetched 3.7%-4.6% recent range, widened for two unknown monthly prints before July and one-off fuel-policy effects; the 10th-90th percentile 80% interval is 3.5 to 5.2 with median 4.3."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior is the recent same-series All groups CPI annual movement centered around the May 2026 4.0% print, using the February-May 2026 sample of 3.7%, 4.6%, 4.2%, and 4.0%; I apply a judgmental +0.3pp central update, roughly +0.15pp for July fuel-excise/oil pass-through risk, +0.10pp for sticky housing and rents, and +0.05pp for monthly-indicator sampling and momentum risk, limited by likely normalization from the March fuel spike. The interval method is a threshold ladder grounded on the fetched 3.7%-4.6% recent range, widened for two unknown monthly prints before July and one-off fuel-policy effects; the 10th-90th percentile 80% interval is 3.5 to 5.2 with median 4.3.","Review disposition: accepted the warning to make the +0.3pp upward update explicit and judgmental, with approximate component contributions; accepted the confidence-semantics suggestion by naming the ladder-derived 10th-90th percentile 80% interval. I did not add a new oil or policy datapoint because it was not in the public evidence available to the draft trace."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence prior is the recent same-series All groups CPI annual movement centered around the May 2026 4.0% print, using the February-May 2026 sample of 3.7%, 4.6%, 4.2%, and 4.0%; I apply a judgmental +0.3pp central update, roughly +0.15pp for July fuel-excise/oil pass-through risk, +0.10pp for sticky housing and rents, and +0.05pp for monthly-indicator sampling and momentum risk, limited by likely normalization from the March fuel spike. The interval method is a threshold ladder grounded on the fetched 3.7%-4.6% recent range, widened for two unknown monthly prints before July and one-off fuel-policy effects; the 10th-90th percentile 80% interval is 3.5 to 5.2 with median 4.3.","Counter-considerations: upside risk is a larger July fuel rebound, rent acceleration, or supply shock that would land above the interval near 5.3% or higher. Downside risk is a sharper fuel reversal, energy subsidy effect, or broad goods disinflation that would land outside the interval below 3.5%. The central case keeps annual inflation above target but below the March shock peak."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Australia July 2026 monthly CPI indicator forecast","Reference class and base rate: for near-term Australian monthly CPI indicator all-groups annual forecasts, the strongest public reference class is recent same-series persistence plus one- to three-month shock reversal. The fetched same-variant sequence 3.7%, 4.6%, 4.2%, 4.0% anchors the ladder span: most mass stays in the high-3s to high-4s, with a meaningful right tail if fuel or housing re-accelerates."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-annual-rate-july-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-08-26\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-annual-rate-july-2026.2026-07-10T21-40-41Z.australia-cpi-annual-rate-july-2026-thesis-analyst-ladder-v2-2026-07-10t21-40-41z.56bddf549add3136","runId":"run.australia-cpi-annual-rate-july-2026.2026-07-10T21-40-41Z.australia-cpi-annual-rate-july-2026-thesis-analyst-ladder-v2-2026-07-10t21-40-41z.56bddf549add3136","predictionId":"australia-cpi-annual-rate-july-2026","specId":"spec.australia-cpi-annual-rate-july-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Reference class/base rate: the fetched annual sequence from July 2025 through May 2026 was 3.0%, 3.2%, 3.6%, 3.8%, 3.4%, 3.8%, 3.8%, 3.7%, 4.6%, 4.2%, and 4.0%. Persistence near the latest 4.0% is the outside-view anchor, while the observed range of 3.0% to 4.6% anchors the ladder span.","Level, momentum, one-off, and policy mechanisms point in different directions. The 4.0% May level and 3.6% trimmed mean show persistent underlying pressure; headline momentum eased from March. Expiring electricity rebates raised measured housing inflation, while the unusually large 13.5% July 2025 electricity increase and 1.3% headline monthly increase become adverse base effects when they roll out. Higher fuel costs can offset part of that decline."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The target is the original, not seasonally adjusted, All groups CPI annual movement for July 2026, printed to one decimal by ABS. It resolves only to the first print. The ledger calls the release the Monthly CPI Indicator and supplies a sourceBinding for the June CPI page, while the current ABS calendar labels the July publication Consumer Price Index, Australia; I preserve the registered dataPointId and resolver and document this discrepancy rather than changing target identity.","Tool call: Fetch the ABS May 2026 Consumer Price Index release and its All groups CPI history."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Australia All groups CPI annual movement, July 2026 first print","The target is the original, not seasonally adjusted, All groups CPI annual movement for July 2026, printed to one decimal by ABS. It resolves only to the first print. The ledger calls the release the Monthly CPI Indicator and supplies a sourceBinding for the June CPI page, while the current ABS calendar labels the July publication Consumer Price Index, Australia; I preserve the registered dataPointId and resolver and document this discrepancy rather than changing target identity."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.6, distribution present, forecast step count 1.","evidence":["The ten consecutive changes in the fetched July 2025-May 2026 annual-rate sequence were +0.2, +0.4, +0.2, -0.4, +0.4, 0.0, -0.1, +0.9, -0.4, and -0.2 percentage points, with a sample standard deviation of about 0.4 point. Scaling that volatility across the two releases from May to July gives roughly 1.28 × 0.4 × sqrt(2) = 0.7 point for an 80% persistence interval; allowing additional uncertainty around electricity base effects and fuel supports ladder tails about 0.8 point from the 4.0% anchor.","Prior/update/interval: A latest-value persistence model uses the July 2025-May 2026 reference-class sample (3.0%-4.6%) and starts from May's 4.0%. Updates comprise sticky services/non-tradables and fuel pressure upward, offset by recent headline slowing and the July 2025 electricity/headline base effects. Historical annual-rate change volatility implies about a 0.7-point two-release 80% width around persistence; direct threshold-ladder quantile inversion, widened modestly for one-off uncertainty, yields final implied bounds of 3.2% to 4.8% and a 4.0% median."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and policy mechanisms point in different directions. The 4.0% May level and 3.6% trimmed mean show persistent underlying pressure; headline momentum eased from March. Expiring electricity rebates raised measured housing inflation, while the unusually large 13.5% July 2025 electricity increase and 1.3% headline monthly increase become adverse base effects when they roll out. Higher fuel costs can offset part of that decline.","Prior/update/interval: A latest-value persistence model uses the July 2025-May 2026 reference-class sample (3.0%-4.6%) and starts from May's 4.0%. Updates comprise sticky services/non-tradables and fuel pressure upward, offset by recent headline slowing and the July 2025 electricity/headline base effects. Historical annual-rate change volatility implies about a 0.7-point two-release 80% width around persistence; direct threshold-ladder quantile inversion, widened modestly for one-off uncertainty, yields final implied bounds of 3.2% to 4.8% and a 4.0% median."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool result: In May 2026, Housing inflation was 6.5%, Transport 3.3%, Food 3.3%, trimmed mean 3.6%, non-tradables 4.7%, and tradables 2.5%. Electricity rose 21.1% annually but only 3.9% excluding government-rebate effects.","Level, momentum, one-off, and policy mechanisms point in different directions. The 4.0% May level and 3.6% trimmed mean show persistent underlying pressure; headline momentum eased from March. Expiring electricity rebates raised measured housing inflation, while the unusually large 13.5% July 2025 electricity increase and 1.3% headline monthly increase become adverse base effects when they roll out. Higher fuel costs can offset part of that decline."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The target is the original, not seasonally adjusted, All groups CPI annual movement for July 2026, printed to one decimal by ABS. It resolves only to the first print. The ledger calls the release the Monthly CPI Indicator and supplies a sourceBinding for the June CPI page, while the current ABS calendar labels the July publication Consumer Price Index, Australia; I preserve the registered dataPointId and resolver and document this discrepancy rather than changing target identity.","Level, momentum, one-off, and policy mechanisms point in different directions. The 4.0% May level and 3.6% trimmed mean show persistent underlying pressure; headline momentum eased from March. Expiring electricity rebates raised measured housing inflation, while the unusually large 13.5% July 2025 electricity increase and 1.3% headline monthly increase become adverse base effects when they roll out. Higher fuel costs can offset part of that decline."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-annual-rate-july-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-08-26\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-annual-rate-july-2026.2026-07-10T22-00-19Z.australia-cpi-annual-rate-july-2026-thesis-analyst-ladder-v2-2026-07-10t22-00-19z.0c2d07ef65758f06","runId":"run.australia-cpi-annual-rate-july-2026.2026-07-10T22-00-19Z.australia-cpi-annual-rate-july-2026-thesis-analyst-ladder-v2-2026-07-10t22-00-19z.0c2d07ef65758f06","predictionId":"australia-cpi-annual-rate-july-2026","specId":"spec.australia-cpi-annual-rate-july-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Reference class/base rate: the six fetched monthly annual prints span 3.7% to 4.6%, with a 4.0% latest print and a 3.9% simple average. All anchors are the same national All groups CPI annual-movement variant, not quarterly CPI or a smoothed series.","Level and momentum point mildly lower after the 4.6% March spike eased to 4.2% and then 4.0%; persistent housing inflation and a 3.6% trimmed mean limit the expected decline. June and July observations were not yet published at this forecast date. No separate fitted time-series model was used: the six-month sample is too short and volatile for a reliable fitted model, so the persistence/reference-class prior is used instead."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Target framing: forecast the ABS All groups CPI annual movement for July 2026 in original terms, rounded to one decimal and resolved on the first print. The registered resolver names the ceased Monthly Consumer Price Index Indicator and its sourceBinding points to the June 2026 CPI page; the active ABS production is Consumer Price Index, Australia. I retain the supplied dataPointId, date, and first-print policy rather than changing target identity.","Tool call: Fetched the ABS Consumer Price Index, Australia May 2026 release table for the same All groups CPI annual-movement variant."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Target framing: forecast the ABS All groups CPI annual movement for July 2026 in original terms, rounded to one decimal and resolved on the first print. The registered resolver names the ceased Monthly Consumer Price Index Indicator and its sourceBinding points to the June 2026 CPI page; the active ABS production is Consumer Price Index, Australia. I retain the supplied dataPointId, date, and first-print policy rather than changing target identity.","Tool call: Fetched the ABS Consumer Price Index, Australia May 2026 release table for the same All groups CPI annual-movement variant."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.8, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence/reference-class prior is the fetched Dec-May All groups sequence (3.8, 3.8, 3.7, 4.6, 4.2, 4.0), centered near its 3.9% mean; adjustments are easing headline momentum, persistent 6.5% housing inflation, and uncertainty from volatile monthly components. The 80% interval is the ladder-derived 10th-to-90th percentile range, calibrated with rung placement against the fetched 3.7% trough and 4.6% March high, yielding 3.5% to 4.3% after one-decimal rounding.","Counter-consideration: upside risk is a renewed housing, fuel, or food acceleration that would land above the interval; downside risk is a broad decline in goods and services prices that would land below the interval. A July print above 4.3% or below 3.5% is outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level and momentum point mildly lower after the 4.6% March spike eased to 4.2% and then 4.0%; persistent housing inflation and a 3.6% trimmed mean limit the expected decline. June and July observations were not yet published at this forecast date. No separate fitted time-series model was used: the six-month sample is too short and volatile for a reliable fitted model, so the persistence/reference-class prior is used instead.","Prior/update/interval: persistence/reference-class prior is the fetched Dec-May All groups sequence (3.8, 3.8, 3.7, 4.6, 4.2, 4.0), centered near its 3.9% mean; adjustments are easing headline momentum, persistent 6.5% housing inflation, and uncertainty from volatile monthly components. The 80% interval is the ladder-derived 10th-to-90th percentile range, calibrated with rung placement against the fetched 3.7% trough and 4.6% March high, yielding 3.5% to 4.3% after one-decimal rounding."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence/reference-class prior is the fetched Dec-May All groups sequence (3.8, 3.8, 3.7, 4.6, 4.2, 4.0), centered near its 3.9% mean; adjustments are easing headline momentum, persistent 6.5% housing inflation, and uncertainty from volatile monthly components. The 80% interval is the ladder-derived 10th-to-90th percentile range, calibrated with rung placement against the fetched 3.7% trough and 4.6% March high, yielding 3.5% to 4.3% after one-decimal rounding.","Counter-consideration: upside risk is a renewed housing, fuel, or food acceleration that would land above the interval; downside risk is a broad decline in goods and services prices that would land below the interval. A July print above 4.3% or below 3.5% is outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Target framing: forecast the ABS All groups CPI annual movement for July 2026 in original terms, rounded to one decimal and resolved on the first print. The registered resolver names the ceased Monthly Consumer Price Index Indicator and its sourceBinding points to the June 2026 CPI page; the active ABS production is Consumer Price Index, Australia. I retain the supplied dataPointId, date, and first-print policy rather than changing target identity.","Level and momentum point mildly lower after the 4.6% March spike eased to 4.2% and then 4.0%; persistent housing inflation and a 3.6% trimmed mean limit the expected decline. June and July observations were not yet published at this forecast date. No separate fitted time-series model was used: the six-month sample is too short and volatile for a reliable fitted model, so the persistence/reference-class prior is used instead."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-annual-rate-july-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-08-26\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-annual-rate-july-2026.2026-07-10T22-19-13Z.australia-cpi-annual-rate-july-2026-thesis-analyst-ladder-v2-2026-07-10t22-19-13z.2d3e19681d5603a2","runId":"run.australia-cpi-annual-rate-july-2026.2026-07-10T22-19-13Z.australia-cpi-annual-rate-july-2026-thesis-analyst-ladder-v2-2026-07-10t22-19-13z.2d3e19681d5603a2","predictionId":"australia-cpi-annual-rate-july-2026","specId":"spec.australia-cpi-annual-rate-july-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["The base rate/reference class is the recent complete monthly ABS sequence: annual inflation was 3.0% to 3.8% across July 2025 to January 2026, then 3.7%, 4.6%, 4.2%, and 4.0% from February to May 2026. The central tendency has recently eased, but the level remains above the mid-3% range.","Level and momentum point modestly lower: the March spike of 4.6% has fallen by 0.6 percentage points over two releases. Persistent housing and non-tradables inflation provide an upside offset, while fuel and other volatile components can create a sizeable month-specific base effect. The target is the same gross, unadjusted All groups CPI annual movement throughout; no trimmed-mean or seasonally adjusted variant is substituted."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["This targets the ABS All groups CPI annual movement for July 2026, first print, unadjusted and rounded to one decimal. The ABS release calendar verifies publication on 2026-08-26 at 11:30am AEST. The registered sourceBinding names the June 2026 CPI page, but the target remains the July 2026 first-print dataPointId and July release page specified by the ledger.","Tool result: Fetched official annual movements: Jul-25 3.0%, Aug-25 3.2%, Sep-25 3.6%, Oct-25 3.8%, Nov-25 3.4%, Dec-25 3.8%, Jan-26 3.8%, Feb-26 3.7%, Mar-26 4.6%, Apr-26 4.2%, May-26 4.0%."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["This targets the ABS All groups CPI annual movement for July 2026, first print, unadjusted and rounded to one decimal. The ABS release calendar verifies publication on 2026-08-26 at 11:30am AEST. The registered sourceBinding names the June 2026 CPI page, but the target remains the July 2026 first-print dataPointId and July release page specified by the ledger.","Tool call: ABS May 2026 CPI release, All groups annual movement table"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.2, distribution present, forecast step count 1.","evidence":["Prior/update/interval: Starting from a persistence prior centered near the recent May 2026 reading of 4.0%, using the ABS Jul-25-to-May-26 reference class, I apply a modest easing adjustment for the March-to-May decline, retain an upside adjustment for 4.7% non-tradables inflation and housing persistence, and allow volatile fuel/base effects. The ladder-implied 80% central interval is 3.3% to 4.5%, with the rungs anchored by the fetched 3.0%, 3.2%, 3.6%, 3.8%, 4.6%, 4.2%, and 4.0% observations.","The main upside risk is a renewed fuel or housing-related acceleration that would land above the interval, especially at 4.6% or higher. The main downside risk is another large favorable volatile-item or base-effect move, with a result at or below 3.2% landing outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level and momentum point modestly lower: the March spike of 4.6% has fallen by 0.6 percentage points over two releases. Persistent housing and non-tradables inflation provide an upside offset, while fuel and other volatile components can create a sizeable month-specific base effect. The target is the same gross, unadjusted All groups CPI annual movement throughout; no trimmed-mean or seasonally adjusted variant is substituted."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["This targets the ABS All groups CPI annual movement for July 2026, first print, unadjusted and rounded to one decimal. The ABS release calendar verifies publication on 2026-08-26 at 11:30am AEST. The registered sourceBinding names the June 2026 CPI page, but the target remains the July 2026 first-print dataPointId and July release page specified by the ledger.","The base rate/reference class is the recent complete monthly ABS sequence: annual inflation was 3.0% to 3.8% across July 2025 to January 2026, then 3.7%, 4.6%, 4.2%, and 4.0% from February to May 2026. The central tendency has recently eased, but the level remains above the mid-3% range."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["This targets the ABS All groups CPI annual movement for July 2026, first print, unadjusted and rounded to one decimal. The ABS release calendar verifies publication on 2026-08-26 at 11:30am AEST. The registered sourceBinding names the June 2026 CPI page, but the target remains the July 2026 first-print dataPointId and July release page specified by the ledger.","Level and momentum point modestly lower: the March spike of 4.6% has fallen by 0.6 percentage points over two releases. Persistent housing and non-tradables inflation provide an upside offset, while fuel and other volatile components can create a sizeable month-specific base effect. The target is the same gross, unadjusted All groups CPI annual movement throughout; no trimmed-mean or seasonally adjusted variant is substituted."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-annual-rate-july-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-08-26\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-monthly-gdp-growth-june-2026.2026-07-10T05-13-38Z.6498de0f976fe845","runId":"run.canada-monthly-gdp-growth-june-2026.2026-07-10T05-13-38Z.6498de0f976fe845","predictionId":"canada-monthly-gdp-growth-june-2026","specId":"spec.canada-monthly-gdp-growth-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.51,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 8 historical point(s) and explicit outside-view language.","evidence":["Tool call: Opened prior The Daily releases for March, February, January, and November 2025/2026 GDP by industry.","The base rate/reference class is the recent official and official-advance monthly percent-change sequence for the same variant: seasonally adjusted real GDP by industry at basic prices, all industries, monthly change. The average of October 2025 through May 2026 advance values [-0.3, 0.0, 0.2, 0.1, 0.2, -0.1, 0.5, 0.1] is +0.0875%, so a near +0.1% prior is appropriate before inside-view adjustments."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 8 source-context item(s), activity log present.","evidence":["Framing and exact resolver: target is Statistics Canada's first-print, seasonally adjusted real GDP by industry, all industries, month-to-month percent change for June 2026. The ledger binds resolution to Table 36-10-0434-01 and The Daily; StatCan also exposes a derived growth-rates view as Table 36-10-0434-02, but I keep the forecast tied to the ledger resolver.","The base rate/reference class is the recent official and official-advance monthly percent-change sequence for the same variant: seasonally adjusted real GDP by industry at basic prices, all industries, monthly change. The average of October 2025 through May 2026 advance values [-0.3, 0.0, 0.2, 0.1, 0.2, -0.1, 0.5, 0.1] is +0.0875%, so a near +0.1% prior is appropriate before inside-view adjustments."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: target is Statistics Canada's first-print, seasonally adjusted real GDP by industry, all industries, month-to-month percent change for June 2026. The ledger binds resolution to Table 36-10-0434-01 and The Daily; StatCan also exposes a derived growth-rates view as Table 36-10-0434-02, but I keep the forecast tied to the ledger resolver.","Tool call: Opened Statistics Canada 2026-2027 major economic releases PDF and read the Gross domestic product by industry schedule."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.6, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is the recent same-series reference class mean +0.0875% from Oct 2025-May 2026 advance, a short recent-month sample rather than a full-cycle volatility estimate; adjustment components are +0.02 for May advance persistence, -0.03 for partial unwind after April's oil/goods rebound, +0.02 for services/finance-real-estate support, and -0.01 for wholesale/agriculture/tariff-sensitive drag, leaving a rounded point of +0.1%. For a change/flow series, sigma is computed from the values themselves: sample sigma = 0.24 percentage point for [-0.3, 0.0, 0.2, 0.1, 0.2, -0.1, 0.5, 0.1]. The 80% half-width is roughly 1.28*sigma = 1.28*0.24 = 0.31 percentage point, rounded to 0.30 percentage point, so +0.1 +/- 0.3 percentage point of month-to-month growth gives [-0.2, +0.4].","Counter-considerations: upside risk would come from another mining/oil, construction, or manufacturing rebound plus steady services and would land above the interval if broad sector gains pushed June to +0.5% or stronger. Downside risk would come from renewed goods-sector weakness, wildfire or energy disruption, or a sharper tariff-sensitive trade slowdown and would land below the interval if June printed -0.3% or weaker. The outside the interval scenarios are plausible but not central given the May advance and recent base rate."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Framing and exact resolver: target is Statistics Canada's first-print, seasonally adjusted real GDP by industry, all industries, month-to-month percent change for June 2026. The ledger binds resolution to Table 36-10-0434-01 and The Daily; StatCan also exposes a derived growth-rates view as Table 36-10-0434-02, but I keep the forecast tied to the ledger resolver.","Counter-considerations: upside risk would come from another mining/oil, construction, or manufacturing rebound plus steady services and would land above the interval if broad sector gains pushed June to +0.5% or stronger. Downside risk would come from renewed goods-sector weakness, wildfire or energy disruption, or a sharper tariff-sensitive trade slowdown and would land below the interval if June printed -0.3% or weaker. The outside the interval scenarios are plausible but not central given the May advance and recent base rate."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Canada June 2026 Monthly GDP By Industry Forecast","Framing and exact resolver: target is Statistics Canada's first-print, seasonally adjusted real GDP by industry, all industries, month-to-month percent change for June 2026. The ledger binds resolution to Table 36-10-0434-01 and The Daily; StatCan also exposes a derived growth-rates view as Table 36-10-0434-02, but I keep the forecast tied to the ledger resolver."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-monthly-gdp-growth-june-2026\nrunLabel: Headline\nresolutionDate: 2026-08-28\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.jolts-openings-july-2026.2026-07-10T05-20-01Z.82a6057c099f283b","runId":"run.jolts-openings-july-2026.2026-07-10T05-20-01Z.82a6057c099f283b","predictionId":"jolts-openings-july-2026","specId":"spec.jolts-openings-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: for the same SA total nonfarm JOLTS level series, the 2024-01 through 2026-05 monthly path moved from 8.378 million to 7.594 million, with large month-to-month noise and no stable acceleration. A persistence/random-walk base rate from the latest official JOLTS print starts at 7.594 million.","Prior/update/interval: persistence prior = latest JTS000000000000000JOL May 2026 preliminary level 7.594 million; historical sample = fetched monthly JOLTS values from Jan 2024 through May 2026; successive-change sigma = 0.33 million from the 28 monthly changes; adjustment components = -0.20 million for weak June payroll growth of 57 thousand, treating sub-100 thousand payroll growth as evidence that vacancy demand is unlikely to sustain the Apr-May jump, -0.08 million for mean reversion after the Apr-May jump from 6.887 million to 7.594 million, -0.02 million for still-elevated unemployment near 4.2 percent; point = 7.594 - 0.20 - 0.08 - 0.02 = 7.294, rounded to 7.29 million. One-step 80 percent half-width is roughly 1.28*sigma = 1.28*0.33 = 0.42 million; a two-step random-walk analogue is about 1.28*0.33*sqrt(2) = 0.60 million, so I use 0.55 million because the forecast is two reference months beyond the latest JOLTS print and the April rebound introduced regime uncertainty. Final implied bounds: 7.29 - 0.55 = 6.74 and 7.29 + 0.55 = 7.84 million."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing: the target is BLS series JTS000000000000000JOL, total nonfarm job openings, seasonally adjusted, level in thousands, converted to millions. The BLS schedule page verifies that the July 2026 JOLTS reference month is scheduled for release on 2026-09-01 at 10:00 AM, so the ledger resolutionDate is consistent with the official calendar.","Tool call: BLS data page for JTS000000000000000JOL, total nonfarm job openings, seasonally adjusted, level in thousands"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast for July 2026 first-print JOLTS job openings","Framing: the target is BLS series JTS000000000000000JOL, total nonfarm job openings, seasonally adjusted, level in thousands, converted to millions. The BLS schedule page verifies that the July 2026 JOLTS reference month is scheduled for release on 2026-09-01 at 10:00 AM, so the ledger resolutionDate is consistent with the official calendar."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.1, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = latest JTS000000000000000JOL May 2026 preliminary level 7.594 million; historical sample = fetched monthly JOLTS values from Jan 2024 through May 2026; successive-change sigma = 0.33 million from the 28 monthly changes; adjustment components = -0.20 million for weak June payroll growth of 57 thousand, treating sub-100 thousand payroll growth as evidence that vacancy demand is unlikely to sustain the Apr-May jump, -0.08 million for mean reversion after the Apr-May jump from 6.887 million to 7.594 million, -0.02 million for still-elevated unemployment near 4.2 percent; point = 7.594 - 0.20 - 0.08 - 0.02 = 7.294, rounded to 7.29 million. One-step 80 percent half-width is roughly 1.28*sigma = 1.28*0.33 = 0.42 million; a two-step random-walk analogue is about 1.28*0.33*sqrt(2) = 0.60 million, so I use 0.55 million because the forecast is two reference months beyond the latest JOLTS print and the April rebound introduced regime uncertainty. Final implied bounds: 7.29 - 0.55 = 6.74 and 7.29 + 0.55 = 7.84 million.","Upside risk: if July labor demand remains close to the Apr-May rebound and employers keep vacancies open despite soft payroll growth, the first print could land above the interval, especially above 7.84 million. Downside risk: if the May level was a temporary rebound and weak payroll hiring reflects broad demand cooling, July openings could fall back toward early-2026 levels and land below the interval. Outside the interval would require either a renewed vacancy surge above roughly 7.84 million or a sharp retracement below roughly 6.74 million."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior = latest JTS000000000000000JOL May 2026 preliminary level 7.594 million; historical sample = fetched monthly JOLTS values from Jan 2024 through May 2026; successive-change sigma = 0.33 million from the 28 monthly changes; adjustment components = -0.20 million for weak June payroll growth of 57 thousand, treating sub-100 thousand payroll growth as evidence that vacancy demand is unlikely to sustain the Apr-May jump, -0.08 million for mean reversion after the Apr-May jump from 6.887 million to 7.594 million, -0.02 million for still-elevated unemployment near 4.2 percent; point = 7.594 - 0.20 - 0.08 - 0.02 = 7.294, rounded to 7.29 million. One-step 80 percent half-width is roughly 1.28*sigma = 1.28*0.33 = 0.42 million; a two-step random-walk analogue is about 1.28*0.33*sqrt(2) = 0.60 million, so I use 0.55 million because the forecast is two reference months beyond the latest JOLTS print and the April rebound introduced regime uncertainty. Final implied bounds: 7.29 - 0.55 = 6.74 and 7.29 + 0.55 = 7.84 million."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence prior = latest JTS000000000000000JOL May 2026 preliminary level 7.594 million; historical sample = fetched monthly JOLTS values from Jan 2024 through May 2026; successive-change sigma = 0.33 million from the 28 monthly changes; adjustment components = -0.20 million for weak June payroll growth of 57 thousand, treating sub-100 thousand payroll growth as evidence that vacancy demand is unlikely to sustain the Apr-May jump, -0.08 million for mean reversion after the Apr-May jump from 6.887 million to 7.594 million, -0.02 million for still-elevated unemployment near 4.2 percent; point = 7.594 - 0.20 - 0.08 - 0.02 = 7.294, rounded to 7.29 million. One-step 80 percent half-width is roughly 1.28*sigma = 1.28*0.33 = 0.42 million; a two-step random-walk analogue is about 1.28*0.33*sqrt(2) = 0.60 million, so I use 0.55 million because the forecast is two reference months beyond the latest JOLTS print and the April rebound introduced regime uncertainty. Final implied bounds: 7.29 - 0.55 = 6.74 and 7.29 + 0.55 = 7.84 million.","Upside risk: if July labor demand remains close to the Apr-May rebound and employers keep vacancies open despite soft payroll growth, the first print could land above the interval, especially above 7.84 million. Downside risk: if the May level was a temporary rebound and weak payroll hiring reflects broad demand cooling, July openings could fall back toward early-2026 levels and land below the interval. Outside the interval would require either a renewed vacancy surge above roughly 7.84 million or a sharp retracement below roughly 6.74 million."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for July 2026 first-print JOLTS job openings","Prior/update/interval: persistence prior = latest JTS000000000000000JOL May 2026 preliminary level 7.594 million; historical sample = fetched monthly JOLTS values from Jan 2024 through May 2026; successive-change sigma = 0.33 million from the 28 monthly changes; adjustment components = -0.20 million for weak June payroll growth of 57 thousand, treating sub-100 thousand payroll growth as evidence that vacancy demand is unlikely to sustain the Apr-May jump, -0.08 million for mean reversion after the Apr-May jump from 6.887 million to 7.594 million, -0.02 million for still-elevated unemployment near 4.2 percent; point = 7.594 - 0.20 - 0.08 - 0.02 = 7.294, rounded to 7.29 million. One-step 80 percent half-width is roughly 1.28*sigma = 1.28*0.33 = 0.42 million; a two-step random-walk analogue is about 1.28*0.33*sqrt(2) = 0.60 million, so I use 0.55 million because the forecast is two reference months beyond the latest JOLTS print and the April rebound introduced regime uncertainty. Final implied bounds: 7.29 - 0.55 = 6.74 and 7.29 + 0.55 = 7.84 million."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: jolts-openings-july-2026\nrunLabel: Headline\nresolutionDate: 2026-09-01\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.jolts-quits-rate-july-2026.2026-07-10T05-21-42Z.dc06de3a4984be08","runId":"run.jolts-quits-rate-july-2026.2026-07-10T05-21-42Z.dc06de3a4984be08","predictionId":"jolts-quits-rate-july-2026","specId":"spec.jolts-quits-rate-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: for a monthly level/rate series this close to release, the strongest outside-view anchor is persistence in the same SA total-rate series. The recent official reference class has total rates 1.9, 2.0, 1.9, and 1.9 from February through May 2026, with May 2025 at 2.1, so the base rate is near 1.9 rather than a return toward the 2021-2022 high-quits regime.","Current-release adjustment: May 2026 was flat at 1.9 despite offsetting industry moves. Leisure and hospitality rose to 4.0 and other services to 2.5, but health care and social assistance eased to 1.7 and construction fell to 1.3. That mix argues for no material level adjustment from the 1.9 persistence prior."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Forecast for July 2026 BLS JOLTS total quits rate","Framing and exact resolver: this is the seasonally adjusted Total quits rate in BLS JOLTS Table 4, not the quits level, not not-seasonally-adjusted data, and not a revised vintage. The series code context is BLS JOLTS total nonfarm quits rate, and the ledger source URL points to Table 4."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: Checked the BLS JOLTS release schedule by release name and the September 2026 BLS calendar for the July 2026 reference month.","Reference class and base rate: for a monthly level/rate series this close to release, the strongest outside-view anchor is persistence in the same SA total-rate series. The recent official reference class has total rates 1.9, 2.0, 1.9, and 1.9 from February through May 2026, with May 2025 at 2.1, so the base rate is near 1.9 rather than a return toward the 2021-2022 high-quits regime."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.3, distribution present, forecast step count 1.","evidence":["Tool result: Fetched industry rates for May 2026: total private 2.1, construction 1.3, manufacturing 1.4, retail trade 2.8, professional and business services 2.0, health care and social assistance 1.7, leisure and hospitality 4.0, government 0.8.","Prior/update/interval: persistence prior = latest official SA total quits rate of 1.9 using the February-May 2026 BLS Table 4 reference class. Successive monthly changes are +0.1, -0.1, and 0.0 percentage point, so sigma = 0.08 percentage point on those changes. Because this is only a three-change recent sample, I treat it as a judgmental short-run uncertainty proxy rather than a full long-run volatility estimate. The one-month 80% half-width is about 1.28*sigma = 1.28*0.08 = 0.10; for a two-reference-month horizon from May to July, scale by sqrt(2), giving 0.14, rounded to a 0.15 percentage point half-width. Point = 1.9 + 0.0 level/momentum adjustment = 1.9; 80% interval = 1.9 +/- 0.15 = [1.75, 2.05]."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Fetched BLS Table 4 industry rows to check whether total quits pressure was broad or sector-specific.","Prior/update/interval: persistence prior = latest official SA total quits rate of 1.9 using the February-May 2026 BLS Table 4 reference class. Successive monthly changes are +0.1, -0.1, and 0.0 percentage point, so sigma = 0.08 percentage point on those changes. Because this is only a three-change recent sample, I treat it as a judgmental short-run uncertainty proxy rather than a full long-run volatility estimate. The one-month 80% half-width is about 1.28*sigma = 1.28*0.08 = 0.10; for a two-reference-month horizon from May to July, scale by sqrt(2), giving 0.14, rounded to a 0.15 percentage point half-width. Point = 1.9 + 0.0 level/momentum adjustment = 1.9; 80% interval = 1.9 +/- 0.15 = [1.75, 2.05]."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Current-release adjustment: May 2026 was flat at 1.9 despite offsetting industry moves. Leisure and hospitality rose to 4.0 and other services to 2.5, but health care and social assistance eased to 1.7 and construction fell to 1.3. That mix argues for no material level adjustment from the 1.9 persistence prior.","Prior/update/interval: persistence prior = latest official SA total quits rate of 1.9 using the February-May 2026 BLS Table 4 reference class. Successive monthly changes are +0.1, -0.1, and 0.0 percentage point, so sigma = 0.08 percentage point on those changes. Because this is only a three-change recent sample, I treat it as a judgmental short-run uncertainty proxy rather than a full long-run volatility estimate. The one-month 80% half-width is about 1.28*sigma = 1.28*0.08 = 0.10; for a two-reference-month horizon from May to July, scale by sqrt(2), giving 0.14, rounded to a 0.15 percentage point half-width. Point = 1.9 + 0.0 level/momentum adjustment = 1.9; 80% interval = 1.9 +/- 0.15 = [1.75, 2.05]."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for July 2026 BLS JOLTS total quits rate","Framing and exact resolver: this is the seasonally adjusted Total quits rate in BLS JOLTS Table 4, not the quits level, not not-seasonally-adjusted data, and not a revised vintage. The series code context is BLS JOLTS total nonfarm quits rate, and the ledger source URL points to Table 4."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: jolts-quits-rate-july-2026\nrunLabel: Headline\nresolutionDate: 2026-09-01\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.euro-area-unemployment-rate-july-2026.2026-07-10T05-31-26Z.df2003dd44fa5014","runId":"run.euro-area-unemployment-rate-july-2026.2026-07-10T05-31-26Z.df2003dd44fa5014","predictionId":"euro-area-unemployment-rate-july-2026","specId":"spec.euro-area-unemployment-rate-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate / reference class: for this low-volatility monthly rate series, the outside-view prior is persistence at the latest official one-decimal print. The recent reference class is the same Eurostat euro area SA total age 15-74 rate, where the last five displayed values were tightly clustered between 6.2 and 6.4 percent.","Level, momentum, and mechanism: the level is historically low at 6.2%; momentum from February to May is mildly downward, but the last month is flat at 6.2. The May count decline of 55 thousand supports no near-term jump, while two months of macro noise before the July reference month argues against narrowing the interval too much."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this forecast targets Eurostat table une_rt_m, euro area unemployment rate, seasonally adjusted, total sex, age 15-74, percent, for July 2026. The resolution source is the Eurostat euro-indicators unemployment release and the same une_rt_m data page; the resolution is the first official print, not a revised vintage.","Tool result: Fetched latest same-series official values: May 2026 euro area seasonally adjusted unemployment rate 6.2%, April 2026 6.2%, May 2025 6.3%, EU May 2026 5.9%, and euro area unemployed persons 10.986 million."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Euro area unemployment rate, July 2026 first print","Framing and exact resolver: this forecast targets Eurostat table une_rt_m, euro area unemployment rate, seasonally adjusted, total sex, age 15-74, percent, for July 2026. The resolution source is the Eurostat euro-indicators unemployment release and the same une_rt_m data page; the resolution is the first official print, not a revised vintage."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.4, distribution present, forecast step count 1.","evidence":["Level, momentum, and mechanism: the level is historically low at 6.2%; momentum from February to May is mildly downward, but the last month is flat at 6.2. The May count decline of 55 thousand supports no near-term jump, while two months of macro noise before the July reference month argues against narrowing the interval too much.","Prior/update/interval: persistence prior 6.2 from May 2026; contiguous monthly historical sample Feb-May 2026 values 6.4, 6.3, 6.2, 6.2; adjustment components are 0.0 for latest flat momentum, -0.05 for Feb-May downtrend, and +0.05 for two-step mean reversion/rounding risk, leaving point 6.2. Contiguous one-month changes are -0.1, -0.1, 0.0; RMS monthly sigma is sqrt((0.01+0.01+0.00)/3)=0.08. For two unreleased monthly steps, sigma = 0.08*sqrt(2)=0.12, so the 80% half-width is roughly 1.28*sigma = 1.28*0.12 = 0.15; I widen to 0.2 for the limited short sample and one-decimal rounding risk, giving final implied bounds of 6.0 to 6.4."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, and mechanism: the level is historically low at 6.2%; momentum from February to May is mildly downward, but the last month is flat at 6.2. The May count decline of 55 thousand supports no near-term jump, while two months of macro noise before the July reference month argues against narrowing the interval too much.","Prior/update/interval: persistence prior 6.2 from May 2026; contiguous monthly historical sample Feb-May 2026 values 6.4, 6.3, 6.2, 6.2; adjustment components are 0.0 for latest flat momentum, -0.05 for Feb-May downtrend, and +0.05 for two-step mean reversion/rounding risk, leaving point 6.2. Contiguous one-month changes are -0.1, -0.1, 0.0; RMS monthly sigma is sqrt((0.01+0.01+0.00)/3)=0.08. For two unreleased monthly steps, sigma = 0.08*sqrt(2)=0.12, so the 80% half-width is roughly 1.28*sigma = 1.28*0.12 = 0.15; I widen to 0.2 for the limited short sample and one-decimal rounding risk, giving final implied bounds of 6.0 to 6.4."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, and mechanism: the level is historically low at 6.2%; momentum from February to May is mildly downward, but the last month is flat at 6.2. The May count decline of 55 thousand supports no near-term jump, while two months of macro noise before the July reference month argues against narrowing the interval too much.","Prior/update/interval: persistence prior 6.2 from May 2026; contiguous monthly historical sample Feb-May 2026 values 6.4, 6.3, 6.2, 6.2; adjustment components are 0.0 for latest flat momentum, -0.05 for Feb-May downtrend, and +0.05 for two-step mean reversion/rounding risk, leaving point 6.2. Contiguous one-month changes are -0.1, -0.1, 0.0; RMS monthly sigma is sqrt((0.01+0.01+0.00)/3)=0.08. For two unreleased monthly steps, sigma = 0.08*sqrt(2)=0.12, so the 80% half-width is roughly 1.28*sigma = 1.28*0.12 = 0.15; I widen to 0.2 for the limited short sample and one-decimal rounding risk, giving final implied bounds of 6.0 to 6.4."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Framing and exact resolver: this forecast targets Eurostat table une_rt_m, euro area unemployment rate, seasonally adjusted, total sex, age 15-74, percent, for July 2026. The resolution source is the Eurostat euro-indicators unemployment release and the same une_rt_m data page; the resolution is the first official print, not a revised vintage.","Level, momentum, and mechanism: the level is historically low at 6.2%; momentum from February to May is mildly downward, but the last month is flat at 6.2. The May count decline of 55 thousand supports no near-term jump, while two months of macro noise before the July reference month argues against narrowing the interval too much."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: euro-area-unemployment-rate-july-2026\nrunLabel: Headline\nresolutionDate: 2026-09-01\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.belgium-unemployment-rate-july-2026.2026-07-10T05-39-07Z.30ae77b0851697f0","runId":"run.belgium-unemployment-rate-july-2026.2026-07-10T05-39-07Z.30ae77b0851697f0","predictionId":"belgium-unemployment-rate-july-2026","specId":"spec.belgium-unemployment-rate-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base rate / reference class: the same-series outside view is strong persistence around 6.0 to 6.2 percent after a drift down from 6.5 percent in mid-2025. With only June and July still to print before the target, the base rate says July should usually remain within a few tenths of the latest 6.0 percent.","Prior/update/interval: persistence prior from the 12-month Eurostat same-variant sample is latest value 6.0. Successive monthly changes are -0.1,-0.1,-0.1,0.0,-0.1,0.0,0.0,-0.1,+0.1,0.0,-0.1, so sigma = 0.07 percentage point. For a two-month-ahead July value, 1.28*sigma*sqrt(2)=1.28*0.07*1.41=0.13. I widen to 0.20, about 1.54x the mechanical two-step half-width, because first-print monthly labour-force estimates are rounded to one decimal and can absorb small survey noise. With no separate public evidence strong enough to move the latest-value prior, the point remains 6.0; the 80% interval is centered on 6.0 after widening, giving 5.8 to 6.2."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this forecast targets Eurostat table une_rt_m, Belgium geo=BE, seasonally adjusted s_adj=SA, total sex=T, age Y15-74, unit PC_ACT, for 2026-07. I use the same variant for anchors and history and resolve on the first official Eurostat print, rounded to one decimal percent.","Tool result: Official calendar context used for this run: the unemployment release is scheduled for 2026-09-01 in Europe/Luxembourg time, inside the registered 2026-08-26 to 2026-09-03 window; this fixes resolutionDate=2026-09-01."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Belgium July 2026 unemployment first print","Framing and exact resolver: this forecast targets Eurostat table une_rt_m, Belgium geo=BE, seasonally adjusted s_adj=SA, total sex=T, age Y15-74, unit PC_ACT, for 2026-07. I use the same variant for anchors and history and resolve on the first official Eurostat print, rounded to one decimal percent."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.4, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior from the 12-month Eurostat same-variant sample is latest value 6.0. Successive monthly changes are -0.1,-0.1,-0.1,0.0,-0.1,0.0,0.0,-0.1,+0.1,0.0,-0.1, so sigma = 0.07 percentage point. For a two-month-ahead July value, 1.28*sigma*sqrt(2)=1.28*0.07*1.41=0.13. I widen to 0.20, about 1.54x the mechanical two-step half-width, because first-print monthly labour-force estimates are rounded to one decimal and can absorb small survey noise. With no separate public evidence strong enough to move the latest-value prior, the point remains 6.0; the 80% interval is centered on 6.0 after widening, giving 5.8 to 6.2.","Counter-considerations: upside risk is a sharp deterioration in hiring or labour-force re-entry that would push the first print to 6.3 or above, outside the interval. Downside risk is a stronger summer employment gain or favourable survey rotation that would land below the interval at 5.7 or less."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior from the 12-month Eurostat same-variant sample is latest value 6.0. Successive monthly changes are -0.1,-0.1,-0.1,0.0,-0.1,0.0,0.0,-0.1,+0.1,0.0,-0.1, so sigma = 0.07 percentage point. For a two-month-ahead July value, 1.28*sigma*sqrt(2)=1.28*0.07*1.41=0.13. I widen to 0.20, about 1.54x the mechanical two-step half-width, because first-print monthly labour-force estimates are rounded to one decimal and can absorb small survey noise. With no separate public evidence strong enough to move the latest-value prior, the point remains 6.0; the 80% interval is centered on 6.0 after widening, giving 5.8 to 6.2.","Level, momentum, one-off, and policy effects: level is near 6.0; momentum is mildly downward over the prior year but flat in spring 2026; I see no one-off July mechanism large enough to move the rate by more than a few tenths; policy effects are slow-moving and do not justify departing from the persistence prior."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, one-off, and policy effects: level is near 6.0; momentum is mildly downward over the prior year but flat in spring 2026; I see no one-off July mechanism large enough to move the rate by more than a few tenths; policy effects are slow-moving and do not justify departing from the persistence prior.","Counter-considerations: upside risk is a sharp deterioration in hiring or labour-force re-entry that would push the first print to 6.3 or above, outside the interval. Downside risk is a stronger summer employment gain or favourable survey rotation that would land below the interval at 5.7 or less."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Framing and exact resolver: this forecast targets Eurostat table une_rt_m, Belgium geo=BE, seasonally adjusted s_adj=SA, total sex=T, age Y15-74, unit PC_ACT, for 2026-07. I use the same variant for anchors and history and resolve on the first official Eurostat print, rounded to one decimal percent.","Prior/update/interval: persistence prior from the 12-month Eurostat same-variant sample is latest value 6.0. Successive monthly changes are -0.1,-0.1,-0.1,0.0,-0.1,0.0,0.0,-0.1,+0.1,0.0,-0.1, so sigma = 0.07 percentage point. For a two-month-ahead July value, 1.28*sigma*sqrt(2)=1.28*0.07*1.41=0.13. I widen to 0.20, about 1.54x the mechanical two-step half-width, because first-print monthly labour-force estimates are rounded to one decimal and can absorb small survey noise. With no separate public evidence strong enough to move the latest-value prior, the point remains 6.0; the 80% interval is centered on 6.0 after widening, giving 5.8 to 6.2."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: belgium-unemployment-rate-july-2026\nrunLabel: Headline\nresolutionDate: 2026-09-01\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-participation-may-2026.2026-07-10T05-11-13Z.756724ad68edc1c7","runId":"run.snap-participation-may-2026.2026-07-10T05-11-13Z.756724ad68edc1c7","predictionId":"snap-participation-may-2026","specId":"spec.snap-participation-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the recent official-source base rate is a high-level, slow-moving national caseload around 41.7 to 42.3 million persons, with May-to-May moves of -0.353 million from 2023 to 2024 and +0.460 million from 2024 to 2025 rather than a clear trend.","Prior/update/interval: persistence prior = latest official November 2025 Persons, 42.311 million; historical sample = recent FNS May-to-May movements from the same national monthly Persons series, May 2023 to May 2024 = -0.353 million and May 2024 to May 2025 = +0.460 million; adjustment components = -0.04 million seasonal Nov-to-May base drift and -0.35 million for 2026 eligibility/administrative tightening, so point = 42.311 - 0.04 - 0.35 = 41.921 million, rounded to 41.92. Interval method = realized dispersion of comparable annual May movements; sigma = 0.41 million by RMS of the two May-to-May moves, so 1.28*sigma = 0.52 million. I widen to 0.72 million, 1.38x the mechanical half-width, for policy timing uncertainty, giving 41.92 - 0.72 = 41.20 and 41.92 + 0.72 = 42.64."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Forecast for USDA FNS SNAP Persons, May 2026","Framing and exact resolver: this target is the USDA Food and Nutrition Service national SNAP monthly participation table, Persons, not seasonally adjusted. The FNS file reports persons in thousands, and this cell reports millions using the ledger transform factor 0.001."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: Checked USDA FNS release calendar for the first-print timing of the May 2026 SNAP monthly participation table.","Tool result: The official release schedule places the May 2026 SNAP monthly data release on 2026-09-30, inside the registered expected window 2026-09-26 to 2026-10-04; the page also listed monthly SNAP releases with a 2026 schedule year."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.44, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = latest official November 2025 Persons, 42.311 million; historical sample = recent FNS May-to-May movements from the same national monthly Persons series, May 2023 to May 2024 = -0.353 million and May 2024 to May 2025 = +0.460 million; adjustment components = -0.04 million seasonal Nov-to-May base drift and -0.35 million for 2026 eligibility/administrative tightening, so point = 42.311 - 0.04 - 0.35 = 41.921 million, rounded to 41.92. Interval method = realized dispersion of comparable annual May movements; sigma = 0.41 million by RMS of the two May-to-May moves, so 1.28*sigma = 0.52 million. I widen to 0.72 million, 1.38x the mechanical half-width, for policy timing uncertainty, giving 41.92 - 0.72 = 41.20 and 41.92 + 0.72 = 42.64.","Counter-considerations: downside risk for SNAP participation is that eligibility changes bite faster than assumed or states accelerate removals, which would land below the interval near or under 41.20 million. Upside risk for SNAP participation is that policy effects are delayed, litigation or implementation frictions slow terminations, or the labor market weakens; that would land above the interval near or above 42.64 million. Outside the interval would require either a broad administrative drop exceeding roughly 1.1 million from November or renewed caseload growth despite expected policy tightening."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: Public legislation context indicates SNAP work-rule eligibility changes involving adults through age 64 and a 2026 implementation horizon; because the source does not directly translate those provisions into a May 2026 persons count, I use only a modest judgmental participation adjustment, not the draft's larger -0.650 million adjustment.","Level, momentum, and mechanism: level starts from the latest FNS November 2025 value of 42.311 million. Momentum is near flat, because September to November 2025 rose only 0.072 million. The inside-view update is a modest negative policy/administrative effect in early 2026, partially offset by normal churn and any weaker labor-market conditions."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, and mechanism: level starts from the latest FNS November 2025 value of 42.311 million. Momentum is near flat, because September to November 2025 rose only 0.072 million. The inside-view update is a modest negative policy/administrative effect in early 2026, partially offset by normal churn and any weaker labor-market conditions.","Prior/update/interval: persistence prior = latest official November 2025 Persons, 42.311 million; historical sample = recent FNS May-to-May movements from the same national monthly Persons series, May 2023 to May 2024 = -0.353 million and May 2024 to May 2025 = +0.460 million; adjustment components = -0.04 million seasonal Nov-to-May base drift and -0.35 million for 2026 eligibility/administrative tightening, so point = 42.311 - 0.04 - 0.35 = 41.921 million, rounded to 41.92. Interval method = realized dispersion of comparable annual May movements; sigma = 0.41 million by RMS of the two May-to-May moves, so 1.28*sigma = 0.52 million. I widen to 0.72 million, 1.38x the mechanical half-width, for policy timing uncertainty, giving 41.92 - 0.72 = 41.20 and 41.92 + 0.72 = 42.64."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for USDA FNS SNAP Persons, May 2026","Tool call: Pulled same-series FNS national Persons history for recent May reference points and near-current months."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-participation-may-2026\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.belgium-gdp-flash-q3-2026.2026-07-10T05-41-35Z.b3a9e8ee3dcac863","runId":"run.belgium-gdp-flash-q3-2026.2026-07-10T05-41-35Z.b3a9e8ee3dcac863","predictionId":"belgium-gdp-flash-q3-2026","specId":"spec.belgium-gdp-flash-q3-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 9 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the recent same-variant reference class is a low-volatility Belgium qoq-growth process centered around 0.25 percent, with the dated sample 2023-Q4 0.4, 2024-Q1 0.3, 2024-Q2 0.2, 2024-Q3 0.3, 2024-Q4 0.2, 2025-Q1 0.3, 2025-Q2 0.1, and 2026-Q1 0.2; these are value-volatility anchors for the target series rather than forecast-error residuals.","Prior/update/interval: persistence prior is the eight-observation recent flash/preliminary sample [0.4, 0.3, 0.2, 0.3, 0.2, 0.3, 0.1, 0.2], mean = 0.25. For a change/flow series, sigma is computed from the values themselves: sample sigma = 0.093. The Gaussian 80% half-width is 1.28*sigma = 1.28*0.093 = 0.119. I shade the point from 0.25 to 0.20 for softer 2026 euro-area momentum and trade/energy uncertainty; I widen the displayed half-width to about 0.20, which is 1.68 times the mechanical half-width, because Belgium's open economy has a larger tail if external demand or energy prices deteriorate. Rounded to agency precision, this gives 0.0 to 0.4."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Tool result: NBB calendar/ledger target places the first-print release on 2026-10-30 within the expected 2026-10-23 to 2026-11-06 window; resolver uses 1 first-print flash estimate and one-decimal percent growth.","Current-release adjustment: level effects are neutral to mildly positive because annual Belgium growth around 1.2 implies about 0.3 per quarter, momentum is slightly negative from soft euro-area growth and recent Belgian prints near 0.1-0.2, one-off effects are downside from trade and energy volatility, and policy-mechanism effects are mixed as easier earlier ECB policy supports demand but fiscal consolidation and external shocks restrain it."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: target is the National Bank of Belgium first flash estimate for Belgium real GDP, seasonally and calendar adjusted chain-linked volume, quarter-on-quarter percent growth for 2026-Q3. The resolver should stay tied to nbb.gdp.flash_qoq.2026_q3.first_print even though the allowed country enum in the generic JSON template does not list BE.","Tool call: Checked NBB national/regional accounts release calendar and target binding for the Q3 2026 flash estimate."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.4, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is the eight-observation recent flash/preliminary sample [0.4, 0.3, 0.2, 0.3, 0.2, 0.3, 0.1, 0.2], mean = 0.25. For a change/flow series, sigma is computed from the values themselves: sample sigma = 0.093. The Gaussian 80% half-width is 1.28*sigma = 1.28*0.093 = 0.119. I shade the point from 0.25 to 0.20 for softer 2026 euro-area momentum and trade/energy uncertainty; I widen the displayed half-width to about 0.20, which is 1.68 times the mechanical half-width, because Belgium's open economy has a larger tail if external demand or energy prices deteriorate. Rounded to agency precision, this gives 0.0 to 0.4.","Counter-consideration: upside risk is a services-led rebound or inventory/export catch-up that would land above the interval near 0.5 or higher; downside risk is a trade/energy shock or industrial contraction that would land below the interval below 0.0; outside the interval requires either a clear external-demand snapback or an outright quarterly contraction signal."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior is the eight-observation recent flash/preliminary sample [0.4, 0.3, 0.2, 0.3, 0.2, 0.3, 0.1, 0.2], mean = 0.25. For a change/flow series, sigma is computed from the values themselves: sample sigma = 0.093. The Gaussian 80% half-width is 1.28*sigma = 1.28*0.093 = 0.119. I shade the point from 0.25 to 0.20 for softer 2026 euro-area momentum and trade/energy uncertainty; I widen the displayed half-width to about 0.20, which is 1.68 times the mechanical half-width, because Belgium's open economy has a larger tail if external demand or energy prices deteriorate. Rounded to agency precision, this gives 0.0 to 0.4.","Current-release adjustment: level effects are neutral to mildly positive because annual Belgium growth around 1.2 implies about 0.3 per quarter, momentum is slightly negative from soft euro-area growth and recent Belgian prints near 0.1-0.2, one-off effects are downside from trade and energy volatility, and policy-mechanism effects are mixed as easier earlier ECB policy supports demand but fiscal consolidation and external shocks restrain it."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence prior is the eight-observation recent flash/preliminary sample [0.4, 0.3, 0.2, 0.3, 0.2, 0.3, 0.1, 0.2], mean = 0.25. For a change/flow series, sigma is computed from the values themselves: sample sigma = 0.093. The Gaussian 80% half-width is 1.28*sigma = 1.28*0.093 = 0.119. I shade the point from 0.25 to 0.20 for softer 2026 euro-area momentum and trade/energy uncertainty; I widen the displayed half-width to about 0.20, which is 1.68 times the mechanical half-width, because Belgium's open economy has a larger tail if external demand or energy prices deteriorate. Rounded to agency precision, this gives 0.0 to 0.4.","Current-release adjustment: level effects are neutral to mildly positive because annual Belgium growth around 1.2 implies about 0.3 per quarter, momentum is slightly negative from soft euro-area growth and recent Belgian prints near 0.1-0.2, one-off effects are downside from trade and energy volatility, and policy-mechanism effects are mixed as easier earlier ECB policy supports demand but fiscal consolidation and external shocks restrain it."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Belgium 2026-Q3 GDP Flash Forecast","Tool call: Fetched recent Belgium flash/preliminary GDP quarter-on-quarter reference points from NBB/Eurostat public national-accounts releases and databrowser history."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: belgium-gdp-flash-q3-2026\nrunLabel: Headline\nresolutionDate: 2026-10-30\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-nonfarm-productivity-q3-2026-prelim.2026-07-10T05-44-04Z.3a13ed3cf5e7098c","runId":"run.us-nonfarm-productivity-q3-2026-prelim.2026-07-10T05-44-04Z.3a13ed3cf5e7098c","predictionId":"us-nonfarm-productivity-q3-2026-prelim","specId":"spec.us-nonfarm-productivity-q3-2026-prelim","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the post-2020 nonfarm business productivity values average about 1.5 percent annualized, while the 2023-2025 subset is stronger at about 2.8 percent. I put more weight on the broader post-2020 base rate because quarterly productivity first prints are noisy and 2025 likely included tariff and inventory timing effects. The history is revised BLS/FRED public history used as a proxy for first-print volatility because a clean first-print vintage sample was not used.","Prior/update/interval: persistence/reference-class prior is the 2021Q1-2026Q1 PRS85006092 mean, 31.7/21 = 1.51, with no separate AR or econometric time-series model beyond this reference-class prior. I add +0.1 for mean reversion after the weak 2026 Q1 print and +0.1 for moderate trend productivity/capital deepening, giving point = 1.7. For this change-rate series I compute sigma from the fetched values themselves: squared deviations from 1.51 sum to about 146.4, variance = 146.4/21 = 6.97, sigma = 2.64. The 80 percent normal half-width is roughly 1.28*sigma = 1.28*2.64 = 3.38, so 1.7 +/- 3.4 gives -1.7 to 5.1 after one-decimal rounding."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: target is BLS Productivity and Costs Table 2, nonfarm business sector Labor productivity, seasonally adjusted percent change from previous quarter at an annual rate, for 2026 Q3 preliminary. The FRED/BLS series code used for history is PRS85006092; resolution remains the BLS first-print Table 2, not FRED.","Tool call: Checked BLS Productivity and Costs release schedule for the Third Quarter 2026 preliminary release."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["US nonfarm business labor productivity, 2026 Q3 preliminary first print","Framing and exact resolver: target is BLS Productivity and Costs Table 2, nonfarm business sector Labor productivity, seasonally adjusted percent change from previous quarter at an annual rate, for 2026 Q3 preliminary. The FRED/BLS series code used for history is PRS85006092; resolution remains the BLS first-print Table 2, not FRED."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6.8, distribution present, forecast step count 1.","evidence":["Tool call: Read recent BLS/FRED history for the post-2020 reference class used to size uncertainty.","Prior/update/interval: persistence/reference-class prior is the 2021Q1-2026Q1 PRS85006092 mean, 31.7/21 = 1.51, with no separate AR or econometric time-series model beyond this reference-class prior. I add +0.1 for mean reversion after the weak 2026 Q1 print and +0.1 for moderate trend productivity/capital deepening, giving point = 1.7. For this change-rate series I compute sigma from the fetched values themselves: squared deviations from 1.51 sum to about 146.4, variance = 146.4/21 = 6.97, sigma = 2.64. The 80 percent normal half-width is roughly 1.28*sigma = 1.28*2.64 = 3.38, so 1.7 +/- 3.4 gives -1.7 to 5.1 after one-decimal rounding."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate/reference class: the post-2020 nonfarm business productivity values average about 1.5 percent annualized, while the 2023-2025 subset is stronger at about 2.8 percent. I put more weight on the broader post-2020 base rate because quarterly productivity first prints are noisy and 2025 likely included tariff and inventory timing effects. The history is revised BLS/FRED public history used as a proxy for first-print volatility because a clean first-print vintage sample was not used."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool call: Read recent BLS/FRED history for the post-2020 reference class used to size uncertainty.","Counter-considerations: upside risk is a Q3 output rebound with flat or falling hours, which would land above the interval if productivity prints above 5.1. Downside risk is weak real output with continued hours growth, which would land below the interval if productivity prints below -1.7. A large inventory/tariff timing swing or a recession-style hours adjustment is the main outside the interval scenario."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: persistence/reference-class prior is the 2021Q1-2026Q1 PRS85006092 mean, 31.7/21 = 1.51, with no separate AR or econometric time-series model beyond this reference-class prior. I add +0.1 for mean reversion after the weak 2026 Q1 print and +0.1 for moderate trend productivity/capital deepening, giving point = 1.7. For this change-rate series I compute sigma from the fetched values themselves: squared deviations from 1.51 sum to about 146.4, variance = 146.4/21 = 6.97, sigma = 2.64. The 80 percent normal half-width is roughly 1.28*sigma = 1.28*2.64 = 3.38, so 1.7 +/- 3.4 gives -1.7 to 5.1 after one-decimal rounding.","Counter-considerations: upside risk is a Q3 output rebound with flat or falling hours, which would land above the interval if productivity prints above 5.1. Downside risk is weak real output with continued hours growth, which would land below the interval if productivity prints below -1.7. A large inventory/tariff timing swing or a recession-style hours adjustment is the main outside the interval scenario."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-nonfarm-productivity-q3-2026-prelim\nrunLabel: Headline\nresolutionDate: 2026-11-05\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.initial-claims-week-2026-07-11.2026-07-10T03-41-05Z.fbe3c2c3da579fd1","runId":"run.initial-claims-week-2026-07-11.2026-07-10T03-41-05Z.fbe3c2c3da579fd1","predictionId":"initial-claims-week-2026-07-11","specId":"spec.initial-claims-week-2026-07-11","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Tool result: For week ending July 4, 2026, advance seasonally adjusted initial claims were 215,000, down 2,000 from the revised prior week of 217,000; the 4-week moving average was 218,750, down 3,750.","Base rate/reference class: over the DOL table's 54 latest reported week-to-week SA initial-claims changes from June 28, 2025 through July 4, 2026, the average move was about -0.4 thousand and the series usually moved by roughly 10 thousand week to week; this supports a persistence-centered forecast rather than a large directional adjustment."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this targets the DOL advance seasonally adjusted Initial Claims figure for the week ending July 11, 2026, reported in persons in the Unemployment Insurance Weekly Claims release and expressed here in thousands. The variant is SA initial claims, matching source series ICSA; anchors below use the same SA variant except where explicitly flagged as NSA context.","Tool call: Read the DOL release unadjusted-data and state-detail sections for one-off context."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this targets the DOL advance seasonally adjusted Initial Claims figure for the week ending July 11, 2026, reported in persons in the Unemployment Insurance Weekly Claims release and expressed here in thousands. The variant is SA initial claims, matching source series ICSA; anchors below use the same SA variant except where explicitly flagged as NSA context.","Tool call: Opened the current U.S. Department of Labor UI Weekly Claims news release PDF and read the headline SA release table."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 26, distribution present, forecast step count 1.","evidence":["Tool call: Read the DOL release unadjusted-data and state-detail sections for one-off context.","Prior/update/interval: persistence prior = latest SA level 215.0 thousand; historical sample = 54 successive DOL weekly SA changes from June 28, 2025 through July 4, 2026; adjustment components = +1.5 thousand level pull toward the 218.75 thousand four-week average, -0.5 thousand recent downward momentum, +0.0 one-off/NSA surprise adjustment, +0.0 policy-mechanism adjustment, giving point = 216.0 thousand. Interval method uses realized successive-change dispersion for an 80% interval: mean change = -0.4, sigma = 10.3, half-width = 1.28*sigma = 1.28*10.3 = 13.2 thousand, so 216.0 +/- 13.2 gives 202.8 to 229.2, rounded to 203 to 229 thousand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior = latest SA level 215.0 thousand; historical sample = 54 successive DOL weekly SA changes from June 28, 2025 through July 4, 2026; adjustment components = +1.5 thousand level pull toward the 218.75 thousand four-week average, -0.5 thousand recent downward momentum, +0.0 one-off/NSA surprise adjustment, +0.0 policy-mechanism adjustment, giving point = 216.0 thousand. Interval method uses realized successive-change dispersion for an 80% interval: mean change = -0.4, sigma = 10.3, half-width = 1.28*sigma = 1.28*10.3 = 13.2 thousand, so 216.0 +/- 13.2 gives 202.8 to 229.2, rounded to 203 to 229 thousand."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-considerations: upside risk is another July seasonal-adjustment miss or renewed education/auto layoffs that would land above the interval, especially if the SA print returns to the late-May/early-June 225k-230k range. Downside risk is faster normalization after the June bulge or unusually low filings around the holiday week, which would land below the interval near or under 203k. Outside the interval would require a weekly move larger than about one recent sigma from the latest level."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["US initial claims SA forecast for week ending July 11, 2026","Base rate/reference class: over the DOL table's 54 latest reported week-to-week SA initial-claims changes from June 28, 2025 through July 4, 2026, the average move was about -0.4 thousand and the series usually moved by roughly 10 thousand week to week; this supports a persistence-centered forecast rather than a large directional adjustment."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: initial-claims-week-2026-07-11\nrunLabel: Headline\nresolutionDate: 2026-07-16\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.initial-claims-week-2026-07-11.2026-07-10T03-41-05Z.time-series-prior.a5dca327ff891db1","runId":"run.initial-claims-week-2026-07-11.2026-07-10T03-41-05Z.time-series-prior.a5dca327ff891db1","predictionId":"initial-claims-week-2026-07-11","specId":"spec.initial-claims-week-2026-07-11","runLabel":"Ledger persistence baseline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.16,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Time-series prior","Tool call: brier.timeseries.prior({ target: \"us.dol.initial_claims.sa.week_2026-07-11\", model: \"persistence.last_print\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Tool result: latest=215 (2026-07-04); history_points=3; interval_method=ledger_realized_step_change_p80; ledger_refs=us.dol.initial_claims.sa.week_2026-06-13,us.dol.initial_claims.sa.week_2026-06-20,us.dol.initial_claims.sa.week_2026-07-04"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 17.6, distribution present, forecast step count 1.","evidence":["Tool result: latest=215 (2026-07-04); history_points=3; interval_method=ledger_realized_step_change_p80; ledger_refs=us.dol.initial_claims.sa.week_2026-06-13,us.dol.initial_claims.sa.week_2026-06-20,us.dol.initial_claims.sa.week_2026-07-04","Prior point = latest observed value = 215; 80% interval = [206, 224]."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: latest=215 (2026-07-04); history_points=3; interval_method=ledger_realized_step_change_p80; ledger_refs=us.dol.initial_claims.sa.week_2026-06-13,us.dol.initial_claims.sa.week_2026-06-20,us.dol.initial_claims.sa.week_2026-07-04","Prior point = latest observed value = 215; 80% interval = [206, 224]."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: initial-claims-week-2026-07-11\nrunLabel: Ledger persistence baseline\nresolutionDate: 2026-07-16\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.continued-claims-week-2026-07-11.2026-07-10T03-44-05Z.e060719c4b0f3387","runId":"run.continued-claims-week-2026-07-11.2026-07-10T03-44-05Z.e060719c4b0f3387","predictionId":"continued-claims-week-2026-07-11","specId":"spec.continued-claims-week-2026-07-11","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Tool result: For the release on 2026-07-09, initial claims for week ending 2026-07-04 were 215000, down 2000 from 217000, and continued claims for week ending 2026-06-27 were about 1810000, up 8000 from a revised prior level near 1802000.","Reference class and base rate: for a stable level series like SA continued claims, the best short-horizon base rate is persistence plus recent weekly drift. The last six rounded weekly observations sit in a tight 1.770 to 1.815 million range, with no latest initial-claims breakout suggesting a sharp move by the 2026-07-11 continued-claims week."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 8 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this is the DOL ETA seasonally adjusted continued claims series, FRED/ALFRED code CCSA, for the week ending 2026-07-11. The target is the first print in millions, not a later revised vintage; all anchors below refer to the same seasonally adjusted continued-claims variant.","Resolver note: the July 23, 2026 DOL ETA release URL is the intended official first-print resolver location for the scheduled release, not evidence that the unreleased value is already available. ALFRED/FRED is used only as a public vintage/history mirror; the official DOL release controls resolution."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this is the DOL ETA seasonally adjusted continued claims series, FRED/ALFRED code CCSA, for the week ending 2026-07-11. The target is the first print in millions, not a later revised vintage; all anchors below refer to the same seasonally adjusted continued-claims variant.","Resolver note: the July 23, 2026 DOL ETA release URL is the intended official first-print resolver location for the scheduled release, not evidence that the unreleased value is already available. ALFRED/FRED is used only as a public vintage/history mirror; the official DOL release controls resolution."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.08, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior uses the latest first/revised level around 1.810 million for 2026-06-27; historical sample uses recent weekly CCSA levels 1.770, 1.800, 1.810, 1.815, 1.802, 1.810. Adjustment components are +0.003 million for slower June payrolls and longer duration, +0.002 million for the latest +8000 weekly move, and 0.000 million for stable initial claims, giving point 1.810 + 0.005 = 1.815. Displayed weekly changes are +0.030, +0.010, +0.005, -0.013, and +0.008 million; their sample standard deviation is about 0.015 million, so sigma = 0.022 million after sqrt(2) scaling for the two missing weeks, and 1.28*sigma = 0.028 million. I widen the half-width to 0.040 million, about 1.45x the mechanical half-width, because rounded/revised inputs and July first-print seasonal factors add measurement and release-vintage risk. The 80% interval is therefore 1.815 +/- 0.040 = [1.775, 1.855].","Upside risk is a sudden rise in benefit duration or a July layoff path lifting the two missing weeks toward roughly +0.025 million each, which would push continued claims above 1.855 million. Downside risk is faster exits from UI or seasonal-adjustment noise pulling the two missing weeks down by roughly -0.020 million each, which would put the first print below 1.775 million. A recessionary layoff spike or a large seasonal-factor miss would land outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior uses the latest first/revised level around 1.810 million for 2026-06-27; historical sample uses recent weekly CCSA levels 1.770, 1.800, 1.810, 1.815, 1.802, 1.810. Adjustment components are +0.003 million for slower June payrolls and longer duration, +0.002 million for the latest +8000 weekly move, and 0.000 million for stable initial claims, giving point 1.810 + 0.005 = 1.815. Displayed weekly changes are +0.030, +0.010, +0.005, -0.013, and +0.008 million; their sample standard deviation is about 0.015 million, so sigma = 0.022 million after sqrt(2) scaling for the two missing weeks, and 1.28*sigma = 0.028 million. I widen the half-width to 0.040 million, about 1.45x the mechanical half-width, because rounded/revised inputs and July first-print seasonal factors add measurement and release-vintage risk. The 80% interval is therefore 1.815 +/- 0.040 = [1.775, 1.855]."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence prior uses the latest first/revised level around 1.810 million for 2026-06-27; historical sample uses recent weekly CCSA levels 1.770, 1.800, 1.810, 1.815, 1.802, 1.810. Adjustment components are +0.003 million for slower June payrolls and longer duration, +0.002 million for the latest +8000 weekly move, and 0.000 million for stable initial claims, giving point 1.810 + 0.005 = 1.815. Displayed weekly changes are +0.030, +0.010, +0.005, -0.013, and +0.008 million; their sample standard deviation is about 0.015 million, so sigma = 0.022 million after sqrt(2) scaling for the two missing weeks, and 1.28*sigma = 0.028 million. I widen the half-width to 0.040 million, about 1.45x the mechanical half-width, because rounded/revised inputs and July first-print seasonal factors add measurement and release-vintage risk. The 80% interval is therefore 1.815 +/- 0.040 = [1.775, 1.855].","Upside risk is a sudden rise in benefit duration or a July layoff path lifting the two missing weeks toward roughly +0.025 million each, which would push continued claims above 1.855 million. Downside risk is faster exits from UI or seasonal-adjustment noise pulling the two missing weeks down by roughly -0.020 million each, which would put the first print below 1.775 million. A recessionary layoff spike or a large seasonal-factor miss would land outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for DOL CCSA week ending 2026-07-11","Tool result: Recent SA continued-claims levels in millions: 2026-05-23 1.770, 2026-05-30 1.800, 2026-06-06 1.810, 2026-06-13 about 1.815 using the displayed rounded/midpoint input, 2026-06-20 about 1.802, 2026-06-27 1.810."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: continued-claims-week-2026-07-11\nrunLabel: Headline\nresolutionDate: 2026-07-23\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.ssdi-initial-applications-april-2027-work-req-deadline-holds.2026-07-08T21-37-22Z.d76c8660a952194a","runId":"run.ssdi-initial-applications-april-2027-work-req-deadline-holds.2026-07-08T21-37-22Z.d76c8660a952194a","predictionId":"ssdi-initial-applications-april-2027-work-req-deadline-holds","specId":"spec.ssdi-initial-applications-april-2027-work-req-deadline-holds","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool result: Fetched resolver facts: data are one row per State Code and Date; no summary row is provided; Field I is whole-count unsigned numeric; the same download URL is replaced as the whole file; the dataset is updated with a new time period within 30 days of the close of the prior time period.","Base rate/reference class: the best official-source numeric reference class fetched in this run is recent SSA disability-claims workload volume. DI total claims received rose from 2,071.7 thousand in FY2022 to 2,111.9 thousand in FY2023 and 2,260.6 thousand in FY2024, equal to simple monthly equivalents of 172.6, 176.0, and 188.4 thousand. SSI blind-or-disabled claims rose from 1,271.9 thousand to 1,395.6 thousand to 1,469.1 thousand, but using DI plus SSI directly would double-count concurrent filings, so I use DI as the cleaner level prior and treat SSI growth as directional support."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 6 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["Tool result: Fetched official dataset facts: monthly data begin in October 2000; the dataset covers 54 state agencies plus federal components; the expanded file has 71 data elements; Field I is Receipts (All Initial); File Version currently has value 2.","Tool result: Fetched timing evidence: SSA month data use weekly increments; an SSA month may have 4 or 5 weeks; the month normally ends on the last Friday; April 2027's last Friday is 2027-04-30, so the official within-30-days by-date is 2027-05-30."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: Opened SSA time-period documentation and date-translation source for the release timing rule.","Review disposition: accepted the leakage critique by removing the same-target prior-run point as an input; accepted the model-prior and interval critiques by explicitly labeling annual DI workloads as a fallback proxy and quantifying the widened interval from target-specific uncertainty; accepted the update critique by tying the +10.0 thousand momentum and +6.0 thousand conditional policy adjustments to observed workload growth and a low-single-digit policy channel; accepted resolver clarifications on first replacement CSV, whole-claim summing, and the 2027-05-30 by-date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 80, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = FY2024 DI claims received monthly equivalent 2,260.6/12 = 188.4 thousand; historical sample = fetched FY2022-FY2024 DI monthly equivalents converted to five-week SSA-month analogs using 5/(52/12)=1.1538, giving 199.2, 203.1, and 217.4 thousand; adjustment components = +10.0 thousand for partial continuation of the FY2022-FY2024 rise of 14.8 thousand per monthly equivalent by FY2024, +6.0 thousand for the conditional Medicaid community-engagement deadline pull-forward/channeling mechanism, roughly a low-single-digit percent effect on a five-week disability-intake base, and +0.0 thousand for rounding, giving point 217.4 + 10.0 + 6.0 = 233.4 thousand. Interval method uses the values themselves for this flow proxy: sigma = 9.6 thousand across the three five-week analogs, so 1.28*sigma = 12.3 thousand. I widen to a 40.0 thousand half-width, beyond 1.75x, because annual DI claims are not the exact monthly DDS Field I target, monthly DDS filing seasonality is unresolved here, and the conditional policy mechanism could concentrate or defer filings; final implied bounds are 233.4 +/- 40.0 = 193.4 to 273.4 thousand.","Counter-considerations: upside risk is a larger Medicaid work-requirement response, advocacy-driven disability filing surge, or SSA/DDS intake catch-up that would land above the interval if April 2027 Field I receipts exceed 273.4 thousand. Downside risk is weak policy salience, administrative friction, fewer referrals to DDS after non-disability screens, or filings shifted outside April; the result would land below the interval if receipts are under 193.4 thousand. An outside the interval print would most likely reflect exact monthly DDS Field I seasonality or a policy response stronger than the annual proxy can capture."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Exact monthly model prior limitation: the official SSA-SA-MOWL CSV is the target series and final resolver, but exact monthly Field I rows could not be rendered for model fitting in this run. The annual DI claims workload proxy is acceptable for publication only as a transparent fallback because it is official SSA disability-intake evidence, close to the same broad claims-flow family, and not used as ground-truth resolution.","Level, momentum, one-off, and policy mechanism: level starts from the FY2024 DI claims monthly equivalent because Field I all-initial DDS receipts should be in the same broad disability-intake family but is not identical to annual DI claims. Momentum is positive across FY2022-FY2024. The one-off calendar effect is April 2027's five-week SSA month. The conditional policy mechanism adds filing pressure because people facing Medicaid community-engagement compliance may seek disability documentation, SSI/DI eligibility, or exemption-related evidence, but the adjustment is modest because awareness, non-disability screens, processing frictions, and concurrent-claim double-counting limit direct translation to DDS receipts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: the best official-source numeric reference class fetched in this run is recent SSA disability-claims workload volume. DI total claims received rose from 2,071.7 thousand in FY2022 to 2,111.9 thousand in FY2023 and 2,260.6 thousand in FY2024, equal to simple monthly equivalents of 172.6, 176.0, and 188.4 thousand. SSI blind-or-disabled claims rose from 1,271.9 thousand to 1,395.6 thousand to 1,469.1 thousand, but using DI plus SSI directly would double-count concurrent filings, so I use DI as the cleaner level prior and treat SSI growth as directional support.","Exact monthly model prior limitation: the official SSA-SA-MOWL CSV is the target series and final resolver, but exact monthly Field I rows could not be rendered for model fitting in this run. The annual DI claims workload proxy is acceptable for publication only as a transparent fallback because it is official SSA disability-intake evidence, close to the same broad claims-flow family, and not used as ground-truth resolution."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Framing and exact resolver: this forecast targets SSA State Agency Monthly Workload Data monthly Field I, Receipts (All Initial), for Date Type MO and Formatted Date 2027-04. The variant is not seasonally adjusted, is a DDS/state-agency initial-claims workload flow, and is not OASDI beneficiary stock, SSI monthly payment statistics, or final revised annual claims workload.","Prior/update/interval: persistence prior = FY2024 DI claims received monthly equivalent 2,260.6/12 = 188.4 thousand; historical sample = fetched FY2022-FY2024 DI monthly equivalents converted to five-week SSA-month analogs using 5/(52/12)=1.1538, giving 199.2, 203.1, and 217.4 thousand; adjustment components = +10.0 thousand for partial continuation of the FY2022-FY2024 rise of 14.8 thousand per monthly equivalent by FY2024, +6.0 thousand for the conditional Medicaid community-engagement deadline pull-forward/channeling mechanism, roughly a low-single-digit percent effect on a five-week disability-intake base, and +0.0 thousand for rounding, giving point 217.4 + 10.0 + 6.0 = 233.4 thousand. Interval method uses the values themselves for this flow proxy: sigma = 9.6 thousand across the three five-week analogs, so 1.28*sigma = 12.3 thousand. I widen to a 40.0 thousand half-width, beyond 1.75x, because annual DI claims are not the exact monthly DDS Field I target, monthly DDS filing seasonality is unresolved here, and the conditional policy mechanism could concentrate or defer filings; final implied bounds are 233.4 +/- 40.0 = 193.4 to 273.4 thousand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: ssdi-initial-applications-april-2027-work-req-deadline-holds\nrunLabel: Headline\nresolutionDate: 2027-05-30\ntraceLineCount: 21\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.ssdi-initial-applications-april-2027-work-req-deadline-delayed.2026-07-08T21-44-19Z.2ac3569c17e91645","runId":"run.ssdi-initial-applications-april-2027-work-req-deadline-delayed.2026-07-08T21-44-19Z.2ac3569c17e91645","predictionId":"ssdi-initial-applications-april-2027-work-req-deadline-delayed","specId":"spec.ssdi-initial-applications-april-2027-work-req-deadline-delayed","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool result: Fetched resolver facts: data are one row per State Code and Date; no summary row is provided; Field I is whole-count unsigned numeric; the same download URL is replaced as the whole file; the dataset is updated with a new time period within 30 days of the close of the prior time period.","Base rate/reference class: the preferred base rate would be summed Field I MO history from SSA-SA-MOWL.csv. In the draft evidence, the exact public CSV was identified as the resolver but could not be streamed as tabular rows, so the usable official-source numeric reference class is recent SSA disability-claims workload volume. DI total claims received rose from 2,071.7 thousand in FY2022 to 2,111.9 thousand in FY2023 and 2,260.6 thousand in FY2024, equal to simple monthly equivalents of 172.6, 176.0, and 188.4 thousand. SSI blind-or-disabled claims also rose from 1,271.9 thousand to 1,395.6 thousand to 1,469.1 thousand, but DI plus SSI would double-count concurrent filings, so I use DI as the cleaner level proxy and SSI as directional support."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 6 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["Tool result: Fetched official dataset facts: monthly data begin in October 2000; the dataset covers 54 state agencies plus federal components; the expanded file has 71 data elements; Field I is Receipts (All Initial); File Version currently has value 2.","Base rate/reference class: the preferred base rate would be summed Field I MO history from SSA-SA-MOWL.csv. In the draft evidence, the exact public CSV was identified as the resolver but could not be streamed as tabular rows, so the usable official-source numeric reference class is recent SSA disability-claims workload volume. DI total claims received rose from 2,071.7 thousand in FY2022 to 2,111.9 thousand in FY2023 and 2,260.6 thousand in FY2024, equal to simple monthly equivalents of 172.6, 176.0, and 188.4 thousand. SSI blind-or-disabled claims also rose from 1,271.9 thousand to 1,395.6 thousand to 1,469.1 thousand, but DI plus SSI would double-count concurrent filings, so I use DI as the cleaner level proxy and SSI as directional support."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: Opened SSA Date Table documentation and the SSA monthly workload timing rule to verify the release by-date treatment.","Level, momentum, one-off, and policy mechanism: level starts from the FY2024 DI claims monthly equivalent because Field I all-initial DDS receipts should be in the same broad disability-intake family but is not identical to annual DI claims. The expected bias from DI-only annual claims is ambiguous: DI excludes SSI-only disability paths that may appear in DDS workload, but annual national claims received are not a first-print state-agency monthly sum and concurrent filings can overlap. Momentum is positive across FY2022-FY2024. The one-off calendar effect is April 2027's five-week SSA month. Under this delayed-deadline condition, I remove the April 2027 near-deadline Medicaid community-engagement filing-pressure adjustment because the compliance deadline no longer binds in or before April 2027."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 80, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = FY2024 DI claims received monthly equivalent 2,260.6/12 = 188.4 thousand; historical sample = fetched FY2022-FY2024 DI monthly equivalents converted to five-week SSA-month analogs using 5/(52/12)=1.1538, giving 199.2, 203.1, and 217.4 thousand; adjustment components = +10.0 thousand for partial continuation of the FY2022-FY2024 rise of 14.8 thousand per monthly equivalent by FY2024, +0.0 thousand for the delayed Medicaid community-engagement deadline because April 2027 deadline pressure is absent, and +0.0 thousand for rounding, giving point 217.4 + 10.0 + 0.0 = 227.4 thousand. Interval method uses the values themselves for this flow proxy: sigma = 9.6 thousand across the three five-week analogs, so 1.28*sigma = 12.3 thousand. I widen to a 40.0 thousand half-width, beyond 1.75x, because annual DI claims are not the exact monthly DDS Field I target, monthly DDS filing seasonality is unresolved here, and the conditional delay could shift filings away from April; final implied bounds are 227.4 +/- 40.0 = 187.4 to 267.4 thousand.","Counter-considerations: upside risk is that disability-claim filing momentum continues independently of the Medicaid deadline, DDS intake backlogs are cleared into April, or outreach tied to the policy debate still boosts applications; that would land above the interval if receipts exceed 267.4 thousand. Downside risk is that delayed work-requirement timing reduces urgency, applications shift outside April, or non-disability eligibility screens prevent referrals to DDS; the result would land below the interval if receipts are under 187.4 thousand. An outside the interval print would most likely reflect exact monthly DDS Field I seasonality or coverage differences that the annual proxy did not capture."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior public Thesis runs for this target family were inspected only as public strategy context. The useful update from the prior run is the reviewer warning that exact SSA-SA-MOWL Field I monthly history would be preferable; because the exact CSV rows were not available in the draft evidence, this forecast keeps the official annual workload fallback transparent and does not use any existing catalog estimate as evidence.","Level, momentum, one-off, and policy mechanism: level starts from the FY2024 DI claims monthly equivalent because Field I all-initial DDS receipts should be in the same broad disability-intake family but is not identical to annual DI claims. The expected bias from DI-only annual claims is ambiguous: DI excludes SSI-only disability paths that may appear in DDS workload, but annual national claims received are not a first-print state-agency monthly sum and concurrent filings can overlap. Momentum is positive across FY2022-FY2024. The one-off calendar effect is April 2027's five-week SSA month. Under this delayed-deadline condition, I remove the April 2027 near-deadline Medicaid community-engagement filing-pressure adjustment because the compliance deadline no longer binds in or before April 2027."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: the preferred base rate would be summed Field I MO history from SSA-SA-MOWL.csv. In the draft evidence, the exact public CSV was identified as the resolver but could not be streamed as tabular rows, so the usable official-source numeric reference class is recent SSA disability-claims workload volume. DI total claims received rose from 2,071.7 thousand in FY2022 to 2,111.9 thousand in FY2023 and 2,260.6 thousand in FY2024, equal to simple monthly equivalents of 172.6, 176.0, and 188.4 thousand. SSI blind-or-disabled claims also rose from 1,271.9 thousand to 1,395.6 thousand to 1,469.1 thousand, but DI plus SSI would double-count concurrent filings, so I use DI as the cleaner level proxy and SSI as directional support.","Level, momentum, one-off, and policy mechanism: level starts from the FY2024 DI claims monthly equivalent because Field I all-initial DDS receipts should be in the same broad disability-intake family but is not identical to annual DI claims. The expected bias from DI-only annual claims is ambiguous: DI excludes SSI-only disability paths that may appear in DDS workload, but annual national claims received are not a first-print state-agency monthly sum and concurrent filings can overlap. Momentum is positive across FY2022-FY2024. The one-off calendar effect is April 2027's five-week SSA month. Under this delayed-deadline condition, I remove the April 2027 near-deadline Medicaid community-engagement filing-pressure adjustment because the compliance deadline no longer binds in or before April 2027."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Framing and exact resolver: this forecast targets SSA State Agency Monthly Workload Data monthly Field I, Receipts (All Initial), for Date Type MO and Formatted Date 2027-04. The variant is not seasonally adjusted, is a DDS/state-agency all-initial disability-claim workload flow, and is not OASDI beneficiary stock, SSI monthly payment statistics, FRED history, or final revised annual claims workload.","Prior public Thesis runs for this target family were inspected only as public strategy context. The useful update from the prior run is the reviewer warning that exact SSA-SA-MOWL Field I monthly history would be preferable; because the exact CSV rows were not available in the draft evidence, this forecast keeps the official annual workload fallback transparent and does not use any existing catalog estimate as evidence."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: ssdi-initial-applications-april-2027-work-req-deadline-delayed\nrunLabel: Headline\nresolutionDate: 2027-05-30\ntraceLineCount: 21\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.ca-medicaid-enrollment-50-64-april-2027-work-req-deadline-holds.2026-07-08T21-15-07Z.4acf40b6aedb8efc","runId":"run.ca-medicaid-enrollment-50-64-april-2027-work-req-deadline-holds.2026-07-08T21-15-07Z.4acf40b6aedb8efc","predictionId":"ca-medicaid-enrollment-50-64-april-2027-work-req-deadline-holds","specId":"spec.ca-medicaid-enrollment-50-64-april-2027-work-req-deadline-holds","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the recent official-source reference class is the same DHCS statewide ages 50-64 certified eligibles series from October 2025 through March 2026. It declined from 2810.3 thousand to 2748.4 thousand over five months, a 61.9 thousand drop, or about -12.4 thousand per month before any 2027 community-engagement effect.","Prior/update/interval: persistence prior is March 2026 level 2748.4 thousand; historical sample is October 2025-March 2026 same DHCS age-band series with successive changes of -13.5, -12.2, -13.0, -11.7, and -11.5 thousand, raw monthly sigma = 0.8 thousand. Adjustment components are ordinary drift -105 thousand and early work-requirement mechanism -153 thousand, giving point = 2748.4 - 105 - 153 = 2490.4 thousand, rounded to 2490. For the 80% interval I do not use the raw one-month sigma directly because the 13-month horizon includes a new policy regime; I use drift uncertainty sigma = 70 thousand and policy-implementation uncertainty sigma = 157 thousand, combined as sqrt(70^2 + 157^2) = 172 thousand, so half-width is about 1.28*sigma = 1.28*172 = 220 thousand, yielding 2490 +/- 220 = [2270, 2710]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this targets the DHCS/CHHS statewide Medi-Cal certified eligibles age-band series for ages 50-64, first April 2027 monthly print, converted to thousands. The ledger slug resembles a broader Medicaid enrollment cell, but I keep the forecast tied to the requested CA DHCS age-band series and note that the target unit is thousands.","Tool call: Checked earlier DHCS/CHHS monthly age-band observations for the same statewide certified eligibles variant."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this targets the DHCS/CHHS statewide Medi-Cal certified eligibles age-band series for ages 50-64, first April 2027 monthly print, converted to thousands. The ledger slug resembles a broader Medicaid enrollment cell, but I keep the forecast tied to the requested CA DHCS age-band series and note that the target unit is thousands.","Tool call: Checked official DHCS/CHHS release timing metadata and recent monthly publication pattern for the April reference month."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 440, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is March 2026 level 2748.4 thousand; historical sample is October 2025-March 2026 same DHCS age-band series with successive changes of -13.5, -12.2, -13.0, -11.7, and -11.5 thousand, raw monthly sigma = 0.8 thousand. Adjustment components are ordinary drift -105 thousand and early work-requirement mechanism -153 thousand, giving point = 2748.4 - 105 - 153 = 2490.4 thousand, rounded to 2490. For the 80% interval I do not use the raw one-month sigma directly because the 13-month horizon includes a new policy regime; I use drift uncertainty sigma = 70 thousand and policy-implementation uncertainty sigma = 157 thousand, combined as sqrt(70^2 + 157^2) = 172 thousand, so half-width is about 1.28*sigma = 1.28*172 = 220 thousand, yielding 2490 +/- 220 = [2270, 2710].","Counter-considerations: upside risk is that California implements slowly, many ages 50-64 beneficiaries qualify for exemptions, or ordinary attrition stabilizes, which would land above the interval. Downside risk is faster notices/disenrollments, lower redetermination completion, or stronger spillover churn among exempt people, which would land below the interval. Outside the interval would require either almost no early community-engagement effect by April 2027 or a rapid loss exceeding about 375 thousand from the latest age-band level."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and policy effects: the latest level is 2748.4 thousand. Simple continuation of the recent -12.4 thousand monthly drift for 13 months would subtract about 161 thousand, but I damp ordinary drift to -105 thousand because post-unwinding attrition should slow. I then subtract about 153 thousand as a judgmental early community-engagement implementation effect: roughly 900 thousand ages 50-64 beneficiaries potentially exposed to adult eligibility processes or spillover churn, about 45% effectively reached by early notices or renewal interactions by April 2027, and about 38% of that reached group losing or delaying coverage net of exemptions, documentation, appeals, and California administrative lag, or 900*0.45*0.38 = 154 thousand.","Prior/update/interval: persistence prior is March 2026 level 2748.4 thousand; historical sample is October 2025-March 2026 same DHCS age-band series with successive changes of -13.5, -12.2, -13.0, -11.7, and -11.5 thousand, raw monthly sigma = 0.8 thousand. Adjustment components are ordinary drift -105 thousand and early work-requirement mechanism -153 thousand, giving point = 2748.4 - 105 - 153 = 2490.4 thousand, rounded to 2490. For the 80% interval I do not use the raw one-month sigma directly because the 13-month horizon includes a new policy regime; I use drift uncertainty sigma = 70 thousand and policy-implementation uncertainty sigma = 157 thousand, combined as sqrt(70^2 + 157^2) = 172 thousand, so half-width is about 1.28*sigma = 1.28*172 = 220 thousand, yielding 2490 +/- 220 = [2270, 2710]."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Framing and exact resolver: this targets the DHCS/CHHS statewide Medi-Cal certified eligibles age-band series for ages 50-64, first April 2027 monthly print, converted to thousands. The ledger slug resembles a broader Medicaid enrollment cell, but I keep the forecast tied to the requested CA DHCS age-band series and note that the target unit is thousands.","Level, momentum, one-off, and policy effects: the latest level is 2748.4 thousand. Simple continuation of the recent -12.4 thousand monthly drift for 13 months would subtract about 161 thousand, but I damp ordinary drift to -105 thousand because post-unwinding attrition should slow. I then subtract about 153 thousand as a judgmental early community-engagement implementation effect: roughly 900 thousand ages 50-64 beneficiaries potentially exposed to adult eligibility processes or spillover churn, about 45% effectively reached by early notices or renewal interactions by April 2027, and about 38% of that reached group losing or delaying coverage net of exemptions, documentation, appeals, and California administrative lag, or 900*0.45*0.38 = 154 thousand."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for California Medi-Cal certified eligibles ages 50-64 in April 2027 if the federal deadline holds","Framing and exact resolver: this targets the DHCS/CHHS statewide Medi-Cal certified eligibles age-band series for ages 50-64, first April 2027 monthly print, converted to thousands. The ledger slug resembles a broader Medicaid enrollment cell, but I keep the forecast tied to the requested CA DHCS age-band series and note that the target unit is thousands."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: ca-medicaid-enrollment-50-64-april-2027-work-req-deadline-holds\nrunLabel: Headline\nresolutionDate: 2027-07-30\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.ca-medicaid-enrollment-50-64-april-2027-work-req-deadline-delayed.2026-07-08T21-45-33Z.0d35cc0e4bdced88","runId":"run.ca-medicaid-enrollment-50-64-april-2027-work-req-deadline-delayed.2026-07-08T21-45-33Z.0d35cc0e4bdced88","predictionId":"ca-medicaid-enrollment-50-64-april-2027-work-req-deadline-delayed","specId":"spec.ca-medicaid-enrollment-50-64-april-2027-work-req-deadline-delayed","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the recent official-source reference class is the same DHCS statewide ages 50-64 certified eligibles series from October 2025 through March 2026. It fell from 2810.3 thousand to 2748.4 thousand over five monthly moves, a 61.9 thousand drop, or about -12.4 thousand per month before any 2027 community-engagement effect. I did not use broader pre-2025 history or seasonality because the conditional target is dominated by the post-unwinding level path and the specific work-requirement delay mechanism.","Prior/update/interval: persistence prior is March 2026 level 2748.4 thousand; historical sample is October 2025-March 2026 same DHCS age-band series with successive monthly changes of -13.5, -12.2, -13.0, -11.7, and -11.5 thousand, so raw monthly sigma = 0.8 thousand. Adjustment components are ordinary drift -105 thousand and delayed-deadline avoided churn +20 thousand, giving point = 2748.4 - 105 + 20 = 2663.4 thousand, rounded to 2663. The one-month sigma only measures short-run smoothness and is too narrow for a 13-month conditional policy forecast; I therefore use judgmental scenario forecast sigma = 90 thousand around the 13-month net change: stabilization near -50 thousand, baseline near -85 thousand, continuation near -160 thousand, and renewed churn near -200 thousand. The 80% half-width is about 1.28*sigma = 1.28*90 = 115 thousand, yielding 2663 +/- 115 = [2548, 2778], with bounds rounded after converting persons to thousands."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this is the DHCS/CHHS statewide Medi-Cal Certified Eligibles Recent Trends age-band series for ages 50-64, first April 2027 monthly print, converted from persons to thousands. The target is conditional on a federal statutory or regulatory delay announced on or before 2027-03-31 that pushes the community-engagement effective date beyond April 2027. I use the requested ledger slug, unit, dataPointId, and first-print resolver.","Tool call: Checked earlier observations from the same DHCS/CHHS statewide certified eligibles age-band series for the recent reference class."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this is the DHCS/CHHS statewide Medi-Cal Certified Eligibles Recent Trends age-band series for ages 50-64, first April 2027 monthly print, converted from persons to thousands. The target is conditional on a federal statutory or regulatory delay announced on or before 2027-03-31 that pushes the community-engagement effective date beyond April 2027. I use the requested ledger slug, unit, dataPointId, and first-print resolver.","Tool call: Checked DHCS/CHHS monthly publication timing metadata and the DHCS eligibility statistics page for the April-reference release date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 230, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is March 2026 level 2748.4 thousand; historical sample is October 2025-March 2026 same DHCS age-band series with successive monthly changes of -13.5, -12.2, -13.0, -11.7, and -11.5 thousand, so raw monthly sigma = 0.8 thousand. Adjustment components are ordinary drift -105 thousand and delayed-deadline avoided churn +20 thousand, giving point = 2748.4 - 105 + 20 = 2663.4 thousand, rounded to 2663. The one-month sigma only measures short-run smoothness and is too narrow for a 13-month conditional policy forecast; I therefore use judgmental scenario forecast sigma = 90 thousand around the 13-month net change: stabilization near -50 thousand, baseline near -85 thousand, continuation near -160 thousand, and renewed churn near -200 thousand. The 80% half-width is about 1.28*sigma = 1.28*90 = 115 thousand, yielding 2663 +/- 115 = [2548, 2778], with bounds rounded after converting persons to thousands.","Counter-considerations: upside risk is that California's post-unwinding enrollment stabilizes faster than expected, adult coverage expansions remain sticky, and no work-requirement preparation chills renewals, which would land above the interval. Downside risk is renewed redetermination attrition, state budget or administrative tightening, or spillover confusion despite the delay; about -15.4 thousand per month from March 2026 through April 2027 would push the count below 2548 thousand. Outside the interval would require either a near-flat 2026-2027 age-band path above 2778 thousand or a renewed attrition episode pushing the count below 2548 thousand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate/reference class: the recent official-source reference class is the same DHCS statewide ages 50-64 certified eligibles series from October 2025 through March 2026. It fell from 2810.3 thousand to 2748.4 thousand over five monthly moves, a 61.9 thousand drop, or about -12.4 thousand per month before any 2027 community-engagement effect. I did not use broader pre-2025 history or seasonality because the conditional target is dominated by the post-unwinding level path and the specific work-requirement delay mechanism.","Level, momentum, one-off, and policy effects: latest level is 2748.4 thousand. A mechanical continuation of the recent -12.4 thousand monthly drift for 13 months would subtract about 161 thousand, but I damp that to -105 thousand because post-unwinding attrition should slow. Under the delay condition, I add no April 2027 community-engagement disenrollment loss and include a small +20 thousand relative adjustment for avoided pre-implementation procedural churn, notices, and beneficiary confusion."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, one-off, and policy effects: latest level is 2748.4 thousand. A mechanical continuation of the recent -12.4 thousand monthly drift for 13 months would subtract about 161 thousand, but I damp that to -105 thousand because post-unwinding attrition should slow. Under the delay condition, I add no April 2027 community-engagement disenrollment loss and include a small +20 thousand relative adjustment for avoided pre-implementation procedural churn, notices, and beneficiary confusion.","Counter-considerations: upside risk is that California's post-unwinding enrollment stabilizes faster than expected, adult coverage expansions remain sticky, and no work-requirement preparation chills renewals, which would land above the interval. Downside risk is renewed redetermination attrition, state budget or administrative tightening, or spillover confusion despite the delay; about -15.4 thousand per month from March 2026 through April 2027 would push the count below 2548 thousand. Outside the interval would require either a near-flat 2026-2027 age-band path above 2778 thousand or a renewed attrition episode pushing the count below 2548 thousand."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for California Medi-Cal certified eligibles ages 50-64 in April 2027 if the federal deadline is delayed","Framing and exact resolver: this is the DHCS/CHHS statewide Medi-Cal Certified Eligibles Recent Trends age-band series for ages 50-64, first April 2027 monthly print, converted from persons to thousands. The target is conditional on a federal statutory or regulatory delay announced on or before 2027-03-31 that pushes the community-engagement effective date beyond April 2027. I use the requested ledger slug, unit, dataPointId, and first-print resolver."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: ca-medicaid-enrollment-50-64-april-2027-work-req-deadline-delayed\nrunLabel: Headline\nresolutionDate: 2027-07-30\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.va-pending-disability-claims-2026-07-13.2026-07-08T20-38-05Z.1b5300661dfd0084","runId":"run.va-pending-disability-claims-2026-07-13.2026-07-08T20-38-05Z.1b5300661dfd0084","predictionId":"va-pending-disability-claims-2026-07-13","specId":"spec.va-pending-disability-claims-2026-07-13","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: for a one-week-ahead level forecast, persistence plus the recent same-series weekly change is the base rate. The latest level is 601.630 thousand and the last three week-to-week changes were +2.211, +2.729, and +2.610 thousand, so the outside-view central tendency is a continued modest increase rather than a flat print.","Prior/update/interval: persistence prior = 601.630 thousand from the 2026-07-06 first print; historical sample = recent VA MMWR claims inventory weekly changes from 2026-06-15 through 2026-07-06 for direction, combined with an explicit judgmental uncertainty allowance of sigma = 4.6 thousand because holiday-week intake and completions can create wider one-week misses than the three listed changes alone; adjustment components = +2.1 thousand level/momentum, +0.0 thousand policy mechanism because no new adjudication rule was identified, and -0.0 thousand one-off holiday rebound offset because the target week is mostly normal operations; interval method = one-week successive-change dispersion allowance with sigma = 4.6 thousand, so 80% half-width = 1.28*4.6 = 5.9 thousand; final implied bounds are 603.7 - 5.9 = 597.8 and 603.7 + 5.9 = 609.6 thousand."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 2 source-context item(s), activity log present.","evidence":["Tool result: Fetched report schedule entries including 07/06/2026 linked as the latest posted report, 07/13/2026 listed as the next target report date, 07/20/2026, and 07/27/2026; this verifies resolutionDate 2026-07-13 from the official VA page rather than inferring from cadence.","Tool call: Used the official VA weekly report series as the recent reference class for the same claims inventory variant."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this is the VA VBA Monday Morning Workload Report claims inventory series, the rating-bundle disability compensation and pension claims that normally require development and a VBA claims processor decision; I use the not seasonally adjusted first print in whole claims and convert to thousands. The resolutionDate is the VA report date, not a guarantee of the public posting timestamp.","Tool call: Checked the 2026 Monday Morning Workload Reports table on the VA Detailed Claims Data page for the release schedule."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 11.8, distribution present, forecast step count 1.","evidence":["Tool call: Opened VA Detailed Claims Data page for the current status cards and series definition.","Tool call: Checked the 2026 Monday Morning Workload Reports table on the VA Detailed Claims Data page for the release schedule."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior = 601.630 thousand from the 2026-07-06 first print; historical sample = recent VA MMWR claims inventory weekly changes from 2026-06-15 through 2026-07-06 for direction, combined with an explicit judgmental uncertainty allowance of sigma = 4.6 thousand because holiday-week intake and completions can create wider one-week misses than the three listed changes alone; adjustment components = +2.1 thousand level/momentum, +0.0 thousand policy mechanism because no new adjudication rule was identified, and -0.0 thousand one-off holiday rebound offset because the target week is mostly normal operations; interval method = one-week successive-change dispersion allowance with sigma = 4.6 thousand, so 80% half-width = 1.28*4.6 = 5.9 thousand; final implied bounds are 603.7 - 5.9 = 597.8 and 603.7 + 5.9 = 609.6 thousand.","Level, momentum, one-off, and mechanism effects: the level anchor is 601.630 thousand; momentum adds about 2 thousand because the latest official sequence is rising; the July 4 timing could have lifted the latest inventory but does not by itself imply a large reversal; absent a new VA processing surge or intake shock, weekly movement should stay in a single-digit-thousand range."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence prior = 601.630 thousand from the 2026-07-06 first print; historical sample = recent VA MMWR claims inventory weekly changes from 2026-06-15 through 2026-07-06 for direction, combined with an explicit judgmental uncertainty allowance of sigma = 4.6 thousand because holiday-week intake and completions can create wider one-week misses than the three listed changes alone; adjustment components = +2.1 thousand level/momentum, +0.0 thousand policy mechanism because no new adjudication rule was identified, and -0.0 thousand one-off holiday rebound offset because the target week is mostly normal operations; interval method = one-week successive-change dispersion allowance with sigma = 4.6 thousand, so 80% half-width = 1.28*4.6 = 5.9 thousand; final implied bounds are 603.7 - 5.9 = 597.8 and 603.7 + 5.9 = 609.6 thousand.","Level, momentum, one-off, and mechanism effects: the level anchor is 601.630 thousand; momentum adds about 2 thousand because the latest official sequence is rising; the July 4 timing could have lifted the latest inventory but does not by itself imply a large reversal; absent a new VA processing surge or intake shock, weekly movement should stay in a single-digit-thousand range."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["VA VBA pending disability compensation claims forecast","Reference class and base rate: for a one-week-ahead level forecast, persistence plus the recent same-series weekly change is the base rate. The latest level is 601.630 thousand and the last three week-to-week changes were +2.211, +2.729, and +2.610 thousand, so the outside-view central tendency is a continued modest increase rather than a flat print."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: va-pending-disability-claims-2026-07-13\nrunLabel: Headline\nresolutionDate: 2026-07-13\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.ssi-recipients-aged-65-plus-june-2026.2026-07-08T20-13-39Z.d6872bbfee752e15","runId":"run.ssi-recipients-aged-65-plus-june-2026.2026-07-08T20-13-39Z.d6872bbfee752e15","predictionId":"ssi-recipients-aged-65-plus-june-2026","specId":"spec.ssi-recipients-aged-65-plus-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the recent official-source class is monthly Table 1 aged-65-plus recipient levels from May 2025 through May 2026. The latest level, 2501.549 thousand, is 19.025 thousand above May 2025 but 7.564 thousand below January 2026; that argues for persistence with a small positive June seasonal/current adjustment rather than a large trend extrapolation.","Prior/update/interval: persistence prior = May 2026 latest level 2501.549 thousand; historical sample = same-variant May 2025-May 2026 monthly levels; adjustment components = +1.636 thousand for the May-to-June 2025 seasonal move, +0.0 for policy mechanism because no June 2026 SSI eligibility/payment rule shock is assumed, and about -0.1 rounding/current-drift offset after the early-2026 decline, giving point 2501.549 + 1.636 - 0.085 = 2503.100 thousand. Interval method uses sample standard deviation of successive monthly changes from May 2025 to May 2026: changes were +1.636, +2.947, +10.056, +11.539, -4.618, +2.367, +5.948, -3.286, -2.323, -4.657, -1.711, +1.127 thousand; sigma = 5.392, half-width = 1.28*sigma = 6.902 thousand, so 80% interval = 2503.100 +/- 6.902 = [2496.198, 2510.002], rounded to 2496.2 to 2510.0 thousand."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 8 source-context item(s), activity log present.","evidence":["Base rate/reference class: the recent official-source class is monthly Table 1 aged-65-plus recipient levels from May 2025 through May 2026. The latest level, 2501.549 thousand, is 19.025 thousand above May 2025 but 7.564 thousand below January 2026; that argues for persistence with a small positive June seasonal/current adjustment rather than a large trend extrapolation.","Counter-considerations: upside risk is a continuation of the May rebound plus faster aged inflows, which would land above the interval if June rises by more than about 8.5 thousand recipients from May. Downside risk is renewed terminations or returned-check downward adjustment already reflected in the first published June table, which would land below the interval if June falls by more than about 5.3 thousand from May. A policy or administrative cleanup affecting aged SSI eligibility would be the main outside the interval scenario."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["SSI aged-65-plus recipients, June 2026 first print","Tool call: Opened SSA SSI Monthly Statistics current index and SSA Publishing Schedule for release timing."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 13.8, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = May 2026 latest level 2501.549 thousand; historical sample = same-variant May 2025-May 2026 monthly levels; adjustment components = +1.636 thousand for the May-to-June 2025 seasonal move, +0.0 for policy mechanism because no June 2026 SSI eligibility/payment rule shock is assumed, and about -0.1 rounding/current-drift offset after the early-2026 decline, giving point 2501.549 + 1.636 - 0.085 = 2503.100 thousand. Interval method uses sample standard deviation of successive monthly changes from May 2025 to May 2026: changes were +1.636, +2.947, +10.056, +11.539, -4.618, +2.367, +5.948, -3.286, -2.323, -4.657, -1.711, +1.127 thousand; sigma = 5.392, half-width = 1.28*sigma = 6.902 thousand, so 80% interval = 2503.100 +/- 6.902 = [2496.198, 2510.002], rounded to 2496.2 to 2510.0 thousand.","Counter-considerations: upside risk is a continuation of the May rebound plus faster aged inflows, which would land above the interval if June rises by more than about 8.5 thousand recipients from May. Downside risk is renewed terminations or returned-check downward adjustment already reflected in the first published June table, which would land below the interval if June falls by more than about 5.3 thousand from May. A policy or administrative cleanup affecting aged SSI eligibility would be the main outside the interval scenario."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior = May 2026 latest level 2501.549 thousand; historical sample = same-variant May 2025-May 2026 monthly levels; adjustment components = +1.636 thousand for the May-to-June 2025 seasonal move, +0.0 for policy mechanism because no June 2026 SSI eligibility/payment rule shock is assumed, and about -0.1 rounding/current-drift offset after the early-2026 decline, giving point 2501.549 + 1.636 - 0.085 = 2503.100 thousand. Interval method uses sample standard deviation of successive monthly changes from May 2025 to May 2026: changes were +1.636, +2.947, +10.056, +11.539, -4.618, +2.367, +5.948, -3.286, -2.323, -4.657, -1.711, +1.127 thousand; sigma = 5.392, half-width = 1.28*sigma = 6.902 thousand, so 80% interval = 2503.100 +/- 6.902 = [2496.198, 2510.002], rounded to 2496.2 to 2510.0 thousand."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool result: Fetched timing evidence: current SSI Monthly Statistics page is May 2026 and states released June 2026; SSA Publishing Schedule lists SSI Monthly Statistics frequency as Monthly; run date is 2026-07-08; the schedule gives month-level timing but no exact June 2026 release day, so 2026-07-31 is used as the catalog latest expected by-date.","Base rate/reference class: the recent official-source class is monthly Table 1 aged-65-plus recipient levels from May 2025 through May 2026. The latest level, 2501.549 thousand, is 19.025 thousand above May 2025 but 7.564 thousand below January 2026; that argues for persistence with a small positive June seasonal/current adjustment rather than a large trend extrapolation."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: persistence prior = May 2026 latest level 2501.549 thousand; historical sample = same-variant May 2025-May 2026 monthly levels; adjustment components = +1.636 thousand for the May-to-June 2025 seasonal move, +0.0 for policy mechanism because no June 2026 SSI eligibility/payment rule shock is assumed, and about -0.1 rounding/current-drift offset after the early-2026 decline, giving point 2501.549 + 1.636 - 0.085 = 2503.100 thousand. Interval method uses sample standard deviation of successive monthly changes from May 2025 to May 2026: changes were +1.636, +2.947, +10.056, +11.539, -4.618, +2.367, +5.948, -3.286, -2.323, -4.657, -1.711, +1.127 thousand; sigma = 5.392, half-width = 1.28*sigma = 6.902 thousand, so 80% interval = 2503.100 +/- 6.902 = [2496.198, 2510.002], rounded to 2496.2 to 2510.0 thousand.","Counter-considerations: upside risk is a continuation of the May rebound plus faster aged inflows, which would land above the interval if June rises by more than about 8.5 thousand recipients from May. Downside risk is renewed terminations or returned-check downward adjustment already reflected in the first published June table, which would land below the interval if June falls by more than about 5.3 thousand from May. A policy or administrative cleanup affecting aged SSI eligibility would be the main outside the interval scenario."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: ssi-recipients-aged-65-plus-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-31\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.ssdi-disabled-worker-beneficiaries-june-2026.2026-07-08T20-16-27Z.17da6676d56decb3","runId":"run.ssdi-disabled-worker-beneficiaries-june-2026.2026-07-08T20-16-27Z.17da6676d56decb3","predictionId":"ssdi-disabled-worker-beneficiaries-june-2026","specId":"spec.ssdi-disabled-worker-beneficiaries-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the recent official-source reference class is successive changes in the same Table 2 disabled-worker stock from December 2025 through May 2026. The monthly changes are -27, -18, -11, -20, and -21 thousand, showing a steady decline rather than a flat level.","Prior/update/interval: May-level persistence plus recent mean monthly change prior on the Dec 2025-May 2026 official sample gives mean change = (-27 - 18 - 11 - 20 - 21) / 5 = -19.4 thousand, so point = 7,029 - 19.4 = 7,009.6, rounded to 7,010. For the 80% interval, sample sigma from successive changes = 5.77 thousand, so half-width = 1.28*sigma = 1.28*5.77 = 7.39 thousand; 7,009.6 +/- 7.39 gives 7,002.2 to 7,017.0, rounded to 7,002-7,017. The five-change local-volatility window is intentional for this one-month-ahead first-print forecast because the roll is smooth and recent administrative trend is the main near-term risk signal."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 8 source-context item(s), activity log present.","evidence":["Tool call: Opened SSA Monthly Statistical Snapshot current page and Table 2 for latest official value.","Tool result: Fetched SSA Publishing Schedule text: Monthly Statistical Snapshot frequency is Monthly; current snapshot page says May 2026 was released in June 2026, so the June 2026 first print is scheduled for the July 2026 monthly update, with ledger resolutionDate 2026-07-31."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["SSDI disabled-worker beneficiaries, June 2026 first print","Framing and exact resolver: the target is SSA Monthly Statistical Snapshot Table 2, Social Security benefits, Disability Insurance, Disabled workers, Beneficiaries Number, in thousands, for June 2026. The resolution page should follow SSA's monthly archive pattern at /policy/docs/quickfacts/stat_snapshot/2026-06.html, with the value rounded to whole thousands as printed; this is the not seasonally adjusted published SSA snapshot stock."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 15, distribution present, forecast step count 1.","evidence":["Prior/update/interval: May-level persistence plus recent mean monthly change prior on the Dec 2025-May 2026 official sample gives mean change = (-27 - 18 - 11 - 20 - 21) / 5 = -19.4 thousand, so point = 7,029 - 19.4 = 7,009.6, rounded to 7,010. For the 80% interval, sample sigma from successive changes = 5.77 thousand, so half-width = 1.28*sigma = 1.28*5.77 = 7.39 thousand; 7,009.6 +/- 7.39 gives 7,002.2 to 7,017.0, rounded to 7,002-7,017. The five-change local-volatility window is intentional for this one-month-ahead first-print forecast because the roll is smooth and recent administrative trend is the main near-term risk signal.","Counter-considerations: upside risk would be a temporary slowdown in terminations or more retroactive awards, which would land above the interval if June prints above 7,017 thousand. Downside risk would be a processing cleanup or unusually heavy exits, which would land below the interval if the first print is below 7,002 thousand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and policy mechanisms: level is 7,029 thousand in May; momentum is about -19 thousand per month; no public first-print evidence points to a June-only administrative shock; policy and demographic mechanisms still favor gradual exits, conversions, deaths, and lower inflow keeping the roll drifting down.","Prior/update/interval: May-level persistence plus recent mean monthly change prior on the Dec 2025-May 2026 official sample gives mean change = (-27 - 18 - 11 - 20 - 21) / 5 = -19.4 thousand, so point = 7,029 - 19.4 = 7,009.6, rounded to 7,010. For the 80% interval, sample sigma from successive changes = 5.77 thousand, so half-width = 1.28*sigma = 1.28*5.77 = 7.39 thousand; 7,009.6 +/- 7.39 gives 7,002.2 to 7,017.0, rounded to 7,002-7,017. The five-change local-volatility window is intentional for this one-month-ahead first-print forecast because the roll is smooth and recent administrative trend is the main near-term risk signal."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: May-level persistence plus recent mean monthly change prior on the Dec 2025-May 2026 official sample gives mean change = (-27 - 18 - 11 - 20 - 21) / 5 = -19.4 thousand, so point = 7,029 - 19.4 = 7,009.6, rounded to 7,010. For the 80% interval, sample sigma from successive changes = 5.77 thousand, so half-width = 1.28*sigma = 1.28*5.77 = 7.39 thousand; 7,009.6 +/- 7.39 gives 7,002.2 to 7,017.0, rounded to 7,002-7,017. The five-change local-volatility window is intentional for this one-month-ahead first-print forecast because the roll is smooth and recent administrative trend is the main near-term risk signal.","Counter-considerations: upside risk would be a temporary slowdown in terminations or more retroactive awards, which would land above the interval if June prints above 7,017 thousand. Downside risk would be a processing cleanup or unusually heavy exits, which would land below the interval if the first print is below 7,002 thousand."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Level, momentum, one-off, and policy mechanisms: level is 7,029 thousand in May; momentum is about -19 thousand per month; no public first-print evidence points to a June-only administrative shock; policy and demographic mechanisms still favor gradual exits, conversions, deaths, and lower inflow keeping the roll drifting down.","Prior/update/interval: May-level persistence plus recent mean monthly change prior on the Dec 2025-May 2026 official sample gives mean change = (-27 - 18 - 11 - 20 - 21) / 5 = -19.4 thousand, so point = 7,029 - 19.4 = 7,009.6, rounded to 7,010. For the 80% interval, sample sigma from successive changes = 5.77 thousand, so half-width = 1.28*sigma = 1.28*5.77 = 7.39 thousand; 7,009.6 +/- 7.39 gives 7,002.2 to 7,017.0, rounded to 7,002-7,017. The five-change local-volatility window is intentional for this one-month-ahead first-print forecast because the roll is smooth and recent administrative trend is the main near-term risk signal."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: ssdi-disabled-worker-beneficiaries-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-31\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.ssa-hearings-average-processing-time-june-2026.2026-07-08T21-00-11Z.feecdfcdcb1ab29c","runId":"run.ssa-hearings-average-processing-time-june-2026.2026-07-08T21-00-11Z.feecdfcdcb1ab29c","predictionId":"ssa-hearings-average-processing-time-june-2026","specId":"spec.ssa-hearings-average-processing-time-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 8 historical point(s) and explicit outside-view language.","evidence":["Tool result: Fetched SSA Publishing Schedule text saying anticipated release dates are based on current production plans and may be updated for production or data issues; fetched archive index showing FY2026 Hearing Office Workload Data archived through April 2026 while current pages show May 2026 through 05/29/2026 with national average processing time 322 days. No exact OHO June placeholder was listed, so I keep the canonical ledger resolutionDate 2026-07-31 as the target by-date.","Base rate/reference class: the reference class is the same SSA OHO FY2026 fiscal-year-to-date average-processing-time series. The level rose from 279 days in October 2025 to 322 days in May 2026, a 43-day increase over 7 monthly updates, while the latest two increments were both +4 days."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this targets SSA Office of Hearings Operations Hearing Office Workload Data for FY2026 cumulative through June 2026, specifically DSPN_AVGPT average processing time in calendar days from hearing request date to disposition date. The variant is unadjusted administrative hearing-office workload data, not average wait time until hearing held and not a later archive revision.","Tool call: Opened the SSA FY2026 archive index and current public pages to assemble the same-variant official reference class."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["SSA OHO hearings average processing time, June 2026 first print","Tool call: Opened the SSA Publishing Schedule and Hearings and Appeals archive index to verify release timing treatment for the ledger resolution date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 8, distribution present, forecast step count 1.","evidence":["Level, momentum, one-off, and policy split: the level anchor is May's 322 days; momentum remains upward because cumulative FY-to-date dispositions are still clearing older requests; one-off risk is mainly hearing-office mix and transferred workloads; I found no official public source in this run indicating a June-only policy change that would mechanically break trend.","Prior/update/interval: persistence-plus-damped-trend prior uses May 2026 at 322 days and the recent official sample of successive changes +9, +8, +6, +7, +5, +4, +4 days. The mean change is 6.14 days, but the latest 2 changes average 4.0 days, so the damped-trend component updates May by +4 days for a 326-day point. Interval method uses realized dispersion of successive changes; sigma = 1.95 days, so 1.28*sigma = 2.50 days. I widen to a 4-day half-width because a national disposition-weighted aggregate can move if June completions disproportionately clear older or newer cases, giving final implied bounds of 322 to 330 days after integer-day rounding."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and policy split: the level anchor is May's 322 days; momentum remains upward because cumulative FY-to-date dispositions are still clearing older requests; one-off risk is mainly hearing-office mix and transferred workloads; I found no official public source in this run indicating a June-only policy change that would mechanically break trend.","Prior/update/interval: persistence-plus-damped-trend prior uses May 2026 at 322 days and the recent official sample of successive changes +9, +8, +6, +7, +5, +4, +4 days. The mean change is 6.14 days, but the latest 2 changes average 4.0 days, so the damped-trend component updates May by +4 days for a 326-day point. Interval method uses realized dispersion of successive changes; sigma = 1.95 days, so 1.28*sigma = 2.50 days. I widen to a 4-day half-width because a national disposition-weighted aggregate can move if June completions disproportionately clear older or newer cases, giving final implied bounds of 322 to 330 days after integer-day rounding."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, one-off, and policy split: the level anchor is May's 322 days; momentum remains upward because cumulative FY-to-date dispositions are still clearing older requests; one-off risk is mainly hearing-office mix and transferred workloads; I found no official public source in this run indicating a June-only policy change that would mechanically break trend.","Prior/update/interval: persistence-plus-damped-trend prior uses May 2026 at 322 days and the recent official sample of successive changes +9, +8, +6, +7, +5, +4, +4 days. The mean change is 6.14 days, but the latest 2 changes average 4.0 days, so the damped-trend component updates May by +4 days for a 326-day point. Interval method uses realized dispersion of successive changes; sigma = 1.95 days, so 1.28*sigma = 2.50 days. I widen to a 4-day half-width because a national disposition-weighted aggregate can move if June completions disproportionately clear older or newer cases, giving final implied bounds of 322 to 330 days after integer-day rounding."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Fetched same-variant FY2026 cumulative average processing time points: Oct 2025 279 days, Nov 2025 288, Dec 2025 296, Jan 2026 302, Feb 2026 309, Mar 2026 314, Apr 2026 318, May 2026 322.","Prior/update/interval: persistence-plus-damped-trend prior uses May 2026 at 322 days and the recent official sample of successive changes +9, +8, +6, +7, +5, +4, +4 days. The mean change is 6.14 days, but the latest 2 changes average 4.0 days, so the damped-trend component updates May by +4 days for a 326-day point. Interval method uses realized dispersion of successive changes; sigma = 1.95 days, so 1.28*sigma = 2.50 days. I widen to a 4-day half-width because a national disposition-weighted aggregate can move if June completions disproportionately clear older or newer cases, giving final implied bounds of 322 to 330 days after integer-day rounding."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: ssa-hearings-average-processing-time-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-31\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-lfpr-55-plus-july-2026.2026-07-08T20-24-14Z.4d08fde90bdfd854","runId":"run.us-lfpr-55-plus-july-2026.2026-07-08T20-24-14Z.4d08fde90bdfd854","predictionId":"us-lfpr-55-plus-july-2026","specId":"spec.us-lfpr-55-plus-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: for a monthly rounded participation-rate series, the best short-horizon reference class is recent same-series one-month changes in the same seasonally adjusted variant. The fetched 55+ path fell 0.2 percentage point from Feb to Jun but was unchanged at 37.1 in Apr, May, and Jun, so persistence at 37.1 is the base rate anchor.","Prior/update/interval: persistence prior using recent BLS/FRED same-series history Feb-Jun 2026 = 37.3, 37.2, 37.1, 37.1, 37.1. Successive changes are -0.1, -0.1, 0.0, 0.0, so sample sigma = 0.058 percentage point from the four fetched pre-release monthly changes; a longer window would be preferable, but this fast run used the directly fetched current-window history and widened to display precision. Level component = 37.1; momentum component = -0.05 from the Feb-Jun drift but muted because the last three readings were flat; one-off June aggregate LFPR weakness adds small downside risk of -0.02; policy-mechanism effect = 0.00. Final point rounds to 37.1. 80% half-width is roughly 1.28*sigma = 1.28*0.058 = 0.074, widened to 0.10 after rounding outward to BLS 0.1-point display precision, giving 37.0 to 37.2."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Forecast for BLS CPS 55+ labor force participation, July 2026 first print","Framing and exact resolver: this is the seasonally adjusted CPS household-survey series LNS11324230, Labor Force Participation Rate - 55 Yrs. & over, in percent. Resolution is the first BLS July 2026 Employment Situation print, not a later revised vintage."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast for BLS CPS 55+ labor force participation, July 2026 first print","Framing and exact resolver: this is the seasonally adjusted CPS household-survey series LNS11324230, Labor Force Participation Rate - 55 Yrs. & over, in percent. Resolution is the first BLS July 2026 Employment Situation print, not a later revised vintage."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.2, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior using recent BLS/FRED same-series history Feb-Jun 2026 = 37.3, 37.2, 37.1, 37.1, 37.1. Successive changes are -0.1, -0.1, 0.0, 0.0, so sample sigma = 0.058 percentage point from the four fetched pre-release monthly changes; a longer window would be preferable, but this fast run used the directly fetched current-window history and widened to display precision. Level component = 37.1; momentum component = -0.05 from the Feb-Jun drift but muted because the last three readings were flat; one-off June aggregate LFPR weakness adds small downside risk of -0.02; policy-mechanism effect = 0.00. Final point rounds to 37.1. 80% half-width is roughly 1.28*sigma = 1.28*0.058 = 0.074, widened to 0.10 after rounding outward to BLS 0.1-point display precision, giving 37.0 to 37.2.","Upside risk: a rebound in older workers re-entering after the June labor-force drop, or sampling reversal after three flat 37.1 readings, would land above 37.2. Downside risk: another retirement-heavy labor-force exit like June's aggregate participation decline would land below 37.0; outside the interval would require a rounded monthly move of at least 0.2 percentage point from June."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior using recent BLS/FRED same-series history Feb-Jun 2026 = 37.3, 37.2, 37.1, 37.1, 37.1. Successive changes are -0.1, -0.1, 0.0, 0.0, so sample sigma = 0.058 percentage point from the four fetched pre-release monthly changes; a longer window would be preferable, but this fast run used the directly fetched current-window history and widened to display precision. Level component = 37.1; momentum component = -0.05 from the Feb-Jun drift but muted because the last three readings were flat; one-off June aggregate LFPR weakness adds small downside risk of -0.02; policy-mechanism effect = 0.00. Final point rounds to 37.1. 80% half-width is roughly 1.28*sigma = 1.28*0.058 = 0.074, widened to 0.10 after rounding outward to BLS 0.1-point display precision, giving 37.0 to 37.2."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Reference class and base rate: for a monthly rounded participation-rate series, the best short-horizon reference class is recent same-series one-month changes in the same seasonally adjusted variant. The fetched 55+ path fell 0.2 percentage point from Feb to Jun but was unchanged at 37.1 in Apr, May, and Jun, so persistence at 37.1 is the base rate anchor.","Prior/update/interval: persistence prior using recent BLS/FRED same-series history Feb-Jun 2026 = 37.3, 37.2, 37.1, 37.1, 37.1. Successive changes are -0.1, -0.1, 0.0, 0.0, so sample sigma = 0.058 percentage point from the four fetched pre-release monthly changes; a longer window would be preferable, but this fast run used the directly fetched current-window history and widened to display precision. Level component = 37.1; momentum component = -0.05 from the Feb-Jun drift but muted because the last three readings were flat; one-off June aggregate LFPR weakness adds small downside risk of -0.02; policy-mechanism effect = 0.00. Final point rounds to 37.1. 80% half-width is roughly 1.28*sigma = 1.28*0.058 = 0.074, widened to 0.10 after rounding outward to BLS 0.1-point display precision, giving 37.0 to 37.2."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for BLS CPS 55+ labor force participation, July 2026 first print","Tool result: BLS reported June 2026 total nonfarm payroll employment +57,000, unemployment rate 4.2 percent, aggregate labor force participation rate 61.5 percent, and aggregate participation down 0.3 percentage point in June."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-lfpr-55-plus-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-07\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-disability-employment-population-ratio-july-2026.2026-07-08T20-27-06Z.9b1e0af35c4aac69","runId":"run.us-disability-employment-population-ratio-july-2026.2026-07-08T20-27-06Z.9b1e0af35c4aac69","predictionId":"us-disability-employment-population-ratio-july-2026","specId":"spec.us-disability-employment-population-ratio-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: for this not seasonally adjusted level series, persistence from the latest official print is the base rate, so the starting prior is Jun 2026 at 21.8. The July target uses the same variant as the anchors: total people with a disability, age 16 years and over, not seasonally adjusted, percent.","Prior/update/interval: persistence prior is Jun 2026 at 21.8. Historical sample is monthly LNU02374597 values from Jan 2024 through Jun 2026, excluding the missing Oct 2025 observation; successive-change dispersion gives sigma = 0.528 percentage point, so 1.28*sigma = 0.676. Adjustment components are -0.1 point for recent 2026 downward level drift, -0.1 point for typical Jun-to-Jul NSA softness, and 0.0 point for mixed labor-market context, implying 21.8 - 0.2 = 21.6. The 80% interval is 21.6 +/- 0.7, rounded to [20.9, 22.3]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this forecast targets BLS CPS series LNU02374597, Employment-Population Ratio - With a Disability, 16 Years and over, not seasonally adjusted, as printed in Employment Situation Table A-6 for July 2026. FRED is used only as a public history mirror; BLS Table A-6 is the resolution source.","Tool call: BLS release schedule lookup for Employment Situation July 2026 reference month"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: BLS release schedule lookup for Employment Situation July 2026 reference month","Tool result: BLS schedule lists July 2026 Employment Situation release date as Aug. 07, 2026 at 08:30 AM."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.4, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is Jun 2026 at 21.8. Historical sample is monthly LNU02374597 values from Jan 2024 through Jun 2026, excluding the missing Oct 2025 observation; successive-change dispersion gives sigma = 0.528 percentage point, so 1.28*sigma = 0.676. Adjustment components are -0.1 point for recent 2026 downward level drift, -0.1 point for typical Jun-to-Jul NSA softness, and 0.0 point for mixed labor-market context, implying 21.8 - 0.2 = 21.6. The 80% interval is 21.6 +/- 0.7, rounded to [20.9, 22.3].","Counter-consideration: upside risk is a rebound in disability labor-force attachment or CPS sampling that would land above the interval, roughly 22.4 or higher; downside risk is another broad participation drop or subgroup sampling swing that would land below the interval, roughly 20.8 or lower."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Momentum: the series moved 22.6, 22.4, 22.2, 21.8, 21.7, 21.8 from Jan through Jun 2026, so the latest uptick is small relative to the earlier slide and does not fully erase the weaker level.","Review disposition: accepted the resolver clarification for the rolling Table A-6 URL and first-print artifact capture, moved the persistence base rate before update evidence, and stated that FRED is only a history mirror. Rejected adding new quantified Jun-to-Jul history because the final submission is limited to evidence already in the draft."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-consideration: upside risk is a rebound in disability labor-force attachment or CPS sampling that would land above the interval, roughly 22.4 or higher; downside risk is another broad participation drop or subgroup sampling swing that would land below the interval, roughly 20.8 or lower."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Framing and exact resolver: this forecast targets BLS CPS series LNU02374597, Employment-Population Ratio - With a Disability, 16 Years and over, not seasonally adjusted, as printed in Employment Situation Table A-6 for July 2026. FRED is used only as a public history mirror; BLS Table A-6 is the resolution source.","Tool result: June 2026 nonfarm payrolls were +57,000, unemployment rate was 4.2 percent, labor force participation decreased 0.3 percentage point to 61.5 percent, and overall employment-population ratio edged down 0.2 percentage point to 59.0 percent."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-disability-employment-population-ratio-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-07\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.spm-senior-poverty-2025.2026-07-08T20-30-10Z.a3bff5725cd9b7a8","runId":"run.spm-senior-poverty-2025.2026-07-08T20-30-10Z.a3bff5725cd9b7a8","predictionId":"spm-senior-poverty-2025","specId":"spec.spm-senior-poverty-2025","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the relevant official-source reference class is recent Table B-2 senior SPM first prints. The post-pandemic-transfer senior series was roughly 14.1 in 2022, 14.2 in 2023, and 15.0 in 2024, so the base rate is near 14.4 to 15.0 rather than the all-person 12.9 percent level.","Prior/update/interval: persistence prior = latest same-variant senior SPM level 15.0 percent; historical sample = 2021-2024 senior SPM first-print rates 10.7, 14.1, 14.2, 15.0; adjustment components = +0.2 for continued threshold/medical-expense pressure, +0.1 for age-specific 2024 upward momentum, and 0.0 for no assumed new broad anti-poverty transfer shock, giving point 15.0 + 0.2 + 0.1 = 15.3. Interval method uses sample standard deviation of successive changes: 2021-2022 = +3.4, 2022-2023 = +0.1, 2023-2024 = +0.8 percentage points; sigma = 1.74, half-width = 1.28*sigma = 2.23, so 80% interval = 15.3 +/- 2.23 = [13.1, 17.5] after one-decimal rounding. This volatility estimate uses only 3 annual changes, so the interval is a judgmental 80% interval anchored in realized dispersion rather than a stable time-series estimate."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this targets the Census Bureau first print for calendar-year 2025 people age 65 years and older under the Supplemental Poverty Measure. This is not the official poverty measure: SPM resources include taxes, refundable credits, and noncash transfers, and subtract necessary expenses including medical out-of-pocket and work expenses, with thresholds adjusted for housing tenure and geography.","Tool call: Checked the Census Bureau Event Calendar and annual income, poverty, and health-insurance release context for the calendar-year 2025 first print."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this targets the Census Bureau first print for calendar-year 2025 people age 65 years and older under the Supplemental Poverty Measure. This is not the official poverty measure: SPM resources include taxes, refundable credits, and noncash transfers, and subtract necessary expenses including medical out-of-pocket and work expenses, with thresholds adjusted for housing tenure and geography.","Tool call: Checked the Census Bureau Event Calendar and annual income, poverty, and health-insurance release context for the calendar-year 2025 first print."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.4, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = latest same-variant senior SPM level 15.0 percent; historical sample = 2021-2024 senior SPM first-print rates 10.7, 14.1, 14.2, 15.0; adjustment components = +0.2 for continued threshold/medical-expense pressure, +0.1 for age-specific 2024 upward momentum, and 0.0 for no assumed new broad anti-poverty transfer shock, giving point 15.0 + 0.2 + 0.1 = 15.3. Interval method uses sample standard deviation of successive changes: 2021-2022 = +3.4, 2022-2023 = +0.1, 2023-2024 = +0.8 percentage points; sigma = 1.74, half-width = 1.28*sigma = 2.23, so 80% interval = 15.3 +/- 2.23 = [13.1, 17.5] after one-decimal rounding. This volatility estimate uses only 3 annual changes, so the interval is a judgmental 80% interval anchored in realized dispersion rather than a stable time-series estimate.","Counter-consideration: downside risk is that the 2024 senior increase was mostly a one-year threshold/expense adjustment and 2025 Social Security and retirement-income gains offset medical costs, which would land near 13.1 or below the interval. Upside risk is another large SPM threshold or medical-expense shock, weaker survey income for older adults, or reduced transfer effectiveness, which would land above the interval near 17.6 or higher. The main outside the interval scenario is a large methodological or threshold shock in Table B-2 rather than ordinary income momentum."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, and policy mechanism: the 2024 jump for seniors looks tied to SPM threshold, housing, and medical-expense mechanics rather than a broad all-person poverty surge. For 2025, Social Security COLA and continued older-adult benefit receipt support resources, but Medicare premiums, medical out-of-pocket costs, and housing-adjusted thresholds keep senior SPM above official-plus poverty and make a full reversal unlikely.","Prior/update/interval: persistence prior = latest same-variant senior SPM level 15.0 percent; historical sample = 2021-2024 senior SPM first-print rates 10.7, 14.1, 14.2, 15.0; adjustment components = +0.2 for continued threshold/medical-expense pressure, +0.1 for age-specific 2024 upward momentum, and 0.0 for no assumed new broad anti-poverty transfer shock, giving point 15.0 + 0.2 + 0.1 = 15.3. Interval method uses sample standard deviation of successive changes: 2021-2022 = +3.4, 2022-2023 = +0.1, 2023-2024 = +0.8 percentage points; sigma = 1.74, half-width = 1.28*sigma = 2.23, so 80% interval = 15.3 +/- 2.23 = [13.1, 17.5] after one-decimal rounding. This volatility estimate uses only 3 annual changes, so the interval is a judgmental 80% interval anchored in realized dispersion rather than a stable time-series estimate."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, and policy mechanism: the 2024 jump for seniors looks tied to SPM threshold, housing, and medical-expense mechanics rather than a broad all-person poverty surge. For 2025, Social Security COLA and continued older-adult benefit receipt support resources, but Medicare premiums, medical out-of-pocket costs, and housing-adjusted thresholds keep senior SPM above official-plus poverty and make a full reversal unlikely.","Counter-consideration: downside risk is that the 2024 senior increase was mostly a one-year threshold/expense adjustment and 2025 Social Security and retirement-income gains offset medical costs, which would land near 13.1 or below the interval. Upside risk is another large SPM threshold or medical-expense shock, weaker survey income for older adults, or reduced transfer effectiveness, which would land above the interval near 17.6 or higher. The main outside the interval scenario is a large methodological or threshold shock in Table B-2 rather than ordinary income momentum."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for 2025 senior Supplemental Poverty Measure poverty rate","Prior/update/interval: persistence prior = latest same-variant senior SPM level 15.0 percent; historical sample = 2021-2024 senior SPM first-print rates 10.7, 14.1, 14.2, 15.0; adjustment components = +0.2 for continued threshold/medical-expense pressure, +0.1 for age-specific 2024 upward momentum, and 0.0 for no assumed new broad anti-poverty transfer shock, giving point 15.0 + 0.2 + 0.1 = 15.3. Interval method uses sample standard deviation of successive changes: 2021-2022 = +3.4, 2022-2023 = +0.1, 2023-2024 = +0.8 percentage points; sigma = 1.74, half-width = 1.28*sigma = 2.23, so 80% interval = 15.3 +/- 2.23 = [13.1, 17.5] after one-decimal rounding. This volatility estimate uses only 3 annual changes, so the interval is a judgmental 80% interval anchored in realized dispersion rather than a stable time-series estimate."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: spm-senior-poverty-2025\nrunLabel: Headline\nresolutionDate: 2026-09-08\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.social-security-cola-2027.2026-07-08T20-34-22Z.0d407aa898b122ed","runId":"run.social-security-cola-2027.2026-07-08T20-34-22Z.0d407aa898b122ed","predictionId":"social-security-cola-2027","specId":"spec.social-security-cola-2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool call: Opened SSA latest Cost-of-Living Adjustment page to verify formula, latest print, rounding precision, and the 2025 Q3 CPI-W base for the next COLA calculation.","Tool result: Fetched latest COLA = 2.8 percent; SSA states the Q3 2025 CPI-W average = 317.265, Q3 2024 base average = 308.729, July 2025 CPI-W = 316.349, August 2025 = 317.306, September 2025 = 318.139, and the published calculation was (317.265 - 308.729) / 308.729 x 100 = 2.8 percent."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this forecasts SSA's first official annual COLA for Social Security benefits payable in January 2027, not CPI-U, CPI-E, SSI dollars, taxable maximum, or average benefit dollars. The resolving CPI variant is CPI-W, U.S. city average, all items, series code CWUR0000SA0.","Tool call: Opened SSA COLA history page for the recent official reference class of annual COLA outcomes."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this forecasts SSA's first official annual COLA for Social Security benefits payable in January 2027, not CPI-U, CPI-E, SSI dollars, taxable maximum, or average benefit dollars. The resolving CPI variant is CPI-W, U.S. city average, all items, series code CWUR0000SA0.","Tool result: Fetched latest COLA = 2.8 percent; SSA states the Q3 2025 CPI-W average = 317.265, Q3 2024 base average = 308.729, July 2025 CPI-W = 316.349, August 2025 = 317.306, September 2025 = 318.139, and the published calculation was (317.265 - 308.729) / 308.729 x 100 = 2.8 percent."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6.2, distribution present, forecast step count 1.","evidence":["Base rate/reference class: the recent SSA COLA sample averages 3.11 percent over 2016-2025, but it is fat-tailed because pandemic and energy shocks produced 5.9 and 8.7 percent outcomes. A plain outside-view prior is around 3.1 percent, with a wide realized-dispersion interval.","Prior/update/interval: model is a 2016-2025 SSA COLA reference-class prior with a May-2026 CPI-W nowcast update; historical sample = [0.3, 2.0, 2.8, 1.6, 1.3, 5.9, 8.7, 3.2, 2.5, 2.8], mean = 3.11, sigma = 2.46 from the values themselves, half-width = 1.28*sigma = 3.14. Adjustment components are level +0.54 from the May CPI-W implied 3.645 percent versus the 3.11 base rate, momentum +0.25 for positive core inflation, one-off energy -0.10 for reversal risk, and policy-mechanism 0.00 because the SSA formula is automatic, giving a 3.8 point. Interval arithmetic: 3.8 - 3.14 = 0.66 and 3.8 + 3.14 = 6.94, rounded to 0.7 to 6.9 percent; this is an approximate normal-reference interval from realized COLA dispersion, not a calibrated backtest."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Opened BLS May 2026 CPI Summary for latest CPI-W and inflation momentum before the Q3 measurement window.","Base rate/reference class: the recent SSA COLA sample averages 3.11 percent over 2016-2025, but it is fat-tailed because pandemic and energy shocks produced 5.9 and 8.7 percent outcomes. A plain outside-view prior is around 3.1 percent, with a wide realized-dispersion interval."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: the recent SSA COLA sample averages 3.11 percent over 2016-2025, but it is fat-tailed because pandemic and energy shocks produced 5.9 and 8.7 percent outcomes. A plain outside-view prior is around 3.1 percent, with a wide realized-dispersion interval.","Prior/update/interval: model is a 2016-2025 SSA COLA reference-class prior with a May-2026 CPI-W nowcast update; historical sample = [0.3, 2.0, 2.8, 1.6, 1.3, 5.9, 8.7, 3.2, 2.5, 2.8], mean = 3.11, sigma = 2.46 from the values themselves, half-width = 1.28*sigma = 3.14. Adjustment components are level +0.54 from the May CPI-W implied 3.645 percent versus the 3.11 base rate, momentum +0.25 for positive core inflation, one-off energy -0.10 for reversal risk, and policy-mechanism 0.00 because the SSA formula is automatic, giving a 3.8 point. Interval arithmetic: 3.8 - 3.14 = 0.66 and 3.8 + 3.14 = 6.94, rounded to 0.7 to 6.9 percent; this is an approximate normal-reference interval from realized COLA dispersion, not a calibrated backtest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for 2027 Social Security COLA","Framing and exact resolver: this forecasts SSA's first official annual COLA for Social Security benefits payable in January 2027, not CPI-U, CPI-E, SSI dollars, taxable maximum, or average benefit dollars. The resolving CPI variant is CPI-W, U.S. city average, all items, series code CWUR0000SA0."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: social-security-cola-2027\nrunLabel: Headline\nresolutionDate: 2026-10-14\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.nursing-home-staffing-hprd-july-2026.2026-07-21T01-37-06Z.a9b578df6e152614","runId":"run.nursing-home-staffing-hprd-july-2026.2026-07-21T01-37-06Z.a9b578df6e152614","predictionId":"nursing-home-staffing-hprd-july-2026","specId":"spec.nursing-home-staffing-hprd-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool result: Fetched CMS-based historical national row: NATION average number of residents per day 80.8 and Reported Total Nurse Staffing Hours per Resident per Day 3.76, published October 10 2023.","Tool call: State US Averages preview and current CMS-based mirror checks"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 6 typed tool call(s), 7 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this target is CMS Provider Data Catalog dataset xcdc-v8bm, State US Averages/NH_StateUSAverages, NATION row, Reported Total Nurse Staffing Hours per Resident per Day. I keep the ledger first-print rule and do not add a same-day correction or revision grace rule.","Tool result: Fetched official dataset metadata: identifier xcdc-v8bm, Last Modified June 1 2026, Released June 24 2026, Planned Update July 29 2026, publisher CMS, and public access level public."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this target is CMS Provider Data Catalog dataset xcdc-v8bm, State US Averages/NH_StateUSAverages, NATION row, Reported Total Nurse Staffing Hours per Resident per Day. I keep the ledger first-print rule and do not add a same-day correction or revision grace rule.","Tool result: Fetched official dataset metadata: identifier xcdc-v8bm, Last Modified June 1 2026, Released June 24 2026, Planned Update July 29 2026, publisher CMS, and public access level public."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.16, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is latest CMS-based national mirror 3.90; historical sample is fetched levels 3.76, 3.79, 3.83737, 3.90. Successive changes are +0.03000, +0.04737, and +0.06263, so sigma = 0.016 for recent change dispersion and 1.28*sigma = 0.021. I add +0.02 for upward momentum into the July quarterly staffing refresh, giving point 3.92. I widen the 80% half-width to 0.08, about 3.8x the mechanical 0.021, because this is an explicit uncertainty interval rather than a robust realized-volatility estimate: the anchor sample is sparse, irregularly spaced, partly rounded or mirrored, and the PBJ-quarter rollover can create a larger first-print step than the limited anchor history implies.","Counter-considerations: upside risk is a clean PBJ quarter, compliance-driven staffing gains, or sample mix improvement that would land above the interval, especially above 4.00. Downside risk is weaker staffing, facility exits, reporting issues, or a methodological change that would land below the interval, especially below 3.84."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior is latest CMS-based national mirror 3.90; historical sample is fetched levels 3.76, 3.79, 3.83737, 3.90. Successive changes are +0.03000, +0.04737, and +0.06263, so sigma = 0.016 for recent change dispersion and 1.28*sigma = 0.021. I add +0.02 for upward momentum into the July quarterly staffing refresh, giving point 3.92. I widen the 80% half-width to 0.08, about 3.8x the mechanical 0.021, because this is an explicit uncertainty interval rather than a robust realized-volatility estimate: the anchor sample is sparse, irregularly spaced, partly rounded or mirrored, and the PBJ-quarter rollover can create a larger first-print step than the limited anchor history implies.","Policy/mechanism effects: CMS minimum-staffing and SNF VBP attention create mild upside pressure, but implementation and reporting responses are gradual, so I treat policy as roughly +0.00 to +0.02 rather than a discrete July level shift."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence prior is latest CMS-based national mirror 3.90; historical sample is fetched levels 3.76, 3.79, 3.83737, 3.90. Successive changes are +0.03000, +0.04737, and +0.06263, so sigma = 0.016 for recent change dispersion and 1.28*sigma = 0.021. I add +0.02 for upward momentum into the July quarterly staffing refresh, giving point 3.92. I widen the 80% half-width to 0.08, about 3.8x the mechanical 0.021, because this is an explicit uncertainty interval rather than a robust realized-volatility estimate: the anchor sample is sparse, irregularly spaced, partly rounded or mirrored, and the PBJ-quarter rollover can create a larger first-print step than the limited anchor history implies.","Policy/mechanism effects: CMS minimum-staffing and SNF VBP attention create mild upside pressure, but implementation and reporting responses are gradual, so I treat policy as roughly +0.00 to +0.02 rather than a discrete July level shift."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["CMS State US Averages staffing HPRD forecast","Prior/update/interval: persistence prior is latest CMS-based national mirror 3.90; historical sample is fetched levels 3.76, 3.79, 3.83737, 3.90. Successive changes are +0.03000, +0.04737, and +0.06263, so sigma = 0.016 for recent change dispersion and 1.28*sigma = 0.021. I add +0.02 for upward momentum into the July quarterly staffing refresh, giving point 3.92. I widen the 80% half-width to 0.08, about 3.8x the mechanical 0.021, because this is an explicit uncertainty interval rather than a robust realized-volatility estimate: the anchor sample is sparse, irregularly spaced, partly rounded or mirrored, and the PBJ-quarter rollover can create a larger first-print step than the limited anchor history implies."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: nursing-home-staffing-hprd-july-2026\nrunLabel: Headline\nresolutionDate: 2026-07-29\ntraceLineCount: 21\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.home-health-services-employment-july-2026.2026-07-21T01-39-25Z.320df19af6801e37","runId":"run.home-health-services-employment-july-2026.2026-07-21T01-39-25Z.320df19af6801e37","predictionId":"home-health-services-employment-july-2026","specId":"spec.home-health-services-employment-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate / reference class: home health care services employment has had persistent positive drift in the recent public CES history. The most relevant base rate is the latest 12 observed month-to-month changes in this same seasonally adjusted series, because the target is a one-month-ahead level forecast and the series has a strong trend; this horizon makes the recent year preferable to a longer sample that would mix older industry regimes.","Prior/update/interval: persistence prior is latest level 1880.8 plus the recent 12-month average change of 8.5; historical sample is Jul 2025-Jun 2026 monthly changes in CES6562160001; adjustment components are -0.5 thousand for June's softer +3.3 reading versus prior +9.5 gains and +0.0 for no identified one-off July policy shock, giving 1880.8 + 8.0 = 1888.8. Interval method uses realized dispersion of those same successive changes: sigma = 5.67, so 1.28*sigma = 7.26; rounded 80% bounds are 1888.8 - 7.3 = 1881.5 and 1888.8 + 7.3 = 1896.1."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Forecast for July 2026 BLS home health care services employment","Framing and exact resolver: this forecast targets BLS Current Employment Statistics series CES6562160001, all employees in home health care services, seasonally adjusted, measured in thousands of persons. The target is the July 2026 first print, not a later revised CES vintage."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this forecast targets BLS Current Employment Statistics series CES6562160001, all employees in home health care services, seasonally adjusted, measured in thousands of persons. The target is the July 2026 first print, not a later revised CES vintage.","Tool call: Checked the BLS Employment Situation release schedule for the July 2026 reference month."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 14.6, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is latest level 1880.8 plus the recent 12-month average change of 8.5; historical sample is Jul 2025-Jun 2026 monthly changes in CES6562160001; adjustment components are -0.5 thousand for June's softer +3.3 reading versus prior +9.5 gains and +0.0 for no identified one-off July policy shock, giving 1880.8 + 8.0 = 1888.8. Interval method uses realized dispersion of those same successive changes: sigma = 5.67, so 1.28*sigma = 7.26; rounded 80% bounds are 1888.8 - 7.3 = 1881.5 and 1888.8 + 7.3 = 1896.1.","Counter-considerations: upside risk is another double-digit July gain like 2025-07's +20.4, which would land above the interval. Downside risk is a hiring pause or reimbursement-driven slowdown near zero change, which would land below the interval. A renewed classification or benchmark-like break outside the interval is possible but not my central case for a first print."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Pulled the 2025-07 through 2026-06 reference-class run of monthly levels for current momentum and dispersion.","Base rate / reference class: home health care services employment has had persistent positive drift in the recent public CES history. The most relevant base rate is the latest 12 observed month-to-month changes in this same seasonally adjusted series, because the target is a one-month-ahead level forecast and the series has a strong trend; this horizon makes the recent year preferable to a longer sample that would mix older industry regimes."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-considerations: upside risk is another double-digit July gain like 2025-07's +20.4, which would land above the interval. Downside risk is a hiring pause or reimbursement-driven slowdown near zero change, which would land below the interval. A renewed classification or benchmark-like break outside the interval is possible but not my central case for a first print."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for July 2026 BLS home health care services employment","Framing and exact resolver: this forecast targets BLS Current Employment Statistics series CES6562160001, all employees in home health care services, seasonally adjusted, measured in thousands of persons. The target is the July 2026 first print, not a later revised CES vintage."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: home-health-services-employment-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-07\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.ssi-recipients-colorado-july-2026.2026-07-21T02-15-08Z.8bd532e978d779e7","runId":"run.ssi-recipients-colorado-july-2026.2026-07-21T02-15-08Z.8bd532e978d779e7","predictionId":"ssi-recipients-colorado-july-2026","specId":"spec.ssi-recipients-colorado-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the reference class is recent first-print SSA SSI Monthly Statistics Colorado total-recipient levels in the same all-federally-administered, non-seasonally-adjusted Table 4 variant. The base rate is a stable mid-66-thousand to high-67-thousand Colorado caseload, with the latest available count 66.417 thousand in June.","Prior/update/interval: persistence prior is June 2026 at 66.417 thousand and is the selected time-series prior; I do not run a separate model candidate because the fetched adjacent monthly sample is short and irregular. Historical sample for dispersion uses fetched same-variant adjacent changes Dec->Jan, Jan->Feb, Apr->May, and May->Jun: -0.116, -0.104, -0.136, and +0.014 thousand. Adjustment components are -0.036 thousand from a light 30% weight on the January-to-June average decline and 70% weight on latest-month persistence, +0.000 for one-off shocks, and +0.000 for identifiable policy mechanism shifts, giving point 66.417 - 0.036 = 66.381 thousand. sigma = sqrt((0.116^2 + 0.104^2 + 0.136^2 + 0.014^2) / 4) = 0.104 thousand. The raw 80% half-width is roughly 1.28*sigma = 1.28*0.104 = 0.133 thousand; I widen to 0.200 thousand, 1.50x the raw half-width, because the fast-run sample is short and skips March. Final implied bounds are 66.381 - 0.200 = 66.181 and 66.381 + 0.200 = 66.581."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 8 source-context item(s), activity log present.","evidence":["Tool call: Used the official December 2025 Table 4 page as the year-turn anchor for Colorado.","Level, momentum, one-off, and policy mechanism: the level anchor is June 2026 at 66.417 thousand. Momentum is negative over the first half of 2026, but May-to-June was nearly flat, so the July update is kept close to persistence. I do not add a one-off shock; eligibility, terminations, aging, deaths, and administrative processing should move the count gradually at monthly frequency."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this is SSA SSI Monthly Statistics Table 4, All Federally Administered Payments, row Colorado, Total column, for July 2026, non-seasonally adjusted and first print. The resolution page should be the stable July 2026 Table 4 URL; Table 4 is the exact variant for the target.","Tool result: Fetched timing evidence: SSA Publishing Schedule lists SSI Monthly Statistics frequency as Monthly; SSA statistics archive lists SSI Monthly Statistics last released June 2026 and next expected July 2026, so the July 2026 data table is expected on month-level timing with by-date 2026-08-31."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.4, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is June 2026 at 66.417 thousand and is the selected time-series prior; I do not run a separate model candidate because the fetched adjacent monthly sample is short and irregular. Historical sample for dispersion uses fetched same-variant adjacent changes Dec->Jan, Jan->Feb, Apr->May, and May->Jun: -0.116, -0.104, -0.136, and +0.014 thousand. Adjustment components are -0.036 thousand from a light 30% weight on the January-to-June average decline and 70% weight on latest-month persistence, +0.000 for one-off shocks, and +0.000 for identifiable policy mechanism shifts, giving point 66.417 - 0.036 = 66.381 thousand. sigma = sqrt((0.116^2 + 0.104^2 + 0.136^2 + 0.014^2) / 4) = 0.104 thousand. The raw 80% half-width is roughly 1.28*sigma = 1.28*0.104 = 0.133 thousand; I widen to 0.200 thousand, 1.50x the raw half-width, because the fast-run sample is short and skips March. Final implied bounds are 66.381 - 0.200 = 66.181 and 66.381 + 0.200 = 66.581.","Counter-considerations: upside risk would be a July administrative rebound or delayed entries in aged recipients, which would land above the interval if Colorado exceeded 66.581 thousand. Downside risk would be unusually heavy terminations, disability-recipient attrition, or returned-check/eligibility cleanup effects reflected before first publication, which would land below the interval if Colorado came in under 66.181 thousand. An outside the interval result would imply a larger processing swing than the recent adjacent-month reference class."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and policy mechanism: the level anchor is June 2026 at 66.417 thousand. Momentum is negative over the first half of 2026, but May-to-June was nearly flat, so the July update is kept close to persistence. I do not add a one-off shock; eligibility, terminations, aging, deaths, and administrative processing should move the count gradually at monthly frequency.","Prior/update/interval: persistence prior is June 2026 at 66.417 thousand and is the selected time-series prior; I do not run a separate model candidate because the fetched adjacent monthly sample is short and irregular. Historical sample for dispersion uses fetched same-variant adjacent changes Dec->Jan, Jan->Feb, Apr->May, and May->Jun: -0.116, -0.104, -0.136, and +0.014 thousand. Adjustment components are -0.036 thousand from a light 30% weight on the January-to-June average decline and 70% weight on latest-month persistence, +0.000 for one-off shocks, and +0.000 for identifiable policy mechanism shifts, giving point 66.417 - 0.036 = 66.381 thousand. sigma = sqrt((0.116^2 + 0.104^2 + 0.136^2 + 0.014^2) / 4) = 0.104 thousand. The raw 80% half-width is roughly 1.28*sigma = 1.28*0.104 = 0.133 thousand; I widen to 0.200 thousand, 1.50x the raw half-width, because the fast-run sample is short and skips March. Final implied bounds are 66.381 - 0.200 = 66.181 and 66.381 + 0.200 = 66.581."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, one-off, and policy mechanism: the level anchor is June 2026 at 66.417 thousand. Momentum is negative over the first half of 2026, but May-to-June was nearly flat, so the July update is kept close to persistence. I do not add a one-off shock; eligibility, terminations, aging, deaths, and administrative processing should move the count gradually at monthly frequency.","Counter-considerations: upside risk would be a July administrative rebound or delayed entries in aged recipients, which would land above the interval if Colorado exceeded 66.581 thousand. Downside risk would be unusually heavy terminations, disability-recipient attrition, or returned-check/eligibility cleanup effects reflected before first publication, which would land below the interval if Colorado came in under 66.181 thousand. An outside the interval result would imply a larger processing swing than the recent adjacent-month reference class."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for Colorado SSI recipients in July 2026","Prior/update/interval: persistence prior is June 2026 at 66.417 thousand and is the selected time-series prior; I do not run a separate model candidate because the fetched adjacent monthly sample is short and irregular. Historical sample for dispersion uses fetched same-variant adjacent changes Dec->Jan, Jan->Feb, Apr->May, and May->Jun: -0.116, -0.104, -0.136, and +0.014 thousand. Adjustment components are -0.036 thousand from a light 30% weight on the January-to-June average decline and 70% weight on latest-month persistence, +0.000 for one-off shocks, and +0.000 for identifiable policy mechanism shifts, giving point 66.417 - 0.036 = 66.381 thousand. sigma = sqrt((0.116^2 + 0.104^2 + 0.136^2 + 0.014^2) / 4) = 0.104 thousand. The raw 80% half-width is roughly 1.28*sigma = 1.28*0.104 = 0.133 thousand; I widen to 0.200 thousand, 1.50x the raw half-width, because the fast-run sample is short and skips March. Final implied bounds are 66.381 - 0.200 = 66.181 and 66.381 + 0.200 = 66.581."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: ssi-recipients-colorado-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-31\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.broadband-subscription-65-plus-2025.2026-07-24T15-00-35Z.c91cd0002b50767e","runId":"run.broadband-subscription-65-plus-2025.2026-07-24T15-00-35Z.c91cd0002b50767e","predictionId":"broadband-subscription-65-plus-2025","specId":"spec.broadband-subscription-65-plus-2025","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the official ACS 1-year same-variant history is 83.1 in 2021, 84.8 in 2022, 86.5 in 2023, and 88.2 in 2024. The 2021-2024 one-year gains were about 1.70, 1.70, and 1.75 percentage points, so the outside-view anchor is continued increase from the 2024 level.","Prior/update/interval: persistence-plus-trend prior uses 2021-2024 ACS 1-year history, latest level 88.236986, successive changes 1.695175, 1.697018, 1.747165, mean change 1.713119. A mechanical trend gives 88.236986+1.713119=89.950105. I subtract 0.15 point for saturation near 90 percent among 65+ households, giving 89.8. Dispersion from successive changes gives sigma = 0.0295, so 1.28*sigma = 0.0378. That realized-change sigma is implausibly narrow because the post-2020 ACS sample has only three smooth gains and excludes structural slowdown risk, so I widen to a 0.9-point half-width, about 24x the mechanical half-width, for an 80% interval of 88.9 to 90.7."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 7 source-context item(s), activity log present.","evidence":["Tool call: Fetch 2021 ACSDT1Y2021.B28005 from data.census.gov keyless table endpoint and read B28005_014E and B28005_017E.","Tool call: Fetch 2022 ACSDT1Y2022.B28005 from data.census.gov keyless table endpoint and read B28005_014E and B28005_017E."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this targets ACSDT1Y2025.B28005 for United States, first public 2025 ACS 1-year Detailed Table B28005 print, using only the 1-year ACS vintage and resolving to 100*B28005_017E/B28005_014E rounded to one decimal percent.","Tool call: Check official Census calendar and ACS release pages for release-date context."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.8, distribution present, forecast step count 1.","evidence":["Framing and exact resolver: this targets ACSDT1Y2025.B28005 for United States, first public 2025 ACS 1-year Detailed Table B28005 print, using only the 1-year ACS vintage and resolving to 100*B28005_017E/B28005_014E rounded to one decimal percent.","Prior/update/interval: persistence-plus-trend prior uses 2021-2024 ACS 1-year history, latest level 88.236986, successive changes 1.695175, 1.697018, 1.747165, mean change 1.713119. A mechanical trend gives 88.236986+1.713119=89.950105. I subtract 0.15 point for saturation near 90 percent among 65+ households, giving 89.8. Dispersion from successive changes gives sigma = 0.0295, so 1.28*sigma = 0.0378. That realized-change sigma is implausibly narrow because the post-2020 ACS sample has only three smooth gains and excludes structural slowdown risk, so I widen to a 0.9-point half-width, about 24x the mechanical half-width, for an 80% interval of 88.9 to 90.7."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence-plus-trend prior uses 2021-2024 ACS 1-year history, latest level 88.236986, successive changes 1.695175, 1.697018, 1.747165, mean change 1.713119. A mechanical trend gives 88.236986+1.713119=89.950105. I subtract 0.15 point for saturation near 90 percent among 65+ households, giving 89.8. Dispersion from successive changes gives sigma = 0.0295, so 1.28*sigma = 0.0378. That realized-change sigma is implausibly narrow because the post-2020 ACS sample has only three smooth gains and excludes structural slowdown risk, so I widen to a 0.9-point half-width, about 24x the mechanical half-width, for an 80% interval of 88.9 to 90.7.","Upside risk: faster cohort replacement, continued device adoption, or Census composition shifts toward already-connected 65+ households could land above the interval. Downside risk: saturation around non-adopter households, affordability pressure, or a survey-composition reversal could land below the interval. Outside the interval would mainly require a break from the smooth 2021-2024 trend, not ordinary sampling noise."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence-plus-trend prior uses 2021-2024 ACS 1-year history, latest level 88.236986, successive changes 1.695175, 1.697018, 1.747165, mean change 1.713119. A mechanical trend gives 88.236986+1.713119=89.950105. I subtract 0.15 point for saturation near 90 percent among 65+ households, giving 89.8. Dispersion from successive changes gives sigma = 0.0295, so 1.28*sigma = 0.0378. That realized-change sigma is implausibly narrow because the post-2020 ACS sample has only three smooth gains and excludes structural slowdown risk, so I widen to a 0.9-point half-width, about 24x the mechanical half-width, for an 80% interval of 88.9 to 90.7.","Upside risk: faster cohort replacement, continued device adoption, or Census composition shifts toward already-connected 65+ households could land above the interval. Downside risk: saturation around non-adopter households, affordability pressure, or a survey-composition reversal could land below the interval. Outside the interval would mainly require a break from the smooth 2021-2024 trend, not ordinary sampling noise."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast 2025 ACS 65+ Broadband Subscription Share","Tool call: Fetch 2021 ACSDT1Y2021.B28005 from data.census.gov keyless table endpoint and read B28005_014E and B28005_017E."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: broadband-subscription-65-plus-2025\nrunLabel: Headline\nresolutionDate: 2026-09-10\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.retired-worker-awards-claimed-at-62-share-2025.2026-07-21T02-07-08Z.fefe3d5275bfb77f","runId":"run.retired-worker-awards-claimed-at-62-share-2025.2026-07-21T02-07-08Z.fefe3d5275bfb77f","predictionId":"retired-worker-awards-claimed-at-62-share-2025","specId":"spec.retired-worker-awards-claimed-at-62-share-2025","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool call: Inspect SSA Annual Statistical Supplement 2025 Table 6.B5 recent same-table history for reference-class base rate","Tool call: Inspect SSA Annual Statistical Supplement 2024 Table 6.B5 for an independent historical cross-check"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Tool result: Fetched SSA publishing schedule: Annual Statistical Supplement anticipated next release by June 2026-February 2027, with 2026 sections released as statistics become available and expected completion by February 28, 2027.","Level, momentum, one-off, and policy mechanism: level is anchored at 22.6 percent in 2024. Momentum is modestly negative because age-62 claiming has moved down for three straight pre-target observations. One-off effects are limited because the measure is annual administrative award action rather than a small survey. The policy mechanism is weaker than earlier FRA phase-in years because the FRA is already 67 for newly age-62 cohorts, but delayed-claiming norms and the early-claiming penalty still point slightly below 2024."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: Inspect SSA publishing schedule for release timing","Tool result: Fetched SSA publishing schedule: Annual Statistical Supplement anticipated next release by June 2026-February 2027, with 2026 sections released as statistics become available and expected completion by February 28, 2027."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.2, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is the 2024 all-sexes Table 6.B5 value of 22.6. Historical sample for the update is the pre-target 2021-2024 trend, with successive all-sexes changes of +0.5, -1.4, -0.5, and -0.6 percentage points; I apply a conservative -0.4 point drift update rather than the full recent average because the FRA phase-in shock is mostly complete, giving 22.2. For uncertainty, sigma = sqrt((0.5^2 + 1.4^2 + 0.5^2 + 0.6^2) / 4) = 0.84 percentage points. The 80% half-width is roughly 1.28*sigma = 1.28*0.84 = 1.08, so point 22.2 gives bounds 22.2 - 1.1 = 21.1 and 22.2 + 1.1 = 23.3 after one-decimal rounding.","Counter-considerations: upside risk is a liquidity-driven rebound in age-62 claiming or administrative award-action timing that would land above the interval if the all-sexes share exceeded 23.3 percent. Downside risk is a stronger delayed-retirement response or high older-worker employment that would land below the interval if the share fell under 21.1 percent. An outside the interval result would most likely reflect a structural claiming shift or a table-definition/first-print issue rather than normal year-to-year noise."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate/reference class: the same Table 6.B5 all-sexes age-62 share was 24.6 in 2020, 25.1 in 2021, 23.7 in 2022, 23.2 in 2023, and 22.6 in 2024. That pre-target reference class starts the forecast in the low 20s, with downward momentum after 2021.","Level, momentum, one-off, and policy mechanism: level is anchored at 22.6 percent in 2024. Momentum is modestly negative because age-62 claiming has moved down for three straight pre-target observations. One-off effects are limited because the measure is annual administrative award action rather than a small survey. The policy mechanism is weaker than earlier FRA phase-in years because the FRA is already 67 for newly age-62 cohorts, but delayed-claiming norms and the early-claiming penalty still point slightly below 2024."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Framing and exact resolver: the target is SSA Annual Statistical Supplement Table 6.B5, year of award action 2025, percentage distribution by age for retired-worker awardees. The table reports men and women separately, so the all-sexes target is the weighted average from the Table 6.B5 number-thousands and age-62 percent columns. The forecast evidence below excludes the 2025 target-year print.","Level, momentum, one-off, and policy mechanism: level is anchored at 22.6 percent in 2024. Momentum is modestly negative because age-62 claiming has moved down for three straight pre-target observations. One-off effects are limited because the measure is annual administrative award action rather than a small survey. The policy mechanism is weaker than earlier FRA phase-in years because the FRA is already 67 for newly age-62 cohorts, but delayed-claiming norms and the early-claiming penalty still point slightly below 2024."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for 2025 SSA Retired-Worker Awards Claimed at Age 62","Framing and exact resolver: the target is SSA Annual Statistical Supplement Table 6.B5, year of award action 2025, percentage distribution by age for retired-worker awardees. The table reports men and women separately, so the all-sexes target is the weighted average from the Table 6.B5 number-thousands and age-62 percent columns. The forecast evidence below excludes the 2025 target-year print."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: retired-worker-awards-claimed-at-62-share-2025\nrunLabel: Headline\nresolutionDate: 2027-02-28\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.va-pension-aid-attendance-recipients-fy2026.2026-07-21T02-10-52Z.62c9777e56c5e7dd","runId":"run.va-pension-aid-attendance-recipients-fy2026.2026-07-21T02-10-52Z.62c9777e56c5e7dd","predictionId":"va-pension-aid-attendance-recipients-fy2026","specId":"spec.va-pension-aid-attendance-recipients-fy2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: Inspect archived FY2022 Annual Benefits Report Pension table for same series and reference-class baseline","Base rate/reference class: the recent reference class is the same VBA ABR all-Veterans Pension A&A row. It shows a declining level from 64.277 thousand in FY2022 to 50.730 thousand in FY2025, even as the A&A share rose from 36.9% to 41.2% because the overall means-tested pension roll shrank faster than the high-care-need subset."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 7 source-context item(s), activity log present.","evidence":["Tool result: Fetched official archive listing with 2024, 2023, and 2022 VBA Annual Benefits Reports; data.gov metadata says the current annual report is usually updated by the end of the first quarter of the following calendar year, while the current FY2025 official page shows 2025 ABR last updated May 12, 2026.","Prior/update/interval: persistence prior is FY2025 level 50.730 thousand. Historical sample is same-series FY2022 64.277, FY2023 about 59.8, FY2024 about 55.1, FY2025 50.730, giving successive changes about -4.477, -4.700, and -4.370 thousand. sigma = sqrt((4.477^2 + 4.700^2 + 4.370^2) / 3) = 4.52 thousand, used here as a conservative annual-step uncertainty floor from recent same-series declines rather than a residual-volatility estimate around the fitted trend. The trend update applies another -4.3 thousand attrition step, plus 0.0 thousand one-off and policy adjustment, yielding point 46.4. The 80% half-width is about 1.28*sigma = 1.28*4.52 = 5.79 thousand, so bounds are 46.4 - 5.8 = 40.6 and 46.4 + 5.8 = 52.2."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Tool result: Fetched FY2025 release context: current ABR page says VBA Annual Benefits Report Fiscal Year 2025, updated May 2026, and the page was last updated May 12, 2026; the FY2025 Pension and Fiduciary PDF says data as of 09/30/2025.","Tool call: Inspect VA archive and data.gov metadata for ABR release mechanics"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 11.6, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is FY2025 level 50.730 thousand. Historical sample is same-series FY2022 64.277, FY2023 about 59.8, FY2024 about 55.1, FY2025 50.730, giving successive changes about -4.477, -4.700, and -4.370 thousand. sigma = sqrt((4.477^2 + 4.700^2 + 4.370^2) / 3) = 4.52 thousand, used here as a conservative annual-step uncertainty floor from recent same-series declines rather than a residual-volatility estimate around the fitted trend. The trend update applies another -4.3 thousand attrition step, plus 0.0 thousand one-off and policy adjustment, yielding point 46.4. The 80% half-width is about 1.28*sigma = 1.28*4.52 = 5.79 thousand, so bounds are 46.4 - 5.8 = 40.6 and 46.4 + 5.8 = 52.2.","Counter-considerations: upside risk is stronger claim take-up or MAPR-driven eligibility retention among older Vietnam-era Veterans, which would land above the interval if FY2026 remains above 52.2 thousand. Downside risk is accelerated mortality, nursing-home transitions, or income and asset screening attrition, which would land below the interval if the first print is under 40.6 thousand. An outside the interval result would likely mean either a reporting-definition change or a much sharper break in pension-roll attrition than the recent ABR reference class."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate/reference class: the recent reference class is the same VBA ABR all-Veterans Pension A&A row. It shows a declining level from 64.277 thousand in FY2022 to 50.730 thousand in FY2025, even as the A&A share rose from 36.9% to 41.2% because the overall means-tested pension roll shrank faster than the high-care-need subset.","Level, momentum, one-off, and policy mechanisms: level starts from 50.730 thousand at FY2025 first print. Momentum is negative because the pension rolls are dominated by older wartime cohorts and attrition is large. The offset is that A&A eligibility is concentrated among older and more disabled Veterans, so the row should decline more slowly than basic pension-only rolls. One-off policy effects look modest: FY2026 MAPR increases can keep some claimants eligible, but there is no evidence of a broad new enrollment expansion for this specific pension tier."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, one-off, and policy mechanisms: level starts from 50.730 thousand at FY2025 first print. Momentum is negative because the pension rolls are dominated by older wartime cohorts and attrition is large. The offset is that A&A eligibility is concentrated among older and more disabled Veterans, so the row should decline more slowly than basic pension-only rolls. One-off policy effects look modest: FY2026 MAPR increases can keep some claimants eligible, but there is no evidence of a broad new enrollment expansion for this specific pension tier.","Prior/update/interval: persistence prior is FY2025 level 50.730 thousand. Historical sample is same-series FY2022 64.277, FY2023 about 59.8, FY2024 about 55.1, FY2025 50.730, giving successive changes about -4.477, -4.700, and -4.370 thousand. sigma = sqrt((4.477^2 + 4.700^2 + 4.370^2) / 3) = 4.52 thousand, used here as a conservative annual-step uncertainty floor from recent same-series declines rather than a residual-volatility estimate around the fitted trend. The trend update applies another -4.3 thousand attrition step, plus 0.0 thousand one-off and policy adjustment, yielding point 46.4. The 80% half-width is about 1.28*sigma = 1.28*4.52 = 5.79 thousand, so bounds are 46.4 - 5.8 = 40.6 and 46.4 + 5.8 = 52.2."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for FY2026 VA Veterans Pension Aid and Attendance Recipients","Framing and exact resolver: this forecast uses the VBA Annual Benefits Report Pension and Fiduciary table for All Veterans Pension recipients by type of special monthly pension. The variant is Veterans Pension recipients with aid and attendance (A&A), not survivors pension and not the combined A&A-or-housebound subtotal. The unit is thousands, so whole-recipient table values are divided by 1,000."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: va-pension-aid-attendance-recipients-fy2026\nrunLabel: Headline\nresolutionDate: 2027-05-12\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-participants-60-plus-share-fy2025.2026-07-21T02-16-21Z.5ce9e451b9ff8530","runId":"run.snap-participants-60-plus-share-fy2025.2026-07-21T02-16-21Z.5ce9e451b9ff8530","predictionId":"snap-participants-60-plus-share-fy2025","specId":"spec.snap-participants-60-plus-share-fy2025","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 3 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the reference class is annual SNAP QC Characteristics releases with the same age-60-or-older participant share definition. The same-series base rate rose from 14.1 percent in FY2018 to 19.8 percent in FY2024, but the latest annual change slowed to +0.3 percentage point.","Prior/update/interval: persistence prior is FY2024 same-series share 19.8 percent. Historical sample for uncertainty uses same-series official report table values and observed report-to-report changes from FY2015-FY2024 excluding missing FY2021: +1.134, +1.373, +0.989, +1.473, +0.599, +2.108, +1.188, +0.354 percentage points; the FY2020-to-FY2022 change is treated as one two-fiscal-year report gap, not annualized, because no FY2021 report exists. sigma = 0.539. Baseline update is +0.60 percentage point from aging momentum and continuation of the longer-run participant-composition trend, giving 19.8 + 0.60 = 20.4 percent. The normal 80% half-width is roughly 1.28*sigma = 1.28*0.539 = 0.69 point; I widen to 0.9 point, about 1.31x, for policy, QC-release, and missing-year composition uncertainty, giving 20.4 - 0.9 = 19.5 and 20.4 + 0.9 = 21.3."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 6 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Tool call: Inspect official documents listing for annual release timing","Tool result: Fetched official listing numbers: Characteristics of SNAP Households: Fiscal Year 2024 is dated 05/20/2026; nearby program data items include February 2026 Performance Report dated 05/14/2026 and January 2026 Keydata Report dated 04/24/2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: the target is the USDA FNS annual SNAP Characteristics report, not monthly SNAP Program Data tables. The variant is the annual SNAP QC sample Appendix Table A.29, elderly individuals age 60 or older divided by total participants, first public print.","Tool call: Inspect USDA FNS FY2024 Characteristics of SNAP Households release page"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.8, distribution present, forecast step count 1.","evidence":["Level, momentum, one-off, and policy mechanism: the FY2024 level was already high at 19.8 percent. Momentum remains positive because the SNAP caseload is aging, but the FY2022-FY2023 jump looks partly catch-up after pandemic-era QC disruption. I do not add a separate named FY2025 policy effect to the point estimate because the fetched evidence here is the QC characteristics series, not a policy implementation table; possible policy and administrative shifts are handled in the interval.","Prior/update/interval: persistence prior is FY2024 same-series share 19.8 percent. Historical sample for uncertainty uses same-series official report table values and observed report-to-report changes from FY2015-FY2024 excluding missing FY2021: +1.134, +1.373, +0.989, +1.473, +0.599, +2.108, +1.188, +0.354 percentage points; the FY2020-to-FY2022 change is treated as one two-fiscal-year report gap, not annualized, because no FY2021 report exists. sigma = 0.539. Baseline update is +0.60 percentage point from aging momentum and continuation of the longer-run participant-composition trend, giving 19.8 + 0.60 = 20.4 percent. The normal 80% half-width is roughly 1.28*sigma = 1.28*0.539 = 0.69 point; I widen to 0.9 point, about 1.31x, for policy, QC-release, and missing-year composition uncertainty, giving 20.4 - 0.9 = 19.5 and 20.4 + 0.9 = 21.3."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: Fetched report-series publication numbers: FY2023 was published April 2025, FY2022 in June 2024, FY2020 in June 2022, FY2019 in March 2021, FY2018 in November 2019, FY2017 in February 2019, FY2016 in November 2017, and FY2015 in November 2016; FY2021 had no report because data were incomplete.","Level, momentum, one-off, and policy mechanism: the FY2024 level was already high at 19.8 percent. Momentum remains positive because the SNAP caseload is aging, but the FY2022-FY2023 jump looks partly catch-up after pandemic-era QC disruption. I do not add a separate named FY2025 policy effect to the point estimate because the fetched evidence here is the QC characteristics series, not a policy implementation table; possible policy and administrative shifts are handled in the interval."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: the reference class is annual SNAP QC Characteristics releases with the same age-60-or-older participant share definition. The same-series base rate rose from 14.1 percent in FY2018 to 19.8 percent in FY2024, but the latest annual change slowed to +0.3 percentage point.","Level, momentum, one-off, and policy mechanism: the FY2024 level was already high at 19.8 percent. Momentum remains positive because the SNAP caseload is aging, but the FY2022-FY2023 jump looks partly catch-up after pandemic-era QC disruption. I do not add a separate named FY2025 policy effect to the point estimate because the fetched evidence here is the QC characteristics series, not a policy implementation table; possible policy and administrative shifts are handled in the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for FY2025 SNAP Participant Share Age 60 Plus","Base rate/reference class: the reference class is annual SNAP QC Characteristics releases with the same age-60-or-older participant share definition. The same-series base rate rose from 14.1 percent in FY2018 to 19.8 percent in FY2024, but the latest annual change slowed to +0.3 percentage point."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-participants-60-plus-share-fy2025\nrunLabel: Headline\nresolutionDate: 2027-05-20\ntraceLineCount: 20\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.colorado-labor-force-july-2026.2026-07-23T02-54-19Z.0e515aea259022d4","runId":"run.colorado-labor-force-july-2026.2026-07-23T02-54-19Z.0e515aea259022d4","predictionId":"colorado-labor-force-july-2026","specId":"spec.colorado-labor-force-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the cleanest base rate is Colorado's own recent seasonally adjusted LAUS labor-force path, because state labor-force levels are highly persistent and this is a one-month-ahead first-print target. The January through June 2026 sequence moved from 3,248.8 thousand to 3,193.3 thousand, a five-month decline of about 55.5 thousand.","Prior/update/interval: prior model is one-month persistence plus recent-change continuation using the narrow Jan-Jun 2026 Colorado seasonally adjusted labor-force history only. Successive changes in thousands were -10.3, -10.6, -12.3, -9.4, and -12.9; the mean monthly change is -11.1 thousand and sigma = 1.46 thousand. The point is 3,193.3 - 11.1 = 3,182.2 thousand. The normal 80% half-width is 1.28*sigma = 1.87 thousand; because the five-change sample is monotonic and likely understates normal one-month LAUS first-print uncertainty, I widen to 3.2 thousand, about 1.7x, for state CPS noise, the preliminary June anchor, and the small sample, giving final implied bounds 3,179.0 to 3,185.4 thousand."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this target is the BLS LAUS Colorado civilian labor force, seasonally adjusted, for July 2026, first print, in State Employment and Unemployment Table 1. The relevant BLS series code is LASST080000000000006: state 08, measure 06 labor force, seasonally adjusted. The target unit is thousands, so BLS person counts are divided by 1,000.","Tool call: Checked the official BLS August 2026 release calendar for the State Employment and Unemployment publication date."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this target is the BLS LAUS Colorado civilian labor force, seasonally adjusted, for July 2026, first print, in State Employment and Unemployment Table 1. The relevant BLS series code is LASST080000000000006: state 08, measure 06 labor force, seasonally adjusted. The target unit is thousands, so BLS person counts are divided by 1,000.","Tool call: Checked the official BLS August 2026 release calendar for the State Employment and Unemployment publication date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6.4, distribution present, forecast step count 1.","evidence":["Prior/update/interval: prior model is one-month persistence plus recent-change continuation using the narrow Jan-Jun 2026 Colorado seasonally adjusted labor-force history only. Successive changes in thousands were -10.3, -10.6, -12.3, -9.4, and -12.9; the mean monthly change is -11.1 thousand and sigma = 1.46 thousand. The point is 3,193.3 - 11.1 = 3,182.2 thousand. The normal 80% half-width is 1.28*sigma = 1.87 thousand; because the five-change sample is monotonic and likely understates normal one-month LAUS first-print uncertainty, I widen to 3.2 thousand, about 1.7x, for state CPS noise, the preliminary June anchor, and the small sample, giving final implied bounds 3,179.0 to 3,185.4 thousand.","Point and interval arithmetic in thousands: latest official June 2026 preliminary value 3,193.263 plus mean recent change -11.105 = 3,182.158, rounded to 3,182.2. Realized-change sigma = 1.462, so 1.28*sigma = 1.872; widened half-width 3.2 gives ciLow = 3,182.2 - 3.2 = 3,179.0 and ciHigh = 3,182.2 + 3.2 = 3,185.4."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate/reference class: the cleanest base rate is Colorado's own recent seasonally adjusted LAUS labor-force path, because state labor-force levels are highly persistent and this is a one-month-ahead first-print target. The January through June 2026 sequence moved from 3,248.8 thousand to 3,193.3 thousand, a five-month decline of about 55.5 thousand.","Level, momentum, one-off, and mechanism: the latest level is around 3.193 million and momentum is sharply negative but smooth. The mechanism is state CPS/LAUS model movement and labor-force participation, not payroll jobs. I use the same seasonally adjusted LAUS variant throughout; I do not mix in not-seasonally-adjusted COLFN anchors."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, one-off, and mechanism: the latest level is around 3.193 million and momentum is sharply negative but smooth. The mechanism is state CPS/LAUS model movement and labor-force participation, not payroll jobs. I use the same seasonally adjusted LAUS variant throughout; I do not mix in not-seasonally-adjusted COLFN anchors.","Prior/update/interval: prior model is one-month persistence plus recent-change continuation using the narrow Jan-Jun 2026 Colorado seasonally adjusted labor-force history only. Successive changes in thousands were -10.3, -10.6, -12.3, -9.4, and -12.9; the mean monthly change is -11.1 thousand and sigma = 1.46 thousand. The point is 3,193.3 - 11.1 = 3,182.2 thousand. The normal 80% half-width is 1.28*sigma = 1.87 thousand; because the five-change sample is monotonic and likely understates normal one-month LAUS first-print uncertainty, I widen to 3.2 thousand, about 1.7x, for state CPS noise, the preliminary June anchor, and the small sample, giving final implied bounds 3,179.0 to 3,185.4 thousand."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for Colorado July 2026 labor force","Prior/update/interval: prior model is one-month persistence plus recent-change continuation using the narrow Jan-Jun 2026 Colorado seasonally adjusted labor-force history only. Successive changes in thousands were -10.3, -10.6, -12.3, -9.4, and -12.9; the mean monthly change is -11.1 thousand and sigma = 1.46 thousand. The point is 3,193.3 - 11.1 = 3,182.2 thousand. The normal 80% half-width is 1.28*sigma = 1.87 thousand; because the five-change sample is monotonic and likely understates normal one-month LAUS first-print uncertainty, I widen to 3.2 thousand, about 1.7x, for state CPS noise, the preliminary June anchor, and the small sample, giving final implied bounds 3,179.0 to 3,185.4 thousand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: colorado-labor-force-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-21\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.colorado-income-tax-collections-july-2026.2026-07-23T02-58-18Z.daa44454e98be686","runId":"run.colorado-income-tax-collections-july-2026.2026-07-23T02-58-18Z.daa44454e98be686","predictionId":"colorado-income-tax-collections-july-2026","specId":"spec.colorado-income-tax-collections-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the clean official base rate is annual-run-rate persistence from LCS. Dividing 9997.9, 11153.0, and 12537.6 million dollars by 12 gives 0.833, 0.929, and 1.045 billion monthly-average equivalents. July-specific history is volatile: 0.614 billion in ordinary July 2019 versus 1.760 billion in deadline-shift July 2020.","Prior/update/interval: prior model is annual-run-rate persistence from the official June 2026 LCS net individual income tax forecast, with historical sample values 0.833, 0.929, 1.045, 0.614, and 1.760 billion. Adjustment components are 12.5376 / 12 = 1.0448 billion, a judgmental -0.050 billion July timing discount because July lacks the April return-payment peak and the September estimated-payment due date, a judgmental -0.015 billion refund-drag adjustment because refunds were up 15.2 percent through May, and 0.000 net policy adjustment because OBBBA addbacks and credit/refund channels point in opposite directions, giving 0.9798 billion. For this flow series, I size the interval from the cited values themselves while recognizing the sample mixes annual run-rate anchors with July stress points: sigma = 0.434 billion; 1.28*sigma = 0.556 billion; final implied bounds around 0.980 +/- 0.556 are 0.42 to 1.54 billion after rounding."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Colorado July 2026 individual income tax net collections","Framing and exact resolver: the target is CDOR's General Fund Collections Report line for net individual income tax collections for July 2026, cash basis, first print. The variant is net receipts as posted in the Colorado state accounting system, not gross income tax liability, not annual SOI tax-year data, and not a revised later vintage."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: the target is CDOR's General Fund Collections Report line for net individual income tax collections for July 2026, cash basis, first print. The variant is net receipts as posted in the Colorado state accounting system, not gross income tax liability, not annual SOI tax-year data, and not a revised later vintage.","Resolution timing: the canonical ledger gives resolutionDate 2026-08-31 for the first post-July accounting print. I found no concrete ledger error; the official CDOR page is the stable July 2019-to-date monthly publication surface, and the Colorado tax due-date guide supports using the post-month accounting cycle rather than tax-year cadence."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.12, distribution present, forecast step count 1.","evidence":["Level, momentum, one-off, and policy mechanisms: level starts at the FY2026-27 monthly run rate of 1.045 billion. Momentum is positive from strong final payments, estimated payments, and withholding. July should still run below the annual monthly average because it is after the April filing peak and June estimated-payment date but before the September estimated-payment date; the cited ordinary July 2019 value of 0.614 billion was far below April 2019's 1.82 billion, while July 2020 is treated as a deadline-shift tail guide rather than normal seasonality. Policy and accounting effects are two-sided, while elevated refunds reduce net collections.","Prior/update/interval: prior model is annual-run-rate persistence from the official June 2026 LCS net individual income tax forecast, with historical sample values 0.833, 0.929, 1.045, 0.614, and 1.760 billion. Adjustment components are 12.5376 / 12 = 1.0448 billion, a judgmental -0.050 billion July timing discount because July lacks the April return-payment peak and the September estimated-payment due date, a judgmental -0.015 billion refund-drag adjustment because refunds were up 15.2 percent through May, and 0.000 net policy adjustment because OBBBA addbacks and credit/refund channels point in opposite directions, giving 0.9798 billion. For this flow series, I size the interval from the cited values themselves while recognizing the sample mixes annual run-rate anchors with July stress points: sigma = 0.434 billion; 1.28*sigma = 0.556 billion; final implied bounds around 0.980 +/- 0.556 are 0.42 to 1.54 billion after rounding."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Read the LCS General Fund Revenue section for current cash-basis momentum entering the July 2026 collection month.","Tool result: Fetched LCS through-May 2026 momentum: individual income tax revenue expected to increase 11.6 percent to 11.15 billion dollars before transfers; withholding was up 4.9 percent, estimated payments up 20.3 percent, cash with returns up 15.0 percent, and refunds up 15.2 percent."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, one-off, and policy mechanisms: level starts at the FY2026-27 monthly run rate of 1.045 billion. Momentum is positive from strong final payments, estimated payments, and withholding. July should still run below the annual monthly average because it is after the April filing peak and June estimated-payment date but before the September estimated-payment date; the cited ordinary July 2019 value of 0.614 billion was far below April 2019's 1.82 billion, while July 2020 is treated as a deadline-shift tail guide rather than normal seasonality. Policy and accounting effects are two-sided, while elevated refunds reduce net collections.","Counter-consideration: upside risk would land above the interval if late final payments or unusually large pass-through income payments spill into July after the strong spring filing season. Downside risk would land below the interval if refunds remain unusually elevated, high-income payments were mostly pulled forward, or withholding weakens sharply. Outside the interval high would likely require a deadline or accounting-timing shock similar in direction to July 2020; outside the interval low would likely require a large refund-processing batch or a reporting break in the first print."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: Opened the Colorado Legislative Council Staff June 2026 Economic and Revenue Forecast page and report for recent official annual net individual income tax levels.","Tool result: Fetched LCS values in millions of dollars: FY2024-25 net individual income tax actual 9997.9, FY2025-26 estimate 11153.0, and FY2026-27 forecast 12537.6."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: colorado-income-tax-collections-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-31\ntraceLineCount: 20\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.colorado-medicaid-caseload-august-2026.2026-07-23T03-03-37Z.8b31867878ece80c","runId":"run.colorado-medicaid-caseload-august-2026.2026-07-23T03-03-37Z.8b31867878ece80c","predictionId":"colorado-medicaid-caseload-august-2026","specId":"spec.colorado-medicaid-caseload-august-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool result: Fetched HCPF page statement that the reports describe monthly spending and caseload statistics for Medical Services Premiums; it states reports contain data about the prior month and that a link labeled August references August activity but is dated September. The page listed FY 2025-26 report links for 7 months from July 2025 through February 2026.","Base rate/reference class: the official-source reference class is the same HCPF TOTAL row from January 2025 through January 2026. The base rate is slow-moving level persistence with modest positive drift: January 2026 was 1,236.302 thousand, up 21.878 thousand from January 2025 and only 0.973 thousand above August 2025 after a temporary November dip."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Tool call: Checked the HCPF Premiums, Expenditures and Caseload Reports page for the official data page and report timing convention.","Tool call: Checked CMS Medicaid and CHIP Eligibility Operations and Enrollment Snapshot page for broader public enrollment-release context."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this targets HCPF's statewide Health First Colorado Medicaid TOTAL caseload in the Medical Premiums Expenditure and Caseload Report for August 2026, converted from members to thousands. It is the same HCPF Medical Premiums TOTAL variant throughout; it is not CHP+, not a county-only report, and not the CMS Medicaid-and-CHIP snapshot.","Tool result: Fetched HCPF enrollment update: in January 2026 there were 1,236,302 Coloradans enrolled in Health First Colorado and 75,103 enrolled in Child Health Plan Plus; the homepage also describes Medicaid as covering 1 in 5 Coloradans."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 43, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is the January 2026 HCPF TOTAL level of 1236.302 thousand; historical sample is January 2025 through January 2026 same-variant HCPF TOTAL values with successive monthly changes of -4.899, +4.427, +9.836, +2.419, +4.426, +1.856, +2.840, -0.321, +0.935, -14.135, +8.148, and +6.346 thousand. Adjustment components are +9.8 thousand level/momentum, +3.0 thousand seasonality, and -2.0 thousand policy/renewal churn, so point = 1236.302 + 9.8 + 3.0 - 2.0 = 1247.102, rounded to 1247.1 thousand. Monthly sigma = 6.359 thousand; for a seven-month horizon sigma = sqrt(7)*6.359 = 16.8 thousand, and 1.28*sigma = 1.28*16.8 = 21.5 thousand, giving 1247.1 +/- 21.5 = [1225.6, 1268.6].","Counter-considerations: upside risk is stronger retention, outreach, or delayed renewal closures that would land above the interval above 1268.6 thousand, roughly 32.3 thousand above the January 2026 level. Downside risk is renewed administrative churn, a reporting lag like November 2025, or faster eligibility losses that would land below the interval under 1225.6 thousand, roughly 10.7 thousand below January 2026. Outside the interval would most likely require either a sustained post-January surge beyond the 2025 summer path or another broad reporting/renewal shock."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and policy effects: the level anchor is 1,236.302 thousand. Momentum is modestly positive after the November 2025 dip reversed by January 2026. The January-to-August 2025 move was +20.905 thousand, but I damp that because unwind catch-up should be smaller in 2026. I add about +9.8 thousand for seven months of ordinary drift, +3.0 thousand for summer/new-fiscal-year seasonality, and subtract 2.0 thousand for renewal and budget-policy churn.","Prior/update/interval: persistence prior is the January 2026 HCPF TOTAL level of 1236.302 thousand; historical sample is January 2025 through January 2026 same-variant HCPF TOTAL values with successive monthly changes of -4.899, +4.427, +9.836, +2.419, +4.426, +1.856, +2.840, -0.321, +0.935, -14.135, +8.148, and +6.346 thousand. Adjustment components are +9.8 thousand level/momentum, +3.0 thousand seasonality, and -2.0 thousand policy/renewal churn, so point = 1236.302 + 9.8 + 3.0 - 2.0 = 1247.102, rounded to 1247.1 thousand. Monthly sigma = 6.359 thousand; for a seven-month horizon sigma = sqrt(7)*6.359 = 16.8 thousand, and 1.28*sigma = 1.28*16.8 = 21.5 thousand, giving 1247.1 +/- 21.5 = [1225.6, 1268.6]."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool result: Fetched HCPF page statement that the reports describe monthly spending and caseload statistics for Medical Services Premiums; it states reports contain data about the prior month and that a link labeled August references August activity but is dated September. The page listed FY 2025-26 report links for 7 months from July 2025 through February 2026.","Level, momentum, one-off, and policy effects: the level anchor is 1,236.302 thousand. Momentum is modestly positive after the November 2025 dip reversed by January 2026. The January-to-August 2025 move was +20.905 thousand, but I damp that because unwind catch-up should be smaller in 2026. I add about +9.8 thousand for seven months of ordinary drift, +3.0 thousand for summer/new-fiscal-year seasonality, and subtract 2.0 thousand for renewal and budget-policy churn."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for Colorado Medicaid total caseload in August 2026","Prior/update/interval: persistence prior is the January 2026 HCPF TOTAL level of 1236.302 thousand; historical sample is January 2025 through January 2026 same-variant HCPF TOTAL values with successive monthly changes of -4.899, +4.427, +9.836, +2.419, +4.426, +1.856, +2.840, -0.321, +0.935, -14.135, +8.148, and +6.346 thousand. Adjustment components are +9.8 thousand level/momentum, +3.0 thousand seasonality, and -2.0 thousand policy/renewal churn, so point = 1236.302 + 9.8 + 3.0 - 2.0 = 1247.102, rounded to 1247.1 thousand. Monthly sigma = 6.359 thousand; for a seven-month horizon sigma = sqrt(7)*6.359 = 16.8 thousand, and 1.28*sigma = 1.28*16.8 = 21.5 thousand, giving 1247.1 +/- 21.5 = [1225.6, 1268.6]."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: colorado-medicaid-caseload-august-2026\nrunLabel: Headline\nresolutionDate: 2026-09-15\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-qcew-aircraft-manufacturing-establishments-q1-2026.2026-07-23T03-14-11Z.31ed66c657972918","runId":"run.us-qcew-aircraft-manufacturing-establishments-q1-2026.2026-07-23T03-14-11Z.31ed66c657972918","predictionId":"us-qcew-aircraft-manufacturing-establishments-q1-2026","specId":"spec.us-qcew-aircraft-manufacturing-establishments-q1-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Framing and exact resolver: this targets the BLS QCEW NAICS-based quarterly CSV first print for 2026 Q1, national area_fips=US000, private ownership own_code=5, NAICS 336411 Aircraft manufacturing, all establishment sizes size_code=0, field qtrly_estabs. The ledger source URL is a BLS portal; the most specific data-slice pattern for this exact target is https://data.bls.gov/cew/data/api/2026/1/industry/336411.csv when the first print is released.","Base rate/reference class: detailed six-digit manufacturing establishment series are persistent and low-volatility. I anchor the NAICS 336411 level near the recent 2025 QCEW private aircraft manufacturing path, then use the broader manufacturing establishment increase and flat 2025 aircraft employment as offsetting signals."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this targets the BLS QCEW NAICS-based quarterly CSV first print for 2026 Q1, national area_fips=US000, private ownership own_code=5, NAICS 336411 Aircraft manufacturing, all establishment sizes size_code=0, field qtrly_estabs. The ledger source URL is a BLS portal; the most specific data-slice pattern for this exact target is https://data.bls.gov/cew/data/api/2026/1/industry/336411.csv when the first print is released.","Tool call: BLS QCEW release calendar lookup for County Employment and Wages 2026 Q1"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this targets the BLS QCEW NAICS-based quarterly CSV first print for 2026 Q1, national area_fips=US000, private ownership own_code=5, NAICS 336411 Aircraft manufacturing, all establishment sizes size_code=0, field qtrly_estabs. The ledger source URL is a BLS portal; the most specific data-slice pattern for this exact target is https://data.bls.gov/cew/data/api/2026/1/industry/336411.csv when the first print is released.","Tool call: BLS QCEW release calendar lookup for County Employment and Wages 2026 Q1"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 18, distribution present, forecast step count 1.","evidence":["Base rate/reference class: detailed six-digit manufacturing establishment series are persistent and low-volatility. I anchor the NAICS 336411 level near the recent 2025 QCEW private aircraft manufacturing path, then use the broader manufacturing establishment increase and flat 2025 aircraft employment as offsetting signals.","Prior/update/interval: persistence prior is latest 2025 Q4 aircraft-manufacturing establishment nowcast anchor of 393, using the 2023 Q1 through 2025 Q3 same-variant QCEW reference path plus a 2025 Q4 anchor: 365, 367, 369, 371, 374, 376, 379, 381, 388, 390, 391, 393; level effect +0, momentum +2 from recent net openings and parent manufacturing growth, one-off/reclassification effect +0, policy-mechanism effect +0, giving point 393+2=395. Successive changes are 2,2,2,3,2,3,2,7,2,1,2, so sigma = 1.55 establishments; 1.28*sigma = 1.98. I widen to 9 establishments, about 4.5x the mechanical half-width, because six-digit QCEW industry reclassification and disclosure/administrative updates can create lumpy first-print moves beyond recent smooth momentum."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior is latest 2025 Q4 aircraft-manufacturing establishment nowcast anchor of 393, using the 2023 Q1 through 2025 Q3 same-variant QCEW reference path plus a 2025 Q4 anchor: 365, 367, 369, 371, 374, 376, 379, 381, 388, 390, 391, 393; level effect +0, momentum +2 from recent net openings and parent manufacturing growth, one-off/reclassification effect +0, policy-mechanism effect +0, giving point 393+2=395. Successive changes are 2,2,2,3,2,3,2,7,2,1,2, so sigma = 1.55 establishments; 1.28*sigma = 1.98. I widen to 9 establishments, about 4.5x the mechanical half-width, because six-digit QCEW industry reclassification and disclosure/administrative updates can create lumpy first-print moves beyond recent smooth momentum.","Counter-considerations: upside risk would be a reclassification or new reporting wave tied to defense/commercial aircraft suppliers that lifts Q1 above 404. Downside risk would be consolidation, closures, or recoding into other aerospace parts industries that pushes the first print below 386. Either event would land outside the interval because ordinary persistence explains only a few establishments of quarterly movement."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: detailed six-digit manufacturing establishment series are persistent and low-volatility. I anchor the NAICS 336411 level near the recent 2025 QCEW private aircraft manufacturing path, then use the broader manufacturing establishment increase and flat 2025 aircraft employment as offsetting signals.","Counter-considerations: upside risk would be a reclassification or new reporting wave tied to defense/commercial aircraft suppliers that lifts Q1 above 404. Downside risk would be consolidation, closures, or recoding into other aerospace parts industries that pushes the first print below 386. Either event would land outside the interval because ordinary persistence explains only a few establishments of quarterly movement."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["US QCEW Aircraft Manufacturing Establishments Forecast","Tool call: Recent public reference points for same industry and neighboring sources"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-qcew-aircraft-manufacturing-establishments-q1-2026\nrunLabel: Headline\nresolutionDate: 2026-08-28\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-nursing-home-occupancy-july-2026.2026-07-21T08-43-54Z.378cf0ef5df37315","runId":"run.us-nursing-home-occupancy-july-2026.2026-07-21T08-43-54Z.378cf0ef5df37315","predictionId":"us-nursing-home-occupancy-july-2026","specId":"spec.us-nursing-home-occupancy-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 3 historical point(s) and explicit outside-view language.","evidence":["Tool call: CMS archived NH_ProviderInfo aggregate history for first-print occupancy base rate","Base rate/reference class: adjacent Care Compare nursing-home Provider Information first-print snapshots are the right base rate because the target is the same CMS file, same all-facility weighting, same percent unit, and same monthly refresh process. The latest six values show a steady rise from 79.16 to 79.75 percent."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Tool result: Fetched recent official archive aggregate occupancy values used as the reference class: 2026-01 79.16, 2026-02 79.33, 2026-03 79.42, 2026-04 79.55, 2026-05 79.66, and 2026-06 79.75 percent.","Prior/update/interval: persistence-plus-recent-monthly-trend model prior is the June 2026 official aggregate, 79.75 percent. Historical sample is the six 2026 archive values 79.16, 79.33, 79.42, 79.55, 79.66, 79.75; successive changes are +0.17, +0.09, +0.13, +0.11, +0.09 percentage points, with sigma = 0.03 percentage points. The net update is +0.07 point total, composed of about +0.06 from recent occupancy momentum and +0.01 from continued certified-bed denominator contraction, with no one-off policy mechanism adjustment, giving 79.75 + 0.07 = 79.82. The mechanical 80% half-width is 1.28*sigma = 1.28*0.03 = 0.04; I widen to 0.07, about 1.75x, because the July first print can include uneven facility additions/removals and census seasonality around the prior quarter boundary."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["US nursing-home occupancy, July 2026 first print","Framing and exact resolver: this forecast uses CMS Care Compare Provider Information dataset 4pq5-n9py, NH_ProviderInfo, first print for the July 2026 refresh. The resolved value is the national ratio of Average Number of Residents per Day to Number of Certified Beds across all rows with both fields populated, multiplied by 100 and rounded to two decimals."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.14, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence-plus-recent-monthly-trend model prior is the June 2026 official aggregate, 79.75 percent. Historical sample is the six 2026 archive values 79.16, 79.33, 79.42, 79.55, 79.66, 79.75; successive changes are +0.17, +0.09, +0.13, +0.11, +0.09 percentage points, with sigma = 0.03 percentage points. The net update is +0.07 point total, composed of about +0.06 from recent occupancy momentum and +0.01 from continued certified-bed denominator contraction, with no one-off policy mechanism adjustment, giving 79.75 + 0.07 = 79.82. The mechanical 80% half-width is 1.28*sigma = 1.28*0.03 = 0.04; I widen to 0.07, about 1.75x, because the July first print can include uneven facility additions/removals and census seasonality around the prior quarter boundary.","Counter-consideration: upside risk would be a faster resident census gain or a larger drop in certified beds, which would land above the interval. Downside risk would be a flat resident numerator, a larger set of newly included low-occupancy facilities under the all-rows-with-both-fields-populated rule, or a correction to reported average residents, which would land below the interval. Outside the interval is most likely if CMS changes the facility population or reporting completeness more than in recent monthly snapshots."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate/reference class: adjacent Care Compare nursing-home Provider Information first-print snapshots are the right base rate because the target is the same CMS file, same all-facility weighting, same percent unit, and same monthly refresh process. The latest six values show a steady rise from 79.16 to 79.75 percent.","Prior/update/interval: persistence-plus-recent-monthly-trend model prior is the June 2026 official aggregate, 79.75 percent. Historical sample is the six 2026 archive values 79.16, 79.33, 79.42, 79.55, 79.66, 79.75; successive changes are +0.17, +0.09, +0.13, +0.11, +0.09 percentage points, with sigma = 0.03 percentage points. The net update is +0.07 point total, composed of about +0.06 from recent occupancy momentum and +0.01 from continued certified-bed denominator contraction, with no one-off policy mechanism adjustment, giving 79.75 + 0.07 = 79.82. The mechanical 80% half-width is 1.28*sigma = 1.28*0.03 = 0.04; I widen to 0.07, about 1.75x, because the July first print can include uneven facility additions/removals and census seasonality around the prior quarter boundary."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-consideration: upside risk would be a faster resident census gain or a larger drop in certified beds, which would land above the interval. Downside risk would be a flat resident numerator, a larger set of newly included low-occupancy facilities under the all-rows-with-both-fields-populated rule, or a correction to reported average residents, which would land below the interval. Outside the interval is most likely if CMS changes the facility population or reporting completeness more than in recent monthly snapshots."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Framing and exact resolver: this forecast uses CMS Care Compare Provider Information dataset 4pq5-n9py, NH_ProviderInfo, first print for the July 2026 refresh. The resolved value is the national ratio of Average Number of Residents per Day to Number of Certified Beds across all rows with both fields populated, multiplied by 100 and rounded to two decimals.","Prior/update/interval: persistence-plus-recent-monthly-trend model prior is the June 2026 official aggregate, 79.75 percent. Historical sample is the six 2026 archive values 79.16, 79.33, 79.42, 79.55, 79.66, 79.75; successive changes are +0.17, +0.09, +0.13, +0.11, +0.09 percentage points, with sigma = 0.03 percentage points. The net update is +0.07 point total, composed of about +0.06 from recent occupancy momentum and +0.01 from continued certified-bed denominator contraction, with no one-off policy mechanism adjustment, giving 79.75 + 0.07 = 79.82. The mechanical 80% half-width is 1.28*sigma = 1.28*0.03 = 0.04; I widen to 0.07, about 1.75x, because the July first print can include uneven facility additions/removals and census seasonality around the prior quarter boundary."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-nursing-home-occupancy-july-2026\nrunLabel: Headline\nresolutionDate: 2026-07-29\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.colorado-ssi-recipients-65-plus-july-2026.2026-07-21T09-31-43Z.aa3cf3108d9d3268","runId":"run.colorado-ssi-recipients-65-plus-july-2026.2026-07-21T09-31-43Z.aa3cf3108d9d3268","predictionId":"colorado-ssi-recipients-65-plus-july-2026","specId":"spec.colorado-ssi-recipients-65-plus-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 7 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: the official Colorado 65+ recipient count over December 2025 through June 2026 is 23,101, 23,102, 23,060, 23,039, 23,062, 23,036, and 23,063. The level base rate is a stable 23.0k count series, with no month in this window outside 23,036 to 23,102.","Prior/update/interval: persistence prior = latest official June 2026 value 23,063 using the December 2025-June 2026 official SSA Table 4 reference class; adjustment components are level 23,063, momentum -6 from the mean monthly change, and recent stabilization +3, giving point 23,060. Successive changes are +1, -42, -21, +23, -26, +27; sigma = 27.9 recipients from the sample standard deviation of those changes; 80% half-width = 1.28*sigma = 1.28*27.9 = 35.7, rounded to 36, so bounds are 23,060-36 = 23,024 and 23,060+36 = 23,096."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 8 source-context item(s), activity log present.","evidence":["Tool call: Opened SSA SSI Monthly Statistics June 2026 Table 4 for the latest official Colorado age-row anchor.","Tool call: Opened SSA SSI Monthly Statistics May 2026 Table 4 for one-month-back official history."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Colorado SSI aged 65+ recipients, July 2026 first print","Framing and exact resolver: this is the SSA SSI Monthly Statistics Table 4 Colorado row, Age 65 or older column, All Federally Administered Payments. The variant is a whole-person count from the Supplemental Security Record, 100 percent data, not payments, federal-only recipients, state-supplement-only recipients, or a smoothed series. The July 2026 table URL may remain unresolved until first publication, but the resolver is the first posted SSA Table 4 value at that address."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 72, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = latest official June 2026 value 23,063 using the December 2025-June 2026 official SSA Table 4 reference class; adjustment components are level 23,063, momentum -6 from the mean monthly change, and recent stabilization +3, giving point 23,060. Successive changes are +1, -42, -21, +23, -26, +27; sigma = 27.9 recipients from the sample standard deviation of those changes; 80% half-width = 1.28*sigma = 1.28*27.9 = 35.7, rounded to 36, so bounds are 23,060-36 = 23,024 and 23,060+36 = 23,096.","Counter-consideration: upside risk is a continued rebound in aged and disabled recipients after the spring decline, which would land above the interval if Colorado age 65+ exceeds 23,096. Downside risk is a renewed administrative or eligibility-driven drop like January-February, which would land below the interval if the first print is under 23,024. Outside the interval would require a move larger than the recent realized month-to-month dispersion."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and mechanism split: the level anchor is the latest 23,063; six-month momentum is mildly negative at -38 from December to June, while the latest move was +27 from May to June. I apply a small -3 net adjustment because the broader drift offsets the latest rebound. I found no July-specific policy mechanism in the official series definition that would materially change only Colorado aged 65+ recipients.","Prior/update/interval: persistence prior = latest official June 2026 value 23,063 using the December 2025-June 2026 official SSA Table 4 reference class; adjustment components are level 23,063, momentum -6 from the mean monthly change, and recent stabilization +3, giving point 23,060. Successive changes are +1, -42, -21, +23, -26, +27; sigma = 27.9 recipients from the sample standard deviation of those changes; 80% half-width = 1.28*sigma = 1.28*27.9 = 35.7, rounded to 36, so bounds are 23,060-36 = 23,024 and 23,060+36 = 23,096."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Framing and exact resolver: this is the SSA SSI Monthly Statistics Table 4 Colorado row, Age 65 or older column, All Federally Administered Payments. The variant is a whole-person count from the Supplemental Security Record, 100 percent data, not payments, federal-only recipients, state-supplement-only recipients, or a smoothed series. The July 2026 table URL may remain unresolved until first publication, but the resolver is the first posted SSA Table 4 value at that address.","Level, momentum, one-off, and mechanism split: the level anchor is the latest 23,063; six-month momentum is mildly negative at -38 from December to June, while the latest move was +27 from May to June. I apply a small -3 net adjustment because the broader drift offsets the latest rebound. I found no July-specific policy mechanism in the official series definition that would materially change only Colorado aged 65+ recipients."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: persistence prior = latest official June 2026 value 23,063 using the December 2025-June 2026 official SSA Table 4 reference class; adjustment components are level 23,063, momentum -6 from the mean monthly change, and recent stabilization +3, giving point 23,060. Successive changes are +1, -42, -21, +23, -26, +27; sigma = 27.9 recipients from the sample standard deviation of those changes; 80% half-width = 1.28*sigma = 1.28*27.9 = 35.7, rounded to 36, so bounds are 23,060-36 = 23,024 and 23,060+36 = 23,096.","Counter-consideration: upside risk is a continued rebound in aged and disabled recipients after the spring decline, which would land above the interval if Colorado age 65+ exceeds 23,096. Downside risk is a renewed administrative or eligibility-driven drop like January-February, which would land below the interval if the first print is under 23,024. Outside the interval would require a move larger than the recent realized month-to-month dispersion."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: colorado-ssi-recipients-65-plus-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-31\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.uk-construction-output-growth-may-2026.2026-07-08T16-57-27Z.1b7d3cdf269f20a5","runId":"run.uk-construction-output-growth-may-2026.2026-07-08T16-57-27Z.1b7d3cdf269f20a5","predictionId":"uk-construction-output-growth-may-2026","specId":"spec.uk-construction-output-growth-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 10 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the recent official-source monthly all-work SA growth reference class is centered near flat, with mean 0.00% over the ten fetched monthly observations. I anchor near that base rate rather than extrapolating March's 1.5% because ONS described March as helped by financial year-end pushes and April already slowed to 0.1%.","Prior/update/interval: persistence/base-rate prior uses the ten ONS same-variant monthly growth values from July 2025 through April 2026, using latest revised values available before the May 2026 first print where available: 0.2, -0.3, 0.2, -0.6, -1.3, -0.5, 0.2, 0.5, 1.5, 0.1. Mean = 0.00. sigma = 0.75 using sample standard deviation of those values themselves because this is already a change/flow series. 80% half-width = 1.28*sigma = 0.96. Point update: 0.00 base rate + 0.15 positive three-month momentum - 0.05 March one-off/new-orders drag = 0.10. Rounded 80% interval: 0.10 +/- 0.96 gives about -0.9 to 1.1."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["UK construction output growth, May 2026 first print","Framing and exact resolver: target is ONS total construction output in Great Britain, all work, chained volume measure, seasonally adjusted, month-on-month percent growth for May 2026. I use the same SA all-work monthly growth variant for all anchors; the all-work summary dataset page is the table source, while the May 2026 bulletin is the first-print resolution page."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["UK construction output growth, May 2026 first print","Framing and exact resolver: target is ONS total construction output in Great Britain, all work, chained volume measure, seasonally adjusted, month-on-month percent growth for May 2026. I use the same SA all-work monthly growth variant for all anchors; the all-work summary dataset page is the table source, while the May 2026 bulletin is the first-print resolution page."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2, distribution present, forecast step count 1.","evidence":["Tool result: Fetched March 2026 details: monthly total output grew 1.5%, new work grew 2.0%, repair and maintenance grew 0.8%, and Q1 2026 new orders fell 10.5% versus Q4 2025.","Prior/update/interval: persistence/base-rate prior uses the ten ONS same-variant monthly growth values from July 2025 through April 2026, using latest revised values available before the May 2026 first print where available: 0.2, -0.3, 0.2, -0.6, -1.3, -0.5, 0.2, 0.5, 1.5, 0.1. Mean = 0.00. sigma = 0.75 using sample standard deviation of those values themselves because this is already a change/flow series. 80% half-width = 1.28*sigma = 0.96. Point update: 0.00 base rate + 0.15 positive three-month momentum - 0.05 March one-off/new-orders drag = 0.10. Rounded 80% interval: 0.10 +/- 0.96 gives about -0.9 to 1.1."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate/reference class: the recent official-source monthly all-work SA growth reference class is centered near flat, with mean 0.00% over the ten fetched monthly observations. I anchor near that base rate rather than extrapolating March's 1.5% because ONS described March as helped by financial year-end pushes and April already slowed to 0.1%.","Current-release update: level and momentum are mildly positive because the three-month measure rose 1.6% and April did not reverse March's jump. One-off effect is negative because the March financial-year push should not repeat in May. Policy/mechanism pressure is slightly negative from Q1 new orders down 10.5%, but construction output can lag orders, so I do not make a large near-term cut."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Current-release update: level and momentum are mildly positive because the three-month measure rose 1.6% and April did not reverse March's jump. One-off effect is negative because the March financial-year push should not repeat in May. Policy/mechanism pressure is slightly negative from Q1 new orders down 10.5%, but construction output can lag orders, so I do not make a large near-term cut.","Counter-consideration: upside risk is a continued repair-and-maintenance surge plus resilient new-work site activity, which would land above the interval if May prints above 1.1%. Downside risk is delayed new work, weak private new housing, or order-book pass-through from lower new orders, which would land outside the interval below -0.9%."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ONS April 2026 construction output bulletin main-points lookup","Prior/update/interval: persistence/base-rate prior uses the ten ONS same-variant monthly growth values from July 2025 through April 2026, using latest revised values available before the May 2026 first print where available: 0.2, -0.3, 0.2, -0.6, -1.3, -0.5, 0.2, 0.5, 1.5, 0.1. Mean = 0.00. sigma = 0.75 using sample standard deviation of those values themselves because this is already a change/flow series. 80% half-width = 1.28*sigma = 0.96. Point update: 0.00 base rate + 0.15 positive three-month momentum - 0.05 March one-off/new-orders drag = 0.10. Rounded 80% interval: 0.10 +/- 0.96 gives about -0.9 to 1.1."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: uk-construction-output-growth-may-2026\nrunLabel: Headline\nresolutionDate: 2026-07-16\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.fed-g17-capacity-utilization-total-industry-june-2026.2026-07-08T16-53-10Z.b1f4cd5d81defefb","runId":"run.fed-g17-capacity-utilization-total-industry-june-2026.2026-07-08T16-53-10Z.b1f4cd5d81defefb","predictionId":"fed-g17-capacity-utilization-total-industry-june-2026","specId":"spec.fed-g17-capacity-utilization-total-industry-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Prior/update/interval: base rate prior is a near-persistence model for total industry utilization using the recent Federal Reserve/FRED reference class of monthly level changes from Dec 2025 through May 2026: -0.30, +0.54, -0.31, +0.59, +0.04 percentage point, giving sigma = 0.44. Level prior starts at May 2026 TCU 76.1663; momentum adjustment is +0.03 from the positive April-May IP/utilization trend, one-off adjustment is 0.00 because utilities weakness and mining strength offset, and policy-mechanism adjustment is 0.00. Point = 76.1663 + 0.03 = 76.20. 80% half-width is roughly 1.28*sigma = 1.28*0.44 = 0.56, rounded to a one-decimal first-print interval of 75.6 to 76.8.","Review disposition: accepted the reviewer assessment that no required fixes were needed; noted the optional caveat by making clear the interval uses a short, recent five-month volatility reference class rather than a longer historical sample."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Tool call: FRED TCU mirror for precise recent observations sourced to the Federal Reserve Board","Counter-considerations: upside risk would come from another mining jump plus warmer-weather utility output and a rebound in manufacturing, which would land above the interval if utilization prints above 76.8. Downside risk is a June industrial production pullback or capacity benchmark-related weakness across manufacturing; a broad drop larger than about 0.6 point would land below the interval. Outside the interval would require a shock comparable to the largest recent month-to-month moves, not just normal rounding noise."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this is the Federal Reserve G.17 Capacity Utilization: Total Industry series, seasonally adjusted percent of capacity. The target is the first published June 2026 value in the July 17, 2026 G.17 release; the series code mirror is FRED TCU, but resolution is to the Federal Reserve release table.","Tool call: Federal Reserve G.17 release calendar lookup for 2026 monthly releases"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.2, distribution present, forecast step count 1.","evidence":["Prior/update/interval: base rate prior is a near-persistence model for total industry utilization using the recent Federal Reserve/FRED reference class of monthly level changes from Dec 2025 through May 2026: -0.30, +0.54, -0.31, +0.59, +0.04 percentage point, giving sigma = 0.44. Level prior starts at May 2026 TCU 76.1663; momentum adjustment is +0.03 from the positive April-May IP/utilization trend, one-off adjustment is 0.00 because utilities weakness and mining strength offset, and policy-mechanism adjustment is 0.00. Point = 76.1663 + 0.03 = 76.20. 80% half-width is roughly 1.28*sigma = 1.28*0.44 = 0.56, rounded to a one-decimal first-print interval of 75.6 to 76.8.","Counter-considerations: upside risk would come from another mining jump plus warmer-weather utility output and a rebound in manufacturing, which would land above the interval if utilization prints above 76.8. Downside risk is a June industrial production pullback or capacity benchmark-related weakness across manufacturing; a broad drop larger than about 0.6 point would land below the interval. Outside the interval would require a shock comparable to the largest recent month-to-month moves, not just normal rounding noise."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: base rate prior is a near-persistence model for total industry utilization using the recent Federal Reserve/FRED reference class of monthly level changes from Dec 2025 through May 2026: -0.30, +0.54, -0.31, +0.59, +0.04 percentage point, giving sigma = 0.44. Level prior starts at May 2026 TCU 76.1663; momentum adjustment is +0.03 from the positive April-May IP/utilization trend, one-off adjustment is 0.00 because utilities weakness and mining strength offset, and policy-mechanism adjustment is 0.00. Point = 76.1663 + 0.03 = 76.20. 80% half-width is roughly 1.28*sigma = 1.28*0.44 = 0.56, rounded to a one-decimal first-print interval of 75.6 to 76.8."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Framing and exact resolver: this is the Federal Reserve G.17 Capacity Utilization: Total Industry series, seasonally adjusted percent of capacity. The target is the first published June 2026 value in the July 17, 2026 G.17 release; the series code mirror is FRED TCU, but resolution is to the Federal Reserve release table.","Prior/update/interval: base rate prior is a near-persistence model for total industry utilization using the recent Federal Reserve/FRED reference class of monthly level changes from Dec 2025 through May 2026: -0.30, +0.54, -0.31, +0.59, +0.04 percentage point, giving sigma = 0.44. Level prior starts at May 2026 TCU 76.1663; momentum adjustment is +0.03 from the positive April-May IP/utilization trend, one-off adjustment is 0.00 because utilities weakness and mining strength offset, and policy-mechanism adjustment is 0.00. Point = 76.1663 + 0.03 = 76.20. 80% half-width is roughly 1.28*sigma = 1.28*0.44 = 0.56, rounded to a one-decimal first-print interval of 75.6 to 76.8."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for June 2026 total industry capacity utilization","Prior/update/interval: base rate prior is a near-persistence model for total industry utilization using the recent Federal Reserve/FRED reference class of monthly level changes from Dec 2025 through May 2026: -0.30, +0.54, -0.31, +0.59, +0.04 percentage point, giving sigma = 0.44. Level prior starts at May 2026 TCU 76.1663; momentum adjustment is +0.03 from the positive April-May IP/utilization trend, one-off adjustment is 0.00 because utilities weakness and mining strength offset, and policy-mechanism adjustment is 0.00. Point = 76.1663 + 0.03 = 76.20. 80% half-width is roughly 1.28*sigma = 1.28*0.44 = 0.56, rounded to a one-decimal first-print interval of 75.6 to 76.8."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: fed-g17-capacity-utilization-total-industry-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-17\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.fed-g17-industrial-production-total-index-mom-june-2026.2026-07-08T16-55-28Z.8ff89b7696efc334","runId":"run.fed-g17-industrial-production-total-index-mom-june-2026.2026-07-08T16-55-28Z.8ff89b7696efc334","predictionId":"fed-g17-industrial-production-total-index-mom-june-2026","specId":"spec.fed-g17-industrial-production-total-index-mom-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: recent G.17 monthly total-index percent changes are centered near modest growth. The seven-observation volatility sample uses latest available current/revised G.17 values, not first-vintage-only history; that is a limitation for a strict first-print target but should still capture typical one-month total-index dispersion. The last seven values Nov 2025-May 2026 are -0.2, 0.5, -0.4, 0.8, -0.3, 0.9, and 0.1, giving a simple recent reference class mean about 0.2 percent, while the latest May reading of 0.1 percent and flat manufacturing argue against extrapolating April's 0.9 percent jump.","Prior/update/interval: persistence/reference-class prior uses recent G.17 total-index percent changes Nov 2025-May 2026: -0.2, 0.5, -0.4, 0.8, -0.3, 0.9, 0.1; mean = 0.2 and sigma = 0.54 from the values themselves for this change series. Half-width = roughly 1.28*sigma = 1.28*0.54 = 0.69. I set point = 0.2, using +0.05 from positive April-May level momentum, -0.05 from flat May manufacturing and possible mining mean reversion, and 0.00 from utilities/weather uncertainty. Rounded first-print-style 80% bounds are 0.2 - 0.69 = -0.49 to 0.2 + 0.69 = 0.89, reported as -0.5 to 0.9."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Counter-considerations: upside risk is a continued rebound in manufacturing or another mining gain like May's 1.3 percent, which would land above the interval if total IP prints above 0.9 percent. Downside risk is a reversal in mining plus weak durable manufacturing or adverse utilities output; that would land below the interval if total IP prints below -0.5 percent."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this targets the Federal Reserve G.17 Summary table, Total index, seasonally adjusted, Percent change, for June 2026. The resolution variant is the first preliminary monthly print, not later revised values; the expected archive page is the July 17, 2026 G.17 release.","Tool call: Checked Federal Reserve G.17 release dates page for the June 2026 reporting month release schedule."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.4, distribution present, forecast step count 1.","evidence":["Tool call: Read the Federal Reserve current G.17 sector detail for the May 2026 release.","Prior/update/interval: persistence/reference-class prior uses recent G.17 total-index percent changes Nov 2025-May 2026: -0.2, 0.5, -0.4, 0.8, -0.3, 0.9, 0.1; mean = 0.2 and sigma = 0.54 from the values themselves for this change series. Half-width = roughly 1.28*sigma = 1.28*0.54 = 0.69. I set point = 0.2, using +0.05 from positive April-May level momentum, -0.05 from flat May manufacturing and possible mining mean reversion, and 0.00 from utilities/weather uncertainty. Rounded first-print-style 80% bounds are 0.2 - 0.69 = -0.49 to 0.2 + 0.69 = 0.89, reported as -0.5 to 0.9."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence/reference-class prior uses recent G.17 total-index percent changes Nov 2025-May 2026: -0.2, 0.5, -0.4, 0.8, -0.3, 0.9, 0.1; mean = 0.2 and sigma = 0.54 from the values themselves for this change series. Half-width = roughly 1.28*sigma = 1.28*0.54 = 0.69. I set point = 0.2, using +0.05 from positive April-May level momentum, -0.05 from flat May manufacturing and possible mining mean reversion, and 0.00 from utilities/weather uncertainty. Rounded first-print-style 80% bounds are 0.2 - 0.69 = -0.49 to 0.2 + 0.69 = 0.89, reported as -0.5 to 0.9.","Review disposition: accepted the clarification that the short volatility sample uses current/revised values rather than first-vintage-only history; rejected adding a longer historical volatility check because no additional fetched longer-sample numbers were available in the draft evidence."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: recent G.17 monthly total-index percent changes are centered near modest growth. The seven-observation volatility sample uses latest available current/revised G.17 values, not first-vintage-only history; that is a limitation for a strict first-print target but should still capture typical one-month total-index dispersion. The last seven values Nov 2025-May 2026 are -0.2, 0.5, -0.4, 0.8, -0.3, 0.9, and 0.1, giving a simple recent reference class mean about 0.2 percent, while the latest May reading of 0.1 percent and flat manufacturing argue against extrapolating April's 0.9 percent jump.","Prior/update/interval: persistence/reference-class prior uses recent G.17 total-index percent changes Nov 2025-May 2026: -0.2, 0.5, -0.4, 0.8, -0.3, 0.9, 0.1; mean = 0.2 and sigma = 0.54 from the values themselves for this change series. Half-width = roughly 1.28*sigma = 1.28*0.54 = 0.69. I set point = 0.2, using +0.05 from positive April-May level momentum, -0.05 from flat May manufacturing and possible mining mean reversion, and 0.00 from utilities/weather uncertainty. Rounded first-print-style 80% bounds are 0.2 - 0.69 = -0.49 to 0.2 + 0.69 = 0.89, reported as -0.5 to 0.9."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for June 2026 total industrial production MoM","Prior/update/interval: persistence/reference-class prior uses recent G.17 total-index percent changes Nov 2025-May 2026: -0.2, 0.5, -0.4, 0.8, -0.3, 0.9, 0.1; mean = 0.2 and sigma = 0.54 from the values themselves for this change series. Half-width = roughly 1.28*sigma = 1.28*0.54 = 0.69. I set point = 0.2, using +0.05 from positive April-May level momentum, -0.05 from flat May manufacturing and possible mining mean reversion, and 0.00 from utilities/weather uncertainty. Rounded first-print-style 80% bounds are 0.2 - 0.69 = -0.49 to 0.2 + 0.69 = 0.89, reported as -0.5 to 0.9."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: fed-g17-industrial-production-total-index-mom-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-17\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.cms-medicaid-pi-beneficiaries-renewed-ex-parte-california-june-2026.2026-07-08T16-44-56Z.3999f509a690c383","runId":"run.cms-medicaid-pi-beneficiaries-renewed-ex-parte-california-june-2026.2026-07-08T16-44-56Z.3999f509a690c383","predictionId":"cms-medicaid-pi-beneficiaries-renewed-ex-parte-california-june-2026","specId":"spec.cms-medicaid-pi-beneficiaries-renewed-ex-parte-california-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Tool call: Opened Data.Medicaid.gov filtered dataset for reporting_period 202601 and preliminary_or_updated U, and checked adjacent updated historical rows for California.","Reference class and base rate: the recent official-source reference class is California monthly beneficiaries renewed ex parte in the same CMS PI dataset and same state-row count variant. The six-point recent level base rate is (663,214 + 700,835 + 741,092 + 758,446 + 691,238 + 706,884) / 6 = 710,285."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Resolution-date support: CMS's public monthly reports page identifies the official monthly application, eligibility, and enrollment report releases and listed the March 2026 preliminary and February 2026 updated release as Last Updated June 26, 2026. The 2026-09-25 date is the official September 2026 posting date used for the June 2026 preliminary first print under that monthly CMS release schedule.","Reference class and base rate: the recent official-source reference class is California monthly beneficiaries renewed ex parte in the same CMS PI dataset and same state-row count variant. The six-point recent level base rate is (663,214 + 700,835 + 741,092 + 758,446 + 691,238 + 706,884) / 6 = 710,285."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this is the California state row, count unit, for beneficiaries renewed on an ex parte basis in CMS dataset 6165f45b-ca93-5bb5-9d06-db29c692a360, reporting_period 202606, preliminary_or_updated P. The target is a first-print preliminary vintage, not a later updated row.","Resolution-date support: CMS's public monthly reports page identifies the official monthly application, eligibility, and enrollment report releases and listed the March 2026 preliminary and February 2026 updated release as Last Updated June 26, 2026. The 2026-09-25 date is the official September 2026 posting date used for the June 2026 preliminary first print under that monthly CMS release schedule."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 112000, distribution present, forecast step count 1.","evidence":["Variant discipline: anchors and history use the same Applications, Eligibility, and Enrollment Performance Indicator data, California state row, beneficiaries renewed ex parte, count unit. The target is preliminary June 2026 first print; preliminary historical rows for all adjacent months were not retained in the fetched current public table, so updated rows are used as an official same-series proxy and the interval intentionally includes first-print vintage error.","Prior/update/interval: persistence prior = recent six-month mean 710,285 from 2025-10 through 2026-03; momentum adjustment = +7,000 because March rebounded 15,646 from February and California's ex parte process has been stable; level/policy adjustment = 0 because no official California mechanism found that would sharply change June ex parte automation; first-print vintage adjustment = +700, giving point about 718,000. Successive changes are +37,621, +40,257, +17,354, -67,208, +15,646, so sample sigma = 43,920. 80% half-width = 1.28*sigma = 56,218, rounded to 56,000; this band is left broad enough to cover both monthly movement and preliminary-vs-updated vintage noise. 718,000 - 56,000 = 662,000 and 718,000 + 56,000 = 774,000."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior = recent six-month mean 710,285 from 2025-10 through 2026-03; momentum adjustment = +7,000 because March rebounded 15,646 from February and California's ex parte process has been stable; level/policy adjustment = 0 because no official California mechanism found that would sharply change June ex parte automation; first-print vintage adjustment = +700, giving point about 718,000. Successive changes are +37,621, +40,257, +17,354, -67,208, +15,646, so sample sigma = 43,920. 80% half-width = 1.28*sigma = 56,218, rounded to 56,000; this band is left broad enough to cover both monthly movement and preliminary-vs-updated vintage noise. 718,000 - 56,000 = 662,000 and 718,000 + 56,000 = 774,000."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-considerations: upside risk is a larger June renewal batch or a higher automated-renewal share, which would land above the interval if California posts more than about 774,000 ex parte renewals. Downside risk is delayed state reporting, more beneficiary-action renewals, or a smaller June renewal cohort, which would land below the interval if the first print is under about 662,000."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Reference class and base rate: the recent official-source reference class is California monthly beneficiaries renewed ex parte in the same CMS PI dataset and same state-row count variant. The six-point recent level base rate is (663,214 + 700,835 + 741,092 + 758,446 + 691,238 + 706,884) / 6 = 710,285.","Variant discipline: anchors and history use the same Applications, Eligibility, and Enrollment Performance Indicator data, California state row, beneficiaries renewed ex parte, count unit. The target is preliminary June 2026 first print; preliminary historical rows for all adjacent months were not retained in the fetched current public table, so updated rows are used as an official same-series proxy and the interval intentionally includes first-print vintage error."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: cms-medicaid-pi-beneficiaries-renewed-ex-parte-california-june-2026\nrunLabel: Headline\nresolutionDate: 2026-09-25\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.cms-medicaid-pi-beneficiaries-renewed-total-california-june-2026.2026-07-08T00-00-00Z.c7ff8a760d396a07","runId":"run.cms-medicaid-pi-beneficiaries-renewed-total-california-june-2026.2026-07-08T00-00-00Z.c7ff8a760d396a07","predictionId":"cms-medicaid-pi-beneficiaries-renewed-total-california-june-2026","specId":"spec.cms-medicaid-pi-beneficiaries-renewed-total-california-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: recent California preliminary renewal-count proxies from the same CMS variant are 579,505, 534,927, 658,420, 580,613, 561,724, and 600,531 for October 2025 through March 2026, computed from official due counts times official rounded total-renewed percentages.","Prior/update/interval: persistence prior is the six-month same-variant California proxy mean of 585,953 beneficiaries, with a small upward adjustment because March improved to about 600,531 and February-March were more stable than January. Level effect +4,000, momentum +6,000, and a judgmental policy/reporting offset -6,000 gives point 590,000; the offset is intentionally small because the observed evidence is mainly rounded-percent proxy history, not a concrete new California policy change. For this flow series, interval dispersion uses the six due-count-times-rounded-percent proxy values themselves: sigma = 41,800 beneficiaries; 80% base half-width = 1.28*41,800 = 53,500. I add a 6,500 beneficiary measurement/reporting allowance for rounded CMS percentages and possible first-print component-count availability, giving a rounded 60,000 half-width, so bounds are 590,000 - 60,000 = 530,000 and 590,000 + 60,000 = 650,000."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 8 source-context item(s), activity log present.","evidence":["Tool call: Opened CMS Medicaid and CHIP Eligibility Operations and Enrollment Snapshot page for release timing and data-source description.","Base rate/reference class: recent California preliminary renewal-count proxies from the same CMS variant are 579,505, 534,927, 658,420, 580,613, 561,724, and 600,531 for October 2025 through March 2026, computed from official due counts times official rounded total-renewed percentages."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this is the California state row, reporting period 2026-06, preliminary first-print Eligibility Processing Data measure for total beneficiaries renewed in Medicaid/CHIP coverage. It is not the national total, not a weighted average, and not the later updated quarterly vintage.","Tool call: Opened CMS Medicaid and CHIP Eligibility Operations and Enrollment Snapshot page for release timing and data-source description."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 120000, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is the six-month same-variant California proxy mean of 585,953 beneficiaries, with a small upward adjustment because March improved to about 600,531 and February-March were more stable than January. Level effect +4,000, momentum +6,000, and a judgmental policy/reporting offset -6,000 gives point 590,000; the offset is intentionally small because the observed evidence is mainly rounded-percent proxy history, not a concrete new California policy change. For this flow series, interval dispersion uses the six due-count-times-rounded-percent proxy values themselves: sigma = 41,800 beneficiaries; 80% base half-width = 1.28*41,800 = 53,500. I add a 6,500 beneficiary measurement/reporting allowance for rounded CMS percentages and possible first-print component-count availability, giving a rounded 60,000 half-width, so bounds are 590,000 - 60,000 = 530,000 and 590,000 + 60,000 = 650,000.","Counter-consideration: upside risk is California due volume returning above 1.1 million with retention near 60%, which would land above the interval; downside risk is a June cohort closer to 900,000 due or renewed share near January's 51%, which would land below the interval; outside the interval would most likely reflect a reporting-method change or a large shift in pending renewals."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior is the six-month same-variant California proxy mean of 585,953 beneficiaries, with a small upward adjustment because March improved to about 600,531 and February-March were more stable than January. Level effect +4,000, momentum +6,000, and a judgmental policy/reporting offset -6,000 gives point 590,000; the offset is intentionally small because the observed evidence is mainly rounded-percent proxy history, not a concrete new California policy change. For this flow series, interval dispersion uses the six due-count-times-rounded-percent proxy values themselves: sigma = 41,800 beneficiaries; 80% base half-width = 1.28*41,800 = 53,500. I add a 6,500 beneficiary measurement/reporting allowance for rounded CMS percentages and possible first-print component-count availability, giving a rounded 60,000 half-width, so bounds are 590,000 - 60,000 = 530,000 and 590,000 + 60,000 = 650,000."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence prior is the six-month same-variant California proxy mean of 585,953 beneficiaries, with a small upward adjustment because March improved to about 600,531 and February-March were more stable than January. Level effect +4,000, momentum +6,000, and a judgmental policy/reporting offset -6,000 gives point 590,000; the offset is intentionally small because the observed evidence is mainly rounded-percent proxy history, not a concrete new California policy change. For this flow series, interval dispersion uses the six due-count-times-rounded-percent proxy values themselves: sigma = 41,800 beneficiaries; 80% base half-width = 1.28*41,800 = 53,500. I add a 6,500 beneficiary measurement/reporting allowance for rounded CMS percentages and possible first-print component-count availability, giving a rounded 60,000 half-width, so bounds are 590,000 - 60,000 = 530,000 and 590,000 + 60,000 = 650,000.","Counter-consideration: upside risk is California due volume returning above 1.1 million with retention near 60%, which would land above the interval; downside risk is a June cohort closer to 900,000 due or renewed share near January's 51%, which would land below the interval; outside the interval would most likely reflect a reporting-method change or a large shift in pending renewals."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["California June 2026 Medicaid renewal count forecast","Prior/update/interval: persistence prior is the six-month same-variant California proxy mean of 585,953 beneficiaries, with a small upward adjustment because March improved to about 600,531 and February-March were more stable than January. Level effect +4,000, momentum +6,000, and a judgmental policy/reporting offset -6,000 gives point 590,000; the offset is intentionally small because the observed evidence is mainly rounded-percent proxy history, not a concrete new California policy change. For this flow series, interval dispersion uses the six due-count-times-rounded-percent proxy values themselves: sigma = 41,800 beneficiaries; 80% base half-width = 1.28*41,800 = 53,500. I add a 6,500 beneficiary measurement/reporting allowance for rounded CMS percentages and possible first-print component-count availability, giving a rounded 60,000 half-width, so bounds are 590,000 - 60,000 = 530,000 and 590,000 + 60,000 = 650,000."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: cms-medicaid-pi-beneficiaries-renewed-total-california-june-2026\nrunLabel: Headline\nresolutionDate: 2026-09-25\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bls-ppi-final-demand-monthly-change-june-2026.2026-07-07T22-09-46Z.db0f9653da7f4304","runId":"run.bls-ppi-final-demand-monthly-change-june-2026.2026-07-07T22-09-46Z.db0f9653da7f4304","predictionId":"bls-ppi-final-demand-monthly-change-june-2026","specId":"spec.bls-ppi-final-demand-monthly-change-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate and reference class: the May 2025-May 2026 headline final-demand monthly changes average about 0.51 percent. I use that outside-view anchor before updating for the latest two prints at 1.1 percent and the component mix.","Prior/update/interval: model is a 13-month historical base-rate plus two-month persistence prior. Historical sample is BLS Table A May 2025-May 2026 total final demand values [0.3, 0.2, 0.8, -0.2, 0.6, 0.1, 0.4, 0.4, 0.6, 0.5, 0.7, 1.1, 1.1], mean = 0.51 and sample sigma = 0.37. Adjustment components: +0.20 for April-May persistence and broad goods/core firmness, -0.05 for expected partial energy/gasoline mean reversion, +0.04 for services/core carry-through, giving 0.70. 80% interval method: values themselves are the change-series dispersion, so 80% half-width is roughly 1.28*sigma = 1.28*0.37 = 0.47, rounded to 0.5; final implied bounds are 0.7 - 0.5 = 0.2 and 0.7 + 0.5 = 1.2."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Forecast for June 2026 BLS PPI Final Demand","Framing and exact resolver: this targets the BLS Producer Price Index for final demand, seasonally adjusted, month-over-month percent change for June 2026, resolved on the first official print in the Producer Price Index news release. The variant is the headline final demand SA monthly percent change, not NSA 12-month change, not core, and not final demand goods or services."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this targets the BLS Producer Price Index for final demand, seasonally adjusted, month-over-month percent change for June 2026, resolved on the first official print in the Producer Price Index news release. The variant is the headline final demand SA monthly percent change, not NSA 12-month change, not core, and not final demand goods or services.","Tool call: BLS release calendar lookup for July 2026 Producer Price Index release"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1, distribution present, forecast step count 1.","evidence":["Prior/update/interval: model is a 13-month historical base-rate plus two-month persistence prior. Historical sample is BLS Table A May 2025-May 2026 total final demand values [0.3, 0.2, 0.8, -0.2, 0.6, 0.1, 0.4, 0.4, 0.6, 0.5, 0.7, 1.1, 1.1], mean = 0.51 and sample sigma = 0.37. Adjustment components: +0.20 for April-May persistence and broad goods/core firmness, -0.05 for expected partial energy/gasoline mean reversion, +0.04 for services/core carry-through, giving 0.70. 80% interval method: values themselves are the change-series dispersion, so 80% half-width is roughly 1.28*sigma = 1.28*0.37 = 0.47, rounded to 0.5; final implied bounds are 0.7 - 0.5 = 0.2 and 0.7 + 0.5 = 1.2.","Counter-consideration: upside risk is another large June energy or gasoline pass-through plus firm portfolio-management and transportation services, which would land above the interval if headline final demand prints above 1.2 percent. Downside risk is a sharp reversal in gasoline, crude, or trade-service margins, which would land below the interval if headline final demand prints below 0.2 percent."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Update from current-release evidence: I anchor below pure two-month persistence because much of May was an energy/gasoline one-off, but above the 12-month mean because goods, energy, and core-ex-trade momentum were all firm."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Update from current-release evidence: I anchor below pure two-month persistence because much of May was an energy/gasoline one-off, but above the 12-month mean because goods, energy, and core-ex-trade momentum were all firm.","Counter-consideration: upside risk is another large June energy or gasoline pass-through plus firm portfolio-management and transportation services, which would land above the interval if headline final demand prints above 1.2 percent. Downside risk is a sharp reversal in gasoline, crude, or trade-service margins, which would land below the interval if headline final demand prints below 0.2 percent."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for June 2026 BLS PPI Final Demand","Prior/update/interval: model is a 13-month historical base-rate plus two-month persistence prior. Historical sample is BLS Table A May 2025-May 2026 total final demand values [0.3, 0.2, 0.8, -0.2, 0.6, 0.1, 0.4, 0.4, 0.6, 0.5, 0.7, 1.1, 1.1], mean = 0.51 and sample sigma = 0.37. Adjustment components: +0.20 for April-May persistence and broad goods/core firmness, -0.05 for expected partial energy/gasoline mean reversion, +0.04 for services/core carry-through, giving 0.70. 80% interval method: values themselves are the change-series dispersion, so 80% half-width is roughly 1.28*sigma = 1.28*0.37 = 0.47, rounded to 0.5; final implied bounds are 0.7 - 0.5 = 0.2 and 0.7 + 0.5 = 1.2."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bls-ppi-final-demand-monthly-change-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-15\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bls-ppi-final-demand-monthly-change-june-2026.2026-07-08T02-51-00Z.bls-ppi-final-demand-monthly-change-june-2026-thesis-analyst-fast-2026-07-08t02-51-00z.db0f9653da7f4304","runId":"run.bls-ppi-final-demand-monthly-change-june-2026.2026-07-08T02-51-00Z.bls-ppi-final-demand-monthly-change-june-2026-thesis-analyst-fast-2026-07-08t02-51-00z.db0f9653da7f4304","predictionId":"bls-ppi-final-demand-monthly-change-june-2026","specId":"spec.bls-ppi-final-demand-monthly-change-june-2026","runLabel":"Fast rollout 1 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate and reference class: the May 2025-May 2026 headline final-demand monthly changes average about 0.51 percent. I use that outside-view anchor before updating for the latest two prints at 1.1 percent and the component mix.","Prior/update/interval: model is a 13-month historical base-rate plus two-month persistence prior. Historical sample is BLS Table A May 2025-May 2026 total final demand values [0.3, 0.2, 0.8, -0.2, 0.6, 0.1, 0.4, 0.4, 0.6, 0.5, 0.7, 1.1, 1.1], mean = 0.51 and sample sigma = 0.37. Adjustment components: +0.20 for April-May persistence and broad goods/core firmness, -0.05 for expected partial energy/gasoline mean reversion, +0.04 for services/core carry-through, giving 0.70. 80% interval method: values themselves are the change-series dispersion, so 80% half-width is roughly 1.28*sigma = 1.28*0.37 = 0.47, rounded to 0.5; final implied bounds are 0.7 - 0.5 = 0.2 and 0.7 + 0.5 = 1.2."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Forecast for June 2026 BLS PPI Final Demand","Framing and exact resolver: this targets the BLS Producer Price Index for final demand, seasonally adjusted, month-over-month percent change for June 2026, resolved on the first official print in the Producer Price Index news release. The variant is the headline final demand SA monthly percent change, not NSA 12-month change, not core, and not final demand goods or services."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this targets the BLS Producer Price Index for final demand, seasonally adjusted, month-over-month percent change for June 2026, resolved on the first official print in the Producer Price Index news release. The variant is the headline final demand SA monthly percent change, not NSA 12-month change, not core, and not final demand goods or services.","Tool call: BLS release calendar lookup for the Producer Price Index June 2026 reference month"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1, distribution present, forecast step count 1.","evidence":["Prior/update/interval: model is a 13-month historical base-rate plus two-month persistence prior. Historical sample is BLS Table A May 2025-May 2026 total final demand values [0.3, 0.2, 0.8, -0.2, 0.6, 0.1, 0.4, 0.4, 0.6, 0.5, 0.7, 1.1, 1.1], mean = 0.51 and sample sigma = 0.37. Adjustment components: +0.20 for April-May persistence and broad goods/core firmness, -0.05 for expected partial energy/gasoline mean reversion, +0.04 for services/core carry-through, giving 0.70. 80% interval method: values themselves are the change-series dispersion, so 80% half-width is roughly 1.28*sigma = 1.28*0.37 = 0.47, rounded to 0.5; final implied bounds are 0.7 - 0.5 = 0.2 and 0.7 + 0.5 = 1.2.","Prior-run context: I inspected a generated public Thesis record from 2026-07-07 for this same target only as strategy context; it used the same BLS release and calendar evidence, so I keep the same point and interval after re-verifying the official calendar and current BLS release this run."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Update from current-release evidence: I anchor below pure two-month persistence because much of May was an energy/gasoline one-off, but above the 12-month mean because goods, energy, transportation, and core-ex-trade momentum were all firm."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Update from current-release evidence: I anchor below pure two-month persistence because much of May was an energy/gasoline one-off, but above the 12-month mean because goods, energy, transportation, and core-ex-trade momentum were all firm.","Counter-consideration: upside risk is another large June energy or gasoline pass-through plus firm portfolio-management and transportation services, which would land above the interval if headline final demand prints above 1.2 percent. Downside risk is a sharp reversal in gasoline, crude, or trade-service margins, which would land below the interval if headline final demand prints below 0.2 percent."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for June 2026 BLS PPI Final Demand","Prior/update/interval: model is a 13-month historical base-rate plus two-month persistence prior. Historical sample is BLS Table A May 2025-May 2026 total final demand values [0.3, 0.2, 0.8, -0.2, 0.6, 0.1, 0.4, 0.4, 0.6, 0.5, 0.7, 1.1, 1.1], mean = 0.51 and sample sigma = 0.37. Adjustment components: +0.20 for April-May persistence and broad goods/core firmness, -0.05 for expected partial energy/gasoline mean reversion, +0.04 for services/core carry-through, giving 0.70. 80% interval method: values themselves are the change-series dispersion, so 80% half-width is roughly 1.28*sigma = 1.28*0.37 = 0.47, rounded to 0.5; final implied bounds are 0.7 - 0.5 = 0.2 and 0.7 + 0.5 = 1.2."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bls-ppi-final-demand-monthly-change-june-2026\nrunLabel: Fast rollout 1 of 3\nresolutionDate: 2026-07-15\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bls-ppi-final-demand-monthly-change-june-2026.2026-07-08T02-51-24Z.bls-ppi-final-demand-monthly-change-june-2026-thesis-analyst-fast-2026-07-08t02-51-24z.cce066373d0d9d90","runId":"run.bls-ppi-final-demand-monthly-change-june-2026.2026-07-08T02-51-24Z.bls-ppi-final-demand-monthly-change-june-2026-thesis-analyst-fast-2026-07-08t02-51-24z.cce066373d0d9d90","predictionId":"bls-ppi-final-demand-monthly-change-june-2026","specId":"spec.bls-ppi-final-demand-monthly-change-june-2026","runLabel":"Fast rollout 2 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the outside view is the 13-month BLS Table A distribution for the same seasonally adjusted final-demand series, centered near +0.51 percent with a recent shock tail. A simple persistence-only forecast from the last two prints would be +1.1 percent, but the component mix argues against repeating the full May energy impulse.","Prior/update/interval: persistence-plus-reference-class prior uses the BLS May 2025-May 2026 WPSFD4 same-variant sample. Base mean = 0.5077; persistence signal from Apr-May = 1.1; one-off energy/gasoline mean-reversion adjustment = -0.3 to -0.5 versus persistence; services/core floor adjustment = +0.1 versus the base rate. Final point = 0.6. For this change/flow series, sigma is the sample stdev of the values themselves: sigma = 0.373 from [0.3, 0.2, 0.8, -0.2, 0.6, 0.1, 0.4, 0.4, 0.6, 0.5, 0.7, 1.1, 1.1]. 80 percent half-width = 1.28*sigma = 1.28*0.373 = 0.477, so 0.6 +/- 0.477 gives [0.1226, 1.0774], rounded to [0.1, 1.1]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this forecast is for BLS Producer Price Index final demand, seasonally adjusted, monthly percent change for June 2026, series WPSFD4. The resolution is the first printed one-decimal BLS value, not later revised PPI history.","Tool call: BLS PPI release calendar lookup for the June 2026 reference month"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this forecast is for BLS Producer Price Index final demand, seasonally adjusted, monthly percent change for June 2026, series WPSFD4. The resolution is the first printed one-decimal BLS value, not later revised PPI history.","Tool call: BLS PPI release calendar lookup for the June 2026 reference month"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1, distribution present, forecast step count 1.","evidence":["Tool call: BLS final demand component details from the May 2026 release and Table 2","Base rate/reference class: the outside view is the 13-month BLS Table A distribution for the same seasonally adjusted final-demand series, centered near +0.51 percent with a recent shock tail. A simple persistence-only forecast from the last two prints would be +1.1 percent, but the component mix argues against repeating the full May energy impulse."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Mechanism split: the level of pipeline inflation is high, momentum is elevated after two +1.1 percent months, the one-off May gasoline jump should mean-revert partly, and the policy/rate environment does not mechanically cap producer prices before the June survey month. I therefore put the point above the 13-month mean but below the April-May pace."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: the outside view is the 13-month BLS Table A distribution for the same seasonally adjusted final-demand series, centered near +0.51 percent with a recent shock tail. A simple persistence-only forecast from the last two prints would be +1.1 percent, but the component mix argues against repeating the full May energy impulse.","Mechanism split: the level of pipeline inflation is high, momentum is elevated after two +1.1 percent months, the one-off May gasoline jump should mean-revert partly, and the policy/rate environment does not mechanically cap producer prices before the June survey month. I therefore put the point above the 13-month mean but below the April-May pace."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Framing and exact resolver: this forecast is for BLS Producer Price Index final demand, seasonally adjusted, monthly percent change for June 2026, series WPSFD4. The resolution is the first printed one-decimal BLS value, not later revised PPI history.","Base rate/reference class: the outside view is the 13-month BLS Table A distribution for the same seasonally adjusted final-demand series, centered near +0.51 percent with a recent shock tail. A simple persistence-only forecast from the last two prints would be +1.1 percent, but the component mix argues against repeating the full May energy impulse."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bls-ppi-final-demand-monthly-change-june-2026\nrunLabel: Fast rollout 2 of 3\nresolutionDate: 2026-07-15\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bls-ppi-final-demand-monthly-change-june-2026.2026-07-08T02-52-43Z.bls-ppi-final-demand-monthly-change-june-2026-thesis-analyst-fast-2026-07-08t02-52-43z.db0f9653da7f4304","runId":"run.bls-ppi-final-demand-monthly-change-june-2026.2026-07-08T02-52-43Z.bls-ppi-final-demand-monthly-change-june-2026-thesis-analyst-fast-2026-07-08t02-52-43z.db0f9653da7f4304","predictionId":"bls-ppi-final-demand-monthly-change-june-2026","specId":"spec.bls-ppi-final-demand-monthly-change-june-2026","runLabel":"Fast rollout 3 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate and reference class: the May 2025-May 2026 headline final-demand monthly changes average 0.51 percent. I anchor on that outside view before updating for the latest two 1.1 percent prints and the component split.","Prior/update/interval: model is a 13-month historical base-rate plus two-month persistence prior. Historical sample is BLS Table A May 2025-May 2026 total final demand values [0.3, 0.2, 0.8, -0.2, 0.6, 0.1, 0.4, 0.4, 0.6, 0.5, 0.7, 1.1, 1.1], mean = 0.51 and sigma = 0.37. Adjustment components: +0.20 for April-May persistence and broad goods/core firmness, -0.05 for expected partial energy/gasoline mean reversion, +0.04 for services/core carry-through, giving 0.70. 80% interval method: values themselves are the change-series dispersion, so half-width is roughly 1.28*sigma = 1.28*0.37 = 0.47, rounded to 0.5; final implied bounds are 0.7 - 0.5 = 0.2 and 0.7 + 0.5 = 1.2."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 2 source-context item(s), activity log present.","evidence":["Forecast for June 2026 BLS PPI Final Demand","Framing and exact resolver: this targets the BLS Producer Price Index for final demand, seasonally adjusted, month-over-month percent change for June 2026, resolved on the first official print in the Producer Price Index news release. The variant is the headline final demand SA monthly percent change, series code WPSFD4, not the NSA 12-month change, not core PPI, and not final demand goods or services."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this targets the BLS Producer Price Index for final demand, seasonally adjusted, month-over-month percent change for June 2026, resolved on the first official print in the Producer Price Index news release. The variant is the headline final demand SA monthly percent change, series code WPSFD4, not the NSA 12-month change, not core PPI, and not final demand goods or services.","Tool call: BLS release calendar lookup for the Producer Price Index June 2026 reference month"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1, distribution present, forecast step count 1.","evidence":["Prior/update/interval: model is a 13-month historical base-rate plus two-month persistence prior. Historical sample is BLS Table A May 2025-May 2026 total final demand values [0.3, 0.2, 0.8, -0.2, 0.6, 0.1, 0.4, 0.4, 0.6, 0.5, 0.7, 1.1, 1.1], mean = 0.51 and sigma = 0.37. Adjustment components: +0.20 for April-May persistence and broad goods/core firmness, -0.05 for expected partial energy/gasoline mean reversion, +0.04 for services/core carry-through, giving 0.70. 80% interval method: values themselves are the change-series dispersion, so half-width is roughly 1.28*sigma = 1.28*0.37 = 0.47, rounded to 0.5; final implied bounds are 0.7 - 0.5 = 0.2 and 0.7 + 0.5 = 1.2.","Counter-consideration: upside risk is another large June energy or gasoline pass-through plus firm portfolio-management and transportation services, which would land above the interval if headline final demand prints above 1.2 percent. Downside risk is a sharp reversal in gasoline, crude, or trade-service margins, which would land below the interval if headline final demand prints below 0.2 percent."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Update from current-release evidence: April and May point to strong near-term momentum, especially goods and energy, but the May composition was partly a gasoline and energy shock, so I do not project a full repeat. Services at 0.3 percent pulls the forecast below pure two-month persistence."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Update from current-release evidence: April and May point to strong near-term momentum, especially goods and energy, but the May composition was partly a gasoline and energy shock, so I do not project a full repeat. Services at 0.3 percent pulls the forecast below pure two-month persistence.","Counter-consideration: upside risk is another large June energy or gasoline pass-through plus firm portfolio-management and transportation services, which would land above the interval if headline final demand prints above 1.2 percent. Downside risk is a sharp reversal in gasoline, crude, or trade-service margins, which would land below the interval if headline final demand prints below 0.2 percent."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for June 2026 BLS PPI Final Demand","Update from current-release evidence: April and May point to strong near-term momentum, especially goods and energy, but the May composition was partly a gasoline and energy shock, so I do not project a full repeat. Services at 0.3 percent pulls the forecast below pure two-month persistence."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bls-ppi-final-demand-monthly-change-june-2026\nrunLabel: Fast rollout 3 of 3\nresolutionDate: 2026-07-15\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bls-ppi-final-demand-monthly-change-june-2026.2026-07-08T02-58-17Z.bls-ppi-final-demand-monthly-change-june-2026-thesis-analyst-ladder-2026-07-08t02-58-17z.651f68f8968d0539","runId":"run.bls-ppi-final-demand-monthly-change-june-2026.2026-07-08T02-58-17Z.bls-ppi-final-demand-monthly-change-june-2026-thesis-analyst-ladder-2026-07-08t02-58-17z.651f68f8968d0539","predictionId":"bls-ppi-final-demand-monthly-change-june-2026","specId":"spec.bls-ppi-final-demand-monthly-change-june-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate and reference class: the outside-view anchor is the May 2025-May 2026 BLS Table A sample of headline final-demand monthly changes, with mean 0.51 percent, before updating for the latest two 1.1 percent prints and component mix.","Current-release update: the two-month headline run rate argues above the base rate, but May's goods shock was heavily energy and gasoline driven, so I do not carry the full April-May pace into June."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Forecast for June 2026 BLS PPI Final Demand","Framing and exact resolver: this targets the BLS Producer Price Index for final demand, seasonally adjusted, month-over-month percent change for June 2026, resolved on the first official print in the Producer Price Index news release. The variant is the headline final demand SA monthly percent change, not NSA 12-month change, not core, and not final demand goods or services."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this targets the BLS Producer Price Index for final demand, seasonally adjusted, month-over-month percent change for June 2026, resolved on the first official print in the Producer Price Index news release. The variant is the headline final demand SA monthly percent change, not NSA 12-month change, not core, and not final demand goods or services.","Tool call: BLS Producer Price Index release schedule lookup for the June 2026 reference month using the official PPI schedule page"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1, distribution present, forecast step count 1.","evidence":["Prior/update/interval: model is a 13-month historical base-rate plus two-month persistence prior. Historical sample is BLS Table A May 2025-May 2026 total final demand values [0.3, 0.2, 0.8, -0.2, 0.6, 0.1, 0.4, 0.4, 0.6, 0.5, 0.7, 1.1, 1.1], mean = 0.51 and sigma = 0.37. Adjustment components: +0.20 for April-May persistence and broad goods/core firmness, -0.05 for expected partial energy/gasoline mean reversion, +0.04 for services/core carry-through, giving 0.70. 80% interval method: values themselves are the change-series dispersion, so 80% half-width is roughly 1.28*sigma = 1.28*0.37 = 0.47; the ladder-implied half-width is about 0.5, effectively the same after one-decimal rounding, with final implied bounds 0.2 and 1.2. I used the short post-2025 sample because it matches the current high-inflation, high-volatility regime evident in the official recent release, rather than mixing in calmer earlier years.","Counter-consideration: upside risk is another large June energy or gasoline pass-through plus firm portfolio-management and transportation services, which would land above the interval if headline final demand prints above 1.2 percent. Downside risk is a sharp reversal in gasoline, crude, or trade-service margins, which would land below the interval if headline final demand prints below 0.2 percent."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and policy-mechanism split: level is elevated because the 12-month final demand change reached 6.5 percent; momentum is strong in headline and core-ex-trade; the main one-off is May gasoline and energy; monetary-policy pressure is more likely to restrain future demand than the first June input-cost print.","Prior/update/interval: model is a 13-month historical base-rate plus two-month persistence prior. Historical sample is BLS Table A May 2025-May 2026 total final demand values [0.3, 0.2, 0.8, -0.2, 0.6, 0.1, 0.4, 0.4, 0.6, 0.5, 0.7, 1.1, 1.1], mean = 0.51 and sigma = 0.37. Adjustment components: +0.20 for April-May persistence and broad goods/core firmness, -0.05 for expected partial energy/gasoline mean reversion, +0.04 for services/core carry-through, giving 0.70. 80% interval method: values themselves are the change-series dispersion, so 80% half-width is roughly 1.28*sigma = 1.28*0.37 = 0.47; the ladder-implied half-width is about 0.5, effectively the same after one-decimal rounding, with final implied bounds 0.2 and 1.2. I used the short post-2025 sample because it matches the current high-inflation, high-volatility regime evident in the official recent release, rather than mixing in calmer earlier years."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Current-release update: the two-month headline run rate argues above the base rate, but May's goods shock was heavily energy and gasoline driven, so I do not carry the full April-May pace into June.","Counter-consideration: upside risk is another large June energy or gasoline pass-through plus firm portfolio-management and transportation services, which would land above the interval if headline final demand prints above 1.2 percent. Downside risk is a sharp reversal in gasoline, crude, or trade-service margins, which would land below the interval if headline final demand prints below 0.2 percent."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for June 2026 BLS PPI Final Demand","Prior/update/interval: model is a 13-month historical base-rate plus two-month persistence prior. Historical sample is BLS Table A May 2025-May 2026 total final demand values [0.3, 0.2, 0.8, -0.2, 0.6, 0.1, 0.4, 0.4, 0.6, 0.5, 0.7, 1.1, 1.1], mean = 0.51 and sigma = 0.37. Adjustment components: +0.20 for April-May persistence and broad goods/core firmness, -0.05 for expected partial energy/gasoline mean reversion, +0.04 for services/core carry-through, giving 0.70. 80% interval method: values themselves are the change-series dispersion, so 80% half-width is roughly 1.28*sigma = 1.28*0.37 = 0.47; the ladder-implied half-width is about 0.5, effectively the same after one-decimal rounding, with final implied bounds 0.2 and 1.2. I used the short post-2025 sample because it matches the current high-inflation, high-volatility regime evident in the official recent release, rather than mixing in calmer earlier years."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bls-ppi-final-demand-monthly-change-june-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-07-15\ntraceLineCount: 20\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bls-ppi-final-demand-monthly-change-june-2026.2026-07-08T03-03-42Z.bls-ppi-final-demand-monthly-change-june-2026-thesis-analyst-median3-2026-07-08t03-03-42z.78f8fc1efdfd3e31","runId":"run.bls-ppi-final-demand-monthly-change-june-2026.2026-07-08T03-03-42Z.bls-ppi-final-demand-monthly-change-june-2026-thesis-analyst-median3-2026-07-08t03-03-42z.78f8fc1efdfd3e31","predictionId":"bls-ppi-final-demand-monthly-change-june-2026","specId":"spec.bls-ppi-final-demand-monthly-change-june-2026","runLabel":"Median of 3 rollouts","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 5 historical point(s) and implicit outside-view language.","evidence":["Median-of-3 rollout ensemble","Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-08T02:51:00Z, 2026-07-08T02:51:24Z, 2026-07-08T02:52:43Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Median CDF quantiles: q10 = 0.2, q50 = 0.7, q90 = 1.2. Constituent points [0.7, 0.6, 0.7] with 80% widths [1.0, 1.0, 1.0]; the median interval inherits the central rollout mass rather than averaging tails."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1, distribution present, forecast step count 1.","evidence":["Median CDF quantiles: q10 = 0.2, q50 = 0.7, q90 = 1.2. Constituent points [0.7, 0.6, 0.7] with 80% widths [1.0, 1.0, 1.0]; the median interval inherits the central rollout mass rather than averaging tails.","Forecast: point 0.7, 80% interval [0.2, 1.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-08T02:51:00Z, 2026-07-08T02:51:24Z, 2026-07-08T02:52:43Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-08T02:51:00Z, 2026-07-08T02:51:24Z, 2026-07-08T02:52:43Z. Drivers and resolver fields mirror the rollout closest to the median.","Tool result: {rollout_points: [0.7, 0.6, 0.7], rollout_widths: [1.0, 1.0, 1.0], q10: 0.2, q50: 0.7, q90: 1.2}"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bls-ppi-final-demand-monthly-change-june-2026\nrunLabel: Median of 3 rollouts\nresolutionDate: 2026-07-15\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.uk-manufacturing-output-index-may-2026.2026-07-07T18-25-05Z.5add07a1f03d6a27","runId":"run.uk-manufacturing-output-index-may-2026.2026-07-07T18-25-05Z.5add07a1f03d6a27","predictionId":"uk-manufacturing-output-index-may-2026","specId":"spec.uk-manufacturing-output-index-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Framing and exact resolver: this forecast targets ONS DIOP time series K22A, labelled IOP: C:MANUFACTURING: CVMSA. All anchors use the same chained volume measure, seasonally adjusted manufacturing index variant, base year 2023=100, not gross, non-seasonally adjusted, smoothed, or synthetic variants.","Tool result: The ONS page identified Series ID K22A, units index base year = 100, release date 12 June 2026, next release 16 July 2026, and recent monthly values 2026 JAN 100.1, 2026 FEB 99.9, 2026 MAR 101.1, 2026 APR 101.5."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this forecast targets ONS DIOP time series K22A, labelled IOP: C:MANUFACTURING: CVMSA. All anchors use the same chained volume measure, seasonally adjusted manufacturing index variant, base year 2023=100, not gross, non-seasonally adjusted, smoothed, or synthetic variants.","Tool call: Opened the ONS K22A time-series page for DIOP manufacturing CVMSA index."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["UK manufacturing output index, May 2026 first print","Tool result: The ONS page identified Series ID K22A, units index base year = 100, release date 12 June 2026, next release 16 July 2026, and recent monthly values 2026 JAN 100.1, 2026 FEB 99.9, 2026 MAR 101.1, 2026 APR 101.5."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.6, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior on K22A April 2026 = 101.5 for the May first-print level; historical sample = monthly K22A successive changes from 2022 FEB through 2026 APR, n = 51, mean change = +0.04, sum of changes = +2.2, sum of squared changes = 51.02; adjustment components = +0.04 base-rate drift, +0.10 recent manufacturing momentum, -0.04 mean reversion from the elevated April level, giving point 101.5 + 0.10 = 101.6. Interval method uses realized dispersion of successive level changes, with sample standard deviation sigma = 1.01, so 80% half-width is roughly 1.28*sigma = 1.29, rounded to 1.3 index points; 101.6 - 1.3 = 100.3 and 101.6 + 1.3 = 102.9.","Counter-considerations: upside risk is a broad May gain across pharmaceuticals, electronics, and metals after April's 8 of 13 subsectors rising, which would land above the interval if K22A prints above 102.9. Downside risk is reversal in those volatile subsectors or a weak transport/electrical-equipment drag, which would land below the interval if K22A prints below 100.3. Outside the interval would most likely require a move larger than the recent monthly-change reference class expects or a revision-linked first-print discontinuity."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level and momentum update: the latest level, 101.5 in April 2026, is above the 2025 annual value of 99.6 and the 2023 base of 100.0, while recent official momentum is positive: 99.9 in February, 101.1 in March, and 101.5 in April. I apply only a small positive current-release adjustment because the series is noisy and April already followed a large March rise.","Prior/update/interval: persistence prior on K22A April 2026 = 101.5 for the May first-print level; historical sample = monthly K22A successive changes from 2022 FEB through 2026 APR, n = 51, mean change = +0.04, sum of changes = +2.2, sum of squared changes = 51.02; adjustment components = +0.04 base-rate drift, +0.10 recent manufacturing momentum, -0.04 mean reversion from the elevated April level, giving point 101.5 + 0.10 = 101.6. Interval method uses realized dispersion of successive level changes, with sample standard deviation sigma = 1.01, so 80% half-width is roughly 1.28*sigma = 1.29, rounded to 1.3 index points; 101.6 - 1.3 = 100.3 and 101.6 + 1.3 = 102.9."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate / reference class: the outside-view prior is persistence plus the 2022 JAN to 2026 APR K22A monthly-change distribution. That sample is centered close to flat, with mean monthly change about +0.04 index points, so the base rate alone would put May near 101.5 to 101.6.","Counter-considerations: upside risk is a broad May gain across pharmaceuticals, electronics, and metals after April's 8 of 13 subsectors rising, which would land above the interval if K22A prints above 102.9. Downside risk is reversal in those volatile subsectors or a weak transport/electrical-equipment drag, which would land below the interval if K22A prints below 100.3. Outside the interval would most likely require a move larger than the recent monthly-change reference class expects or a revision-linked first-print discontinuity."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Framing and exact resolver: this forecast targets ONS DIOP time series K22A, labelled IOP: C:MANUFACTURING: CVMSA. All anchors use the same chained volume measure, seasonally adjusted manufacturing index variant, base year 2023=100, not gross, non-seasonally adjusted, smoothed, or synthetic variants.","Tool result: Reference class values include 2022 JAN 99.3, 2023 JAN 99.1, 2024 JAN 100.6, 2025 JAN 99.0, 2026 JAN 100.1, and latest 2026 APR 101.5; the 51 monthly successive changes from 2022 FEB to 2026 APR sum to +2.2 index points."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: uk-manufacturing-output-index-may-2026\nrunLabel: Headline\nresolutionDate: 2026-07-16\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.uk-index-of-services-may-2026.2026-07-07T18-28-05Z.e1de8c008c85927b","runId":"run.uk-index-of-services-may-2026.2026-07-07T18-28-05Z.e1de8c008c85927b","predictionId":"uk-index-of-services-may-2026","specId":"spec.uk-index-of-services-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: for this level series I anchor the one-month-ahead change on recent ONS monthly IoS movements, where the latest eight readings are small but not noise-free: +0.2, -0.3, +0.3, +0.3, 0.0, +0.5, +0.3, and -0.2 percent from September 2025 through April 2026. That supports a mild positive mean, but April's fall and the announced national-accounts revision window argue against extrapolating the strong Q1 run fully.","Prior/update/interval: persistence prior is April 2026 total-services index level carried forward, with a working current level anchor of 104.6 index points on the 2022=100 total-services index scale, reconstructed from the recent official ONS monthly growth sequence and IOS1 scale rather than from the existing Thesis catalog forecast. Historical sample is the official recent monthly movements +0.2, -0.3, +0.3, +0.3, 0.0, +0.5, +0.3, -0.2 converted near a 104 index level to index-point changes of +0.21, -0.31, +0.31, +0.31, +0.00, +0.52, +0.31, -0.21. The sample standard deviation of those successive changes gives sigma = 0.29 index points, so a mechanical 80% half-width is about 1.28*sigma = 0.37. I widen to 0.60 as a judgmental add-on of about 0.23 index points for first-print benchmark and revision-window risk in the July release, while keeping the band within roughly 1.6 times the recent-growth volatility half-width. Point update is +0.1 index point from April persistence, so 104.6 + 0.1 = 104.7, with 80% interval 104.1 to 105.3."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this forecast targets the ONS Total Services chained-volume seasonally adjusted Index of Services index, 2022=100, for May 2026, not a gross, non-seasonally adjusted, quarterly, or revised-vintage variant. The ONS dataset identifier used for the time-series page is IOS1; the related detailed table is the Index of Services main components and sectors to four decimal places.","Tool call: Opened ONS Index of Services, UK: April 2026 latest bulletin for release timing and current first-print context."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["UK total services CVMSA index, May 2026 first print","Tool call: Opened ONS Index of Services, UK: April 2026 latest bulletin for release timing and current first-print context."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.2, distribution present, forecast step count 1.","evidence":["Framing and exact resolver: this forecast targets the ONS Total Services chained-volume seasonally adjusted Index of Services index, 2022=100, for May 2026, not a gross, non-seasonally adjusted, quarterly, or revised-vintage variant. The ONS dataset identifier used for the time-series page is IOS1; the related detailed table is the Index of Services main components and sectors to four decimal places.","Tool call: Checked ONS April 2026 bulletin data-source and quality lines for mechanism and uncertainty context."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and policy-mechanism effects: the level prior is a total-services index a little above 104 on a 2022=100 basis; momentum from Q1 and the three months to April is positive; the April monthly fall is treated as partly one-off; policy effects are indirect and small over a one-month horizon, mainly through public-service volumes and household-facing services rather than an explicit policy-rate rule."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool call: Checked ONS April 2026 bulletin data-source and quality lines for mechanism and uncertainty context.","Base rate/reference class: for this level series I anchor the one-month-ahead change on recent ONS monthly IoS movements, where the latest eight readings are small but not noise-free: +0.2, -0.3, +0.3, +0.3, 0.0, +0.5, +0.3, and -0.2 percent from September 2025 through April 2026. That supports a mild positive mean, but April's fall and the announced national-accounts revision window argue against extrapolating the strong Q1 run fully."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Framing and exact resolver: this forecast targets the ONS Total Services chained-volume seasonally adjusted Index of Services index, 2022=100, for May 2026, not a gross, non-seasonally adjusted, quarterly, or revised-vintage variant. The ONS dataset identifier used for the time-series page is IOS1; the related detailed table is the Index of Services main components and sectors to four decimal places.","Tool result: Fetched IOS1 dataset released 12 June 2026, next release 16 July 2026; four-decimal components dataset released 12 June 2026, next release 16 July 2026, with April 2026, March 2026, and February 2026 editions listed; working April 2026 total-services level anchor used for the forecast is 104.6 index points on the 2022=100 scale, reconstructed from the fetched recent ONS growth sequence and IOS1 scale rather than from a separately quoted catalog estimate."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: uk-index-of-services-may-2026\nrunLabel: Headline\nresolutionDate: 2026-07-16\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.census-marts-adv44x72-monthly-change-june-2026.2026-07-07T22-14-55Z.d057f6bb0cdcb131","runId":"run.census-marts-adv44x72-monthly-change-june-2026.2026-07-07T22-14-55Z.d057f6bb0cdcb131","predictionId":"census-marts-adv44x72-monthly-change-june-2026","specId":"spec.census-marts-adv44x72-monthly-change-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 3 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: using recent Census total retail and food services monthly-change evidence available in the release, the fetched values are +0.9, +0.4, and the current-vintage Table 1 April-to-May 2025 adjusted-level change of roughly -1.1. That limited reference class centers near zero but has material month-to-month volatility.","Prior/update/interval: persistence/base-rate prior uses available recent monthly changes [0.9, 0.4, -1.1], mean = (0.9 + 0.4 - 1.1)/3 = 0.07. Current-release adjustment adds +0.20 as a judgmental momentum update from the total-series +0.9 May print after +0.4 April, with no separate category breadth adjustment, giving point about 0.27 rounded to 0.3. For the interval, this 3-point sample is a fallback heuristic because a longer first-print sample was not fetched; sample sigma = 1.04 from [0.9, 0.4, -1.1], 1.28*sigma = 1.33, so 0.3 +/- 1.3 gives about -1.0 to 1.6, a reasonable 80% band for a noisy advance nominal monthly-change print."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this target is Census MARTS/Advance Monthly Sales for Retail and Food Services, total retail and food services NAICS 44X72, seasonally adjusted and not adjusted for price changes. The first-print value is the Table 2 percent change for June 2026 Advance from May 2026, not the later MRTS preliminary revision.","Tool call: Checked Census Monthly Retail Trade release schedule and Economic Indicator calendar for June 2026 Advance Monthly Retail Trade Report."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this target is Census MARTS/Advance Monthly Sales for Retail and Food Services, total retail and food services NAICS 44X72, seasonally adjusted and not adjusted for price changes. The first-print value is the Table 2 percent change for June 2026 Advance from May 2026, not the later MRTS preliminary revision.","Tool call: Checked Census Monthly Retail Trade release schedule and Economic Indicator calendar for June 2026 Advance Monthly Retail Trade Report."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.6, distribution present, forecast step count 1.","evidence":["June 2026 advance retail sales monthly-change forecast","Framing and exact resolver: this target is Census MARTS/Advance Monthly Sales for Retail and Food Services, total retail and food services NAICS 44X72, seasonally adjusted and not adjusted for price changes. The first-print value is the Table 2 percent change for June 2026 Advance from May 2026, not the later MRTS preliminary revision."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence/base-rate prior uses available recent monthly changes [0.9, 0.4, -1.1], mean = (0.9 + 0.4 - 1.1)/3 = 0.07. Current-release adjustment adds +0.20 as a judgmental momentum update from the total-series +0.9 May print after +0.4 April, with no separate category breadth adjustment, giving point about 0.27 rounded to 0.3. For the interval, this 3-point sample is a fallback heuristic because a longer first-print sample was not fetched; sample sigma = 1.04 from [0.9, 0.4, -1.1], 1.28*sigma = 1.33, so 0.3 +/- 1.3 gives about -1.0 to 1.6, a reasonable 80% band for a noisy advance nominal monthly-change print."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: using recent Census total retail and food services monthly-change evidence available in the release, the fetched values are +0.9, +0.4, and the current-vintage Table 1 April-to-May 2025 adjusted-level change of roughly -1.1. That limited reference class centers near zero but has material month-to-month volatility.","Upside risk: unusually strong nominal spending across high-weight retail categories or a large seasonal-adjustment surprise would land above the interval. Downside risk: a broad June reversal after May's strong total print would land below the interval. A shock large enough to move the total monthly change beyond roughly +/-1.3 percentage points from the point forecast is the main outside the interval scenario."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["June 2026 advance retail sales monthly-change forecast","Variant consistency: the target and the direct anchors are Census Advance Monthly Sales for Retail and Food Services total retail and food services, seasonally adjusted, not price-adjusted. The 2025 comparison is computed from current-vintage adjusted Table 1 levels, so it is used only as a fallback volatility/context point, not as a verified first-print advance Table 2 observation."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: census-marts-adv44x72-monthly-change-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-16\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bls-import-price-index-all-imports-mom-june-2026.2026-07-07T22-07-42Z.f8bd3dc28bf7e6b9","runId":"run.bls-import-price-index-all-imports-mom-june-2026.2026-07-07T22-07-42Z.f8bd3dc28bf7e6b9","predictionId":"bls-import-price-index-all-imports-mom-june-2026","specId":"spec.bls-import-price-index-all-imports-mom-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The reference class and base rate are the available BLS Table A all-import monthly percent changes from May 2025 through May 2026, excluding unavailable October and November 2025 entries. Before inside-view adjustments, the simple historical/persistence model prior is the 11-observation mean of about 0.54 percent; no AR, ETS, or regression model was used because the usable first-print sample is short and disrupted by missing 2025 data.","Prior/update/interval: persistence prior uses the 11 available BLS Table A all-import MoM values [-0.5, -0.1, 0.3, -0.1, -0.1, 0.1, 0.5, 1.0, 0.9, 2.0, 1.9], whose mean is 0.54 and sample sigma = 0.83 for this change series; update components are +0.40 for recent momentum above the base rate, +0.25 for firm nonfuel import prices, and -0.10 for likely partial cooling after extreme fuel gains, giving 0.54 + 0.40 + 0.25 - 0.10 = 1.09, rounded to 1.1. The 80% half-width is roughly 1.28*sigma = 1.28*0.83 = 1.06, so 1.1 +/- 1.06 gives about 0.0 to 2.2 after one-decimal target rounding."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Forecast for June 2026 BLS all-import import-price MoM","Framing and exact resolver: this targets the BLS Import/Export Price Indexes first print for June 2026, Table 1 All commodities monthly percent change, which is the all-imports end-use aggregate. The release is not seasonally adjusted in this table, and the target uses the first-published one-decimal percent change, not later revised values."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this targets the BLS Import/Export Price Indexes first print for June 2026, Table 1 All commodities monthly percent change, which is the all-imports end-use aggregate. The release is not seasonally adjusted in this table, and the target uses the first-published one-decimal percent change, not later revised values.","Tool call: Opened BLS schedule page for U.S. Import and Export Price Indexes release dates."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.2, distribution present, forecast step count 1.","evidence":["Tool call: Read BLS release text and Table A component detail for recent all-import, fuel, and nonfuel import prices.","Prior/update/interval: persistence prior uses the 11 available BLS Table A all-import MoM values [-0.5, -0.1, 0.3, -0.1, -0.1, 0.1, 0.5, 1.0, 0.9, 2.0, 1.9], whose mean is 0.54 and sample sigma = 0.83 for this change series; update components are +0.40 for recent momentum above the base rate, +0.25 for firm nonfuel import prices, and -0.10 for likely partial cooling after extreme fuel gains, giving 0.54 + 0.40 + 0.25 - 0.10 = 1.09, rounded to 1.1. The 80% half-width is roughly 1.28*sigma = 1.28*0.83 = 1.06, so 1.1 +/- 1.06 gives about 0.0 to 2.2 after one-decimal target rounding."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The reference class and base rate are the available BLS Table A all-import monthly percent changes from May 2025 through May 2026, excluding unavailable October and November 2025 entries. Before inside-view adjustments, the simple historical/persistence model prior is the 11-observation mean of about 0.54 percent; no AR, ETS, or regression model was used because the usable first-print sample is short and disrupted by missing 2025 data.","Prior/update/interval: persistence prior uses the 11 available BLS Table A all-import MoM values [-0.5, -0.1, 0.3, -0.1, -0.1, 0.1, 0.5, 1.0, 0.9, 2.0, 1.9], whose mean is 0.54 and sample sigma = 0.83 for this change series; update components are +0.40 for recent momentum above the base rate, +0.25 for firm nonfuel import prices, and -0.10 for likely partial cooling after extreme fuel gains, giving 0.54 + 0.40 + 0.25 - 0.10 = 1.09, rounded to 1.1. The 80% half-width is roughly 1.28*sigma = 1.28*0.83 = 1.06, so 1.1 +/- 1.06 gives about 0.0 to 2.2 after one-decimal target rounding."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-considerations: upside risk is another large fuel-import increase or broader tariff/pass-through pressure that would land above the interval, especially if fuels again add double-digit monthly growth. Downside risk is a June reversal in petroleum or natural gas import prices, or a sudden weakening in nonfuel goods prices, which would land outside the interval below 0.0."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for June 2026 BLS all-import import-price MoM","Prior/update/interval: persistence prior uses the 11 available BLS Table A all-import MoM values [-0.5, -0.1, 0.3, -0.1, -0.1, 0.1, 0.5, 1.0, 0.9, 2.0, 1.9], whose mean is 0.54 and sample sigma = 0.83 for this change series; update components are +0.40 for recent momentum above the base rate, +0.25 for firm nonfuel import prices, and -0.10 for likely partial cooling after extreme fuel gains, giving 0.54 + 0.40 + 0.25 - 0.10 = 1.09, rounded to 1.1. The 80% half-width is roughly 1.28*sigma = 1.28*0.83 = 1.06, so 1.1 +/- 1.06 gives about 0.0 to 2.2 after one-decimal target rounding."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bls-import-price-index-all-imports-mom-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-17\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.census-housing-starts-saar-june-2026.2026-07-07T22-13-30Z.4a492053aefceab1","runId":"run.census-housing-starts-saar-june-2026.2026-07-07T22-13-30Z.4a492053aefceab1","predictionId":"census-housing-starts-saar-june-2026","specId":"spec.census-housing-starts-saar-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: over the latest official 13-month current-vintage starts sequence, the level has mostly run between 1.27 million and 1.43 million SAAR before the May 2026 drop to 1.177 million. A persistence base rate from the latest print would be 1.177 million, but the component mix suggests May was unusually weak in multifamily rather than a broad collapse.","Prior/update/interval: persistence prior is May 2026 starts at 1.177 million SAAR using the official Table 3a reference class from May 2025 through May 2026; adjustments are +0.000 million for single-family level, +0.060 million for partial multifamily mean reversion, and +0.000 million for policy/timing effects, giving 1.177 + 0.060 = 1.237. Successive monthly changes in millions are +0.090, +0.053, -0.141, +0.028, -0.046, +0.046, +0.059, +0.007, -0.039, +0.176, -0.130, -0.215, so sigma = 0.113; using an approximately normal 80% half-width, 1.28*sigma = 0.145, giving 1.237 - 0.145 = 1.092 and 1.237 + 0.145 = 1.382."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this forecast targets the Census/HUD New Residential Construction first print for privately owned housing units started, United States total, seasonally adjusted annual rate, June 2026. The table variant is Table 3a, seasonally adjusted annual rate, not not-seasonally-adjusted starts and not permits or completions.","Tool call: Open Census Economic Indicator Release Schedule and Survey of Construction release schedule for June 2026 New Residential Construction."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this forecast targets the Census/HUD New Residential Construction first print for privately owned housing units started, United States total, seasonally adjusted annual rate, June 2026. The table variant is Table 3a, seasonally adjusted annual rate, not not-seasonally-adjusted starts and not permits or completions.","Tool call: Open Census Economic Indicator Release Schedule and Survey of Construction release schedule for June 2026 New Residential Construction."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.29, distribution present, forecast step count 1.","evidence":["Tool call: Read component detail from the May 2026 Census/HUD release for starts and permits.","Prior/update/interval: persistence prior is May 2026 starts at 1.177 million SAAR using the official Table 3a reference class from May 2025 through May 2026; adjustments are +0.000 million for single-family level, +0.060 million for partial multifamily mean reversion, and +0.000 million for policy/timing effects, giving 1.177 + 0.060 = 1.237. Successive monthly changes in millions are +0.090, +0.053, -0.141, +0.028, -0.046, +0.046, +0.059, +0.007, -0.039, +0.176, -0.130, -0.215, so sigma = 0.113; using an approximately normal 80% half-width, 1.28*sigma = 0.145, giving 1.237 - 0.145 = 1.092 and 1.237 + 0.145 = 1.382."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, and mechanisms: single-family starts were only 17,000 below April and single-family permits were 886,000, so I keep that component near 0.88 million. Multifamily starts at 0.284 million were far below recent starts and below May 5-plus-unit permits at 0.474 million, so I add a partial rebound of about 0.060 million rather than a full snapback."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Reference class and base rate: over the latest official 13-month current-vintage starts sequence, the level has mostly run between 1.27 million and 1.43 million SAAR before the May 2026 drop to 1.177 million. A persistence base rate from the latest print would be 1.177 million, but the component mix suggests May was unusually weak in multifamily rather than a broad collapse.","Counter-considerations: upside risk is a faster multifamily rebound toward the 0.40-0.48 million area implied by recent starts and permits, which would land above the interval if single-family also improves. Downside risk is that high mortgage rates and builder caution keep starts near May's depressed multifamily level, which would land below the interval if single-family starts also break below 0.85 million."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["June 2026 U.S. housing starts SAAR forecast","Framing and exact resolver: this forecast targets the Census/HUD New Residential Construction first print for privately owned housing units started, United States total, seasonally adjusted annual rate, June 2026. The table variant is Table 3a, seasonally adjusted annual rate, not not-seasonally-adjusted starts and not permits or completions."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: census-housing-starts-saar-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-17\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.census-housing-starts-saar-june-2026.2026-07-08T02-53-21Z.census-housing-starts-saar-june-2026-thesis-analyst-fast-2026-07-08t02-53-21z.7386e893808cd951","runId":"run.census-housing-starts-saar-june-2026.2026-07-08T02-53-21Z.census-housing-starts-saar-june-2026-thesis-analyst-fast-2026-07-08t02-53-21z.7386e893808cd951","predictionId":"census-housing-starts-saar-june-2026","specId":"spec.census-housing-starts-saar-june-2026","runLabel":"Fast rollout 1 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Framing and exact resolver: this forecast targets Census/HUD New Residential Construction first-print privately owned housing units started, United States total, seasonally adjusted annual rate, for June 2026. The target variant is Table 3a starts SAAR, not not-seasonally-adjusted starts, permits, completions, or later revised historical data.","Base rate/reference class: the comparable Table 3a starts SAAR series over May 2025 through May 2026 is volatile but mostly in the 1.27 to 1.43 million range before the May 2026 drop; the last three target-variant readings, 1.522, 1.392, and 1.177 million, average 1.364 million."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this forecast targets Census/HUD New Residential Construction first-print privately owned housing units started, United States total, seasonally adjusted annual rate, for June 2026. The target variant is Table 3a starts SAAR, not not-seasonally-adjusted starts, permits, completions, or later revised historical data.","Tool call: Opened the Census 2026 Economic Indicator Release Schedule list view for New Residential Construction June 2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this forecast targets Census/HUD New Residential Construction first-print privately owned housing units started, United States total, seasonally adjusted annual rate, for June 2026. The target variant is Table 3a starts SAAR, not not-seasonally-adjusted starts, permits, completions, or later revised historical data.","Tool call: Opened the Census 2026 Economic Indicator Release Schedule list view for New Residential Construction June 2026."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.34, distribution present, forecast step count 1.","evidence":["Tool call: Read the May 2026 Table 3a detail and explanatory notes for measurement noise and month-to-month interpretation.","Tool result: The release reports May 2026 starts at 1,177,000 SAAR, down 15.4 percent from April 2026, with a 90 percent confidence interval of plus or minus 9.8 percentage points; Table 3a average RSE for recent total starts is 7 percent; Census says it may take 6 months to establish an underlying trend for total starts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level and momentum: a naive one-month persistence prior would stay near 1.18 million, but May's 15.4 percent fall is unusually large and permits remained at 1.413 million, so I partially mean-revert June toward the recent starts range rather than extrapolating another decline.","Prior/update/interval: persistence prior from May is 1.177 million; reference class is recent Table 3a total starts SAAR from May 2025 through May 2026. Successive changes across the fetched starts sequence are +0.090, +0.053, -0.141, +0.028, -0.046, +0.046, +0.059, +0.007, -0.039, +0.176, -0.130, and -0.215 million, giving sigma = 0.110. The Gaussian 80 percent half-width is roughly 1.28*sigma = 1.28*0.110 = 0.141 million. I widen to about 0.170 million because the May print carried a 7 percent RSE and an unusually large one-month drop, yielding 1.300 - 0.170 = 1.130 and 1.300 + 0.170 = 1.470."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool result: Table 3a United States total starts SAAR values were May 2025 1,289 thousand, June 2025 1,379 thousand, July 2025 1,432 thousand, September 2025 1,319 thousand, October 2025 1,273 thousand, November 2025 1,319 thousand, January 2026 1,385 thousand, February 2026 1,346 thousand, April 2026 1,392 thousand, and May 2026 1,177 thousand; August 2025 and December 2025 rows have extraction-order ambiguity in the PDF text but correspond to total starts of 1,291 and 1,378 thousand.","Base rate/reference class: the comparable Table 3a starts SAAR series over May 2025 through May 2026 is volatile but mostly in the 1.27 to 1.43 million range before the May 2026 drop; the last three target-variant readings, 1.522, 1.392, and 1.177 million, average 1.364 million."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["June 2026 U.S. housing starts SAAR forecast","Framing and exact resolver: this forecast targets Census/HUD New Residential Construction first-print privately owned housing units started, United States total, seasonally adjusted annual rate, for June 2026. The target variant is Table 3a starts SAAR, not not-seasonally-adjusted starts, permits, completions, or later revised historical data."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: census-housing-starts-saar-june-2026\nrunLabel: Fast rollout 1 of 3\nresolutionDate: 2026-07-17\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.census-housing-starts-saar-june-2026.2026-07-08T02-53-35Z.census-housing-starts-saar-june-2026-thesis-analyst-fast-2026-07-08t02-53-35z.b811c2845d9abc69","runId":"run.census-housing-starts-saar-june-2026.2026-07-08T02-53-35Z.census-housing-starts-saar-june-2026-thesis-analyst-fast-2026-07-08t02-53-35z.b811c2845d9abc69","predictionId":"census-housing-starts-saar-june-2026","specId":"spec.census-housing-starts-saar-june-2026","runLabel":"Fast rollout 2 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Framing and exact resolver: this forecast is for Census/HUD Table 3a, New Privately-Owned Housing Units Started, United States total, seasonally adjusted annual rate, June 2026 first print, converted from thousands to millions. The release variant, anchors, and history are all SAAR first-print or current-release Table 3a values, not NSA or later historical backfills.","Base rate/reference class: for a one-month-ahead total starts forecast, persistence plus partial mean reversion is the right starting point because the official notes say month-to-month seasonally adjusted construction statistics are irregular and it can take 6 months to establish an underlying trend for total starts."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this forecast is for Census/HUD Table 3a, New Privately-Owned Housing Units Started, United States total, seasonally adjusted annual rate, June 2026 first print, converted from thousands to millions. The release variant, anchors, and history are all SAAR first-print or current-release Table 3a values, not NSA or later historical backfills.","Tool call: Open Census/HUD May 2026 New Residential Construction release page and PDF for the latest official starts and permits anchors."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["US housing starts SAAR, June 2026 first print","Framing and exact resolver: this forecast is for Census/HUD Table 3a, New Privately-Owned Housing Units Started, United States total, seasonally adjusted annual rate, June 2026 first print, converted from thousands to millions. The release variant, anchors, and history are all SAAR first-print or current-release Table 3a values, not NSA or later historical backfills."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.28, distribution present, forecast step count 1.","evidence":["Tool call: Read Census/HUD PDF Table 3a for recent total housing starts and component detail.","Prior/update/interval: persistence prior is May 2026 total starts at 1.177 million; historical sample is the 12 successive monthly changes from May 2025 through May 2026 in Table 3a, with sigma = 0.110 million and 80% half-width = 1.28*sigma = 1.28*0.110 = 0.141 million. Adjustment components: +0.020 million for stable single-family starts/permits near 0.88 million, +0.050 million for partial rebound in volatile 5+ starts from 0.284 million, and -0.010 million for soft overall momentum after the May drop. Point = 1.177 + 0.020 + 0.050 - 0.010 = 1.237 million; interval = 1.237 +/- 0.141 = [1.096, 1.378]."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate/reference class: for a one-month-ahead total starts forecast, persistence plus partial mean reversion is the right starting point because the official notes say month-to-month seasonally adjusted construction statistics are irregular and it can take 6 months to establish an underlying trend for total starts.","Prior/update/interval: persistence prior is May 2026 total starts at 1.177 million; historical sample is the 12 successive monthly changes from May 2025 through May 2026 in Table 3a, with sigma = 0.110 million and 80% half-width = 1.28*sigma = 1.28*0.110 = 0.141 million. Adjustment components: +0.020 million for stable single-family starts/permits near 0.88 million, +0.050 million for partial rebound in volatile 5+ starts from 0.284 million, and -0.010 million for soft overall momentum after the May drop. Point = 1.177 + 0.020 + 0.050 - 0.010 = 1.237 million; interval = 1.237 +/- 0.141 = [1.096, 1.378]."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-considerations: upside risk is a quick multifamily rebound toward the 0.40-0.48 million 5+ unit range seen earlier in 2026, which would land above the interval if single-family also holds firm. Downside risk is that May's fall reflected a broader financing or demand pullback rather than noise, which would land below the interval if total starts stay near or under 1.10 million."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Framing and exact resolver: this forecast is for Census/HUD Table 3a, New Privately-Owned Housing Units Started, United States total, seasonally adjusted annual rate, June 2026 first print, converted from thousands to millions. The release variant, anchors, and history are all SAAR first-print or current-release Table 3a values, not NSA or later historical backfills.","Base rate/reference class: for a one-month-ahead total starts forecast, persistence plus partial mean reversion is the right starting point because the official notes say month-to-month seasonally adjusted construction statistics are irregular and it can take 6 months to establish an underlying trend for total starts."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: census-housing-starts-saar-june-2026\nrunLabel: Fast rollout 2 of 3\nresolutionDate: 2026-07-17\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.census-housing-starts-saar-june-2026.2026-07-08T02-57-35Z.census-housing-starts-saar-june-2026-thesis-analyst-fast-2026-07-08t02-57-35z.b811c2845d9abc69","runId":"run.census-housing-starts-saar-june-2026.2026-07-08T02-57-35Z.census-housing-starts-saar-june-2026-thesis-analyst-fast-2026-07-08t02-57-35z.b811c2845d9abc69","predictionId":"census-housing-starts-saar-june-2026","specId":"spec.census-housing-starts-saar-june-2026","runLabel":"Fast rollout 3 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Framing and exact resolver: this forecast is for Census/HUD Table 3a, New Privately-Owned Housing Units Started, United States total, seasonally adjusted annual rate, June 2026 first print, converted from thousands to millions. The release variant, anchors, and history are all SAAR Table 3a values from the current Census/HUD release, not NSA values, smoothed trend charts, or later historical backfills.","Base rate/reference class: for a one-month-ahead total starts forecast, persistence plus partial mean reversion is the right starting point because the Census/HUD explanatory notes say month-to-month seasonally adjusted construction statistics are irregular and it can take 6 months to establish an underlying trend for total starts."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this forecast is for Census/HUD Table 3a, New Privately-Owned Housing Units Started, United States total, seasonally adjusted annual rate, June 2026 first print, converted from thousands to millions. The release variant, anchors, and history are all SAAR Table 3a values from the current Census/HUD release, not NSA values, smoothed trend charts, or later historical backfills.","Tool call: Open Census/HUD May 2026 New Residential Construction current release page and PDF for the latest official starts and permits anchors."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["US housing starts SAAR, June 2026 first print","Framing and exact resolver: this forecast is for Census/HUD Table 3a, New Privately-Owned Housing Units Started, United States total, seasonally adjusted annual rate, June 2026 first print, converted from thousands to millions. The release variant, anchors, and history are all SAAR Table 3a values from the current Census/HUD release, not NSA values, smoothed trend charts, or later historical backfills."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.28, distribution present, forecast step count 1.","evidence":["Tool call: Read Census/HUD PDF Table 3a for recent total housing starts and component detail.","Prior/update/interval: persistence prior is May 2026 total starts at 1.177 million; historical sample is the 12 successive monthly changes from May 2025 through May 2026 in Table 3a, with sigma = 0.110 million and 80% half-width = 1.28*sigma = 1.28*0.110 = 0.141 million. Adjustment components: +0.020 million for stable single-family starts/permits near 0.88 million, +0.050 million for partial rebound in volatile 5+ starts from 0.284 million, and -0.010 million for soft overall momentum after the May drop. Point = 1.177 + 0.020 + 0.050 - 0.010 = 1.237 million; interval = 1.237 +/- 0.141 = [1.096, 1.378]."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate/reference class: for a one-month-ahead total starts forecast, persistence plus partial mean reversion is the right starting point because the Census/HUD explanatory notes say month-to-month seasonally adjusted construction statistics are irregular and it can take 6 months to establish an underlying trend for total starts.","Prior/update/interval: persistence prior is May 2026 total starts at 1.177 million; historical sample is the 12 successive monthly changes from May 2025 through May 2026 in Table 3a, with sigma = 0.110 million and 80% half-width = 1.28*sigma = 1.28*0.110 = 0.141 million. Adjustment components: +0.020 million for stable single-family starts/permits near 0.88 million, +0.050 million for partial rebound in volatile 5+ starts from 0.284 million, and -0.010 million for soft overall momentum after the May drop. Point = 1.177 + 0.020 + 0.050 - 0.010 = 1.237 million; interval = 1.237 +/- 0.141 = [1.096, 1.378]."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-considerations: upside risk is a quick multifamily rebound toward the 0.40-0.48 million 5+ unit range seen earlier in 2026, which would land above the interval if single-family also holds firm. Downside risk is that May's fall reflected a broader financing or demand pullback rather than noise, which would land below the interval if total starts stay near or under 1.10 million."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Framing and exact resolver: this forecast is for Census/HUD Table 3a, New Privately-Owned Housing Units Started, United States total, seasonally adjusted annual rate, June 2026 first print, converted from thousands to millions. The release variant, anchors, and history are all SAAR Table 3a values from the current Census/HUD release, not NSA values, smoothed trend charts, or later historical backfills.","Base rate/reference class: for a one-month-ahead total starts forecast, persistence plus partial mean reversion is the right starting point because the Census/HUD explanatory notes say month-to-month seasonally adjusted construction statistics are irregular and it can take 6 months to establish an underlying trend for total starts."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: census-housing-starts-saar-june-2026\nrunLabel: Fast rollout 3 of 3\nresolutionDate: 2026-07-17\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.census-housing-starts-saar-june-2026.2026-07-08T02-59-50Z.census-housing-starts-saar-june-2026-thesis-analyst-ladder-2026-07-08t02-59-50z.57eed62630309ed1","runId":"run.census-housing-starts-saar-june-2026.2026-07-08T02-59-50Z.census-housing-starts-saar-june-2026-thesis-analyst-ladder-2026-07-08t02-59-50z.57eed62630309ed1","predictionId":"census-housing-starts-saar-june-2026","specId":"spec.census-housing-starts-saar-june-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Framing and exact resolver: this forecast is for Census/HUD Table 3a, New Privately-Owned Housing Units Started, United States total, seasonally adjusted annual rate, June 2026 first print, converted from thousands to millions. The release variant, anchors, and history are all SAAR Table 3a values from the current Census/HUD release, not NSA values, smoothed trend charts, or later historical backfills.","Base rate/reference class: for a one-month-ahead total starts forecast, persistence plus partial mean reversion is the starting point because the Census/HUD explanatory notes say month-to-month seasonally adjusted construction statistics are irregular and it can take 6 months to establish an underlying trend for total starts."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this forecast is for Census/HUD Table 3a, New Privately-Owned Housing Units Started, United States total, seasonally adjusted annual rate, June 2026 first print, converted from thousands to millions. The release variant, anchors, and history are all SAAR Table 3a values from the current Census/HUD release, not NSA values, smoothed trend charts, or later historical backfills.","Tool call: Open Census/HUD May 2026 New Residential Construction current release page and PDF for the latest official starts and permits anchors."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["US housing starts SAAR, June 2026 first print","Framing and exact resolver: this forecast is for Census/HUD Table 3a, New Privately-Owned Housing Units Started, United States total, seasonally adjusted annual rate, June 2026 first print, converted from thousands to millions. The release variant, anchors, and history are all SAAR Table 3a values from the current Census/HUD release, not NSA values, smoothed trend charts, or later historical backfills."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.28, distribution present, forecast step count 1.","evidence":["Tool call: Read Census/HUD PDF Table 3a for recent total housing starts and component detail.","Prior/update/interval: persistence prior is May 2026 total starts at 1.177 million; historical sample is the 12 successive monthly changes from May 2025 through May 2026 in Table 3a, with sigma = 0.110 million and 80% half-width = 1.28*sigma = 1.28*0.110 = 0.141 million. Adjustment components: +0.020 million for stable single-family starts/permits near 0.88 million, +0.050 million for partial rebound in volatile 5+ starts after the May 0.284 million print versus the higher total-starts environment in March-April 2026, and -0.010 million for soft overall momentum after the May drop. Point = 1.177 + 0.020 + 0.050 - 0.010 = 1.237 million. The ladder-implied 80% interval width is 1.378 - 1.096 = 0.282 million, or 0.141 million half-width, matching the 1.28*sigma rule."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate/reference class: for a one-month-ahead total starts forecast, persistence plus partial mean reversion is the starting point because the Census/HUD explanatory notes say month-to-month seasonally adjusted construction statistics are irregular and it can take 6 months to establish an underlying trend for total starts.","Prior/update/interval: persistence prior is May 2026 total starts at 1.177 million; historical sample is the 12 successive monthly changes from May 2025 through May 2026 in Table 3a, with sigma = 0.110 million and 80% half-width = 1.28*sigma = 1.28*0.110 = 0.141 million. Adjustment components: +0.020 million for stable single-family starts/permits near 0.88 million, +0.050 million for partial rebound in volatile 5+ starts after the May 0.284 million print versus the higher total-starts environment in March-April 2026, and -0.010 million for soft overall momentum after the May drop. Point = 1.177 + 0.020 + 0.050 - 0.010 = 1.237 million. The ladder-implied 80% interval width is 1.378 - 1.096 = 0.282 million, or 0.141 million half-width, matching the 1.28*sigma rule."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-considerations: upside risk is a quick multifamily rebound toward the 0.40-0.48 million 5+ unit range seen earlier in 2026, which would land above the interval if single-family also holds firm. Downside risk is that May's fall reflected a broader financing or demand pullback rather than noise, which would land below the interval if total starts stay near or under 1.10 million. A shock from permitting-to-start conversion or weather timing could also put the print outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Framing and exact resolver: this forecast is for Census/HUD Table 3a, New Privately-Owned Housing Units Started, United States total, seasonally adjusted annual rate, June 2026 first print, converted from thousands to millions. The release variant, anchors, and history are all SAAR Table 3a values from the current Census/HUD release, not NSA values, smoothed trend charts, or later historical backfills.","Base rate/reference class: for a one-month-ahead total starts forecast, persistence plus partial mean reversion is the starting point because the Census/HUD explanatory notes say month-to-month seasonally adjusted construction statistics are irregular and it can take 6 months to establish an underlying trend for total starts."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: census-housing-starts-saar-june-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-07-17\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.census-housing-starts-saar-june-2026.2026-07-08T03-03-42Z.census-housing-starts-saar-june-2026-thesis-analyst-median3-2026-07-08t03-03-42z.6d245a66d73a7b35","runId":"run.census-housing-starts-saar-june-2026.2026-07-08T03-03-42Z.census-housing-starts-saar-june-2026-thesis-analyst-median3-2026-07-08t03-03-42z.6d245a66d73a7b35","predictionId":"census-housing-starts-saar-june-2026","specId":"spec.census-housing-starts-saar-june-2026","runLabel":"Median of 3 rollouts","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 5 historical point(s) and implicit outside-view language.","evidence":["Median-of-3 rollout ensemble","Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-08T02:53:21Z, 2026-07-08T02:53:35Z, 2026-07-08T02:57:35Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Median CDF quantiles: q10 = 1.096, q50 = 1.237, q90 = 1.38. Constituent points [1.3, 1.237, 1.237] with 80% widths [0.34, 0.282, 0.282]; the median interval inherits the central rollout mass rather than averaging tails."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.28, distribution present, forecast step count 1.","evidence":["Median CDF quantiles: q10 = 1.096, q50 = 1.237, q90 = 1.38. Constituent points [1.3, 1.237, 1.237] with 80% widths [0.34, 0.282, 0.282]; the median interval inherits the central rollout mass rather than averaging tails.","Forecast: point 1.237, 80% interval [1.096, 1.38]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-08T02:53:21Z, 2026-07-08T02:53:35Z, 2026-07-08T02:57:35Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-08T02:53:21Z, 2026-07-08T02:53:35Z, 2026-07-08T02:57:35Z. Drivers and resolver fields mirror the rollout closest to the median.","Tool result: {rollout_points: [1.3, 1.237, 1.237], rollout_widths: [0.34, 0.282, 0.282], q10: 1.096, q50: 1.237, q90: 1.38}"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: census-housing-starts-saar-june-2026\nrunLabel: Median of 3 rollouts\nresolutionDate: 2026-07-17\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.cms-medicaid-pi-beneficiaries-disenrolled-procedural-california-june-2026.2026-07-07T22-17-12Z.3df1ea72c7a611d6","runId":"run.cms-medicaid-pi-beneficiaries-disenrolled-procedural-california-june-2026.2026-07-07T22-17-12Z.3df1ea72c7a611d6","predictionId":"cms-medicaid-pi-beneficiaries-disenrolled-procedural-california-june-2026","specId":"spec.cms-medicaid-pi-beneficiaries-disenrolled-procedural-california-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool call: Read prior-regime and same-month official CMS Snapshot rows for California and national context.","Reference class/base rate: I use the post-December-2025 California first-print regime as the main base rate because the latest four official state rows cluster around 200000-216000 implied procedural disenrollments, while June-November 2025 show a lower earlier regime. National procedural rates also moved up to 15% in February-March 2026, so the older June 2025 California 3% print is treated as a downside regime marker rather than the main prior."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 7 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this is the CMS Medicaid and CHIP Eligibility Operations and Enrollment Snapshot Data, Eligibility Processing Data, California state row, reporting month June 2026, original/preliminary first print, beneficiaries disenrolled for procedural or administrative reasons. It is not a national total, weighted average, updated quarterly outcome, or enrollment level.","Tool call: Checked the official Medicaid.gov Snapshot index and Data.Medicaid.gov snapshot-data page for release identity and timing."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this is the CMS Medicaid and CHIP Eligibility Operations and Enrollment Snapshot Data, Eligibility Processing Data, California state row, reporting month June 2026, original/preliminary first print, beneficiaries disenrolled for procedural or administrative reasons. It is not a national total, weighted average, updated quarterly outcome, or enrollment level.","Tool call: Checked the official Medicaid.gov Snapshot index and Data.Medicaid.gov snapshot-data page for release identity and timing."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 70000, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is the mean of the Dec 2025-Mar 2026 California first-print implied counts, 208500, 216307, 200616, and 200177, giving 206400. Adjustment components: -2000 for slight enrollment/renewal-volume attrition from March enrollment revision, +1000 for June-quarter reporting risk, and -400 for rounding/proxy uncertainty, yielding about 205000. Interval method uses the recent post-December flow values themselves: sample sigma = 7629, so 1.28*sigma = 9765. I widen to a 35000 half-width because these historical counts are implied from rounded CMS table rates rather than exact dataset values, and because California shifted regimes from 3% in June 2025 to 19-20% in early 2026; final implied bounds are 205000 - 35000 = 170000 and 205000 + 35000 = 240000.","Counter-considerations: upside risk is a June renewal cohort above 1.15 million with the procedural rate still near 20%, which would land above the interval. Downside risk is California reverting toward the June 2025 low-procedural pattern or holding procedural terminations, which would land below the interval. Outside the interval on either side would mainly falsify the current-regime persistence assumption, not the target identity."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Reference class/base rate: I use the post-December-2025 California first-print regime as the main base rate because the latest four official state rows cluster around 200000-216000 implied procedural disenrollments, while June-November 2025 show a lower earlier regime. National procedural rates also moved up to 15% in February-March 2026, so the older June 2025 California 3% print is treated as a downside regime marker rather than the main prior.","Prior/update/interval: persistence prior is the mean of the Dec 2025-Mar 2026 California first-print implied counts, 208500, 216307, 200616, and 200177, giving 206400. Adjustment components: -2000 for slight enrollment/renewal-volume attrition from March enrollment revision, +1000 for June-quarter reporting risk, and -400 for rounding/proxy uncertainty, yielding about 205000. Interval method uses the recent post-December flow values themselves: sample sigma = 7629, so 1.28*sigma = 9765. I widen to a 35000 half-width because these historical counts are implied from rounded CMS table rates rather than exact dataset values, and because California shifted regimes from 3% in June 2025 to 19-20% in early 2026; final implied bounds are 205000 - 35000 = 170000 and 205000 + 35000 = 240000."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence prior is the mean of the Dec 2025-Mar 2026 California first-print implied counts, 208500, 216307, 200616, and 200177, giving 206400. Adjustment components: -2000 for slight enrollment/renewal-volume attrition from March enrollment revision, +1000 for June-quarter reporting risk, and -400 for rounding/proxy uncertainty, yielding about 205000. Interval method uses the recent post-December flow values themselves: sample sigma = 7629, so 1.28*sigma = 9765. I widen to a 35000 half-width because these historical counts are implied from rounded CMS table rates rather than exact dataset values, and because California shifted regimes from 3% in June 2025 to 19-20% in early 2026; final implied bounds are 205000 - 35000 = 170000 and 205000 + 35000 = 240000.","Counter-considerations: upside risk is a June renewal cohort above 1.15 million with the procedural rate still near 20%, which would land above the interval. Downside risk is California reverting toward the June 2025 low-procedural pattern or holding procedural terminations, which would land below the interval. Outside the interval on either side would mainly falsify the current-regime persistence assumption, not the target identity."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: persistence prior is the mean of the Dec 2025-Mar 2026 California first-print implied counts, 208500, 216307, 200616, and 200177, giving 206400. Adjustment components: -2000 for slight enrollment/renewal-volume attrition from March enrollment revision, +1000 for June-quarter reporting risk, and -400 for rounding/proxy uncertainty, yielding about 205000. Interval method uses the recent post-December flow values themselves: sample sigma = 7629, so 1.28*sigma = 9765. I widen to a 35000 half-width because these historical counts are implied from rounded CMS table rates rather than exact dataset values, and because California shifted regimes from 3% in June 2025 to 19-20% in early 2026; final implied bounds are 205000 - 35000 = 170000 and 205000 + 35000 = 240000.","Counter-considerations: upside risk is a June renewal cohort above 1.15 million with the procedural rate still near 20%, which would land above the interval. Downside risk is California reverting toward the June 2025 low-procedural pattern or holding procedural terminations, which would land below the interval. Outside the interval on either side would mainly falsify the current-regime persistence assumption, not the target identity."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: cms-medicaid-pi-beneficiaries-disenrolled-procedural-california-june-2026\nrunLabel: Headline\nresolutionDate: 2026-09-25\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.cms-medicaid-pi-beneficiaries-disenrolled-total-california-june-2026.2026-07-07T22-21-39Z.e01c18e25670f51f","runId":"run.cms-medicaid-pi-beneficiaries-disenrolled-total-california-june-2026.2026-07-07T22-21-39Z.e01c18e25670f51f","predictionId":"cms-medicaid-pi-beneficiaries-disenrolled-total-california-june-2026","specId":"spec.cms-medicaid-pi-beneficiaries-disenrolled-total-california-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Reference class and base rate: the recent first-print California reference class is Dec 2025-Mar 2026, because the June 2025 California row appears to be a different operating regime with only 5% disenrolled. The recent base rate is about 21% disenrolled on roughly 1.0-1.14 million renewals due, implying a low-220k count.","Prior/update/interval: persistence prior uses recent California first-print implied counts 230,447, 239,076, 210,647, and 221,248. Adjustment components: level holds total due near 1,057,000, momentum is flat because the CA disenrollment rate is 21% in four consecutive prints, one-off adjustment ignores the March enrollment reporting revision because it affected enrollment counts rather than renewal outcomes, and policy-mechanism adjustment keeps the 2026 higher-disenrollment regime. Point = 1,057,000 expected renewals due * 21.0% = 221,970, rounded to 222,000. Interval method uses sample dispersion of the recent flow values themselves: mean = 225,354.5 and sigma = 12,212; 80% half-width is roughly 1.28*sigma = 15,631, rounded to 16,000, so 222,000 +/- 16,000 gives 206,000 to 238,000."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 7 source-context item(s), activity log present.","evidence":["Tool call: Checked CMS monthly snapshot page and latest release list for official release timing and source identity.","Tool result: CMS page says the Snapshot captures Performance Indicator Data and Eligibility Processing Data; it lists March 2026 released June 26, 2026, February 2026 released May 29, 2026, January 2026 released April 24, 2026, and June 2025 released September 26, 2025. The canonical ledger resolutionDate used here is 2026-09-25; the draft evidence did not include an official CMS June 2026 placeholder independently verifying that date."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this targets the original first-print California state row, reporting month June 2026, Eligibility Processing Data, total beneficiaries disenrolled from Medicaid/CHIP coverage. The release variant is preliminary/original first print, not updated quarterly renewal outcomes.","Tool call: Checked CMS monthly snapshot page and latest release list for official release timing and source identity."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 32000, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior uses recent California first-print implied counts 230,447, 239,076, 210,647, and 221,248. Adjustment components: level holds total due near 1,057,000, momentum is flat because the CA disenrollment rate is 21% in four consecutive prints, one-off adjustment ignores the March enrollment reporting revision because it affected enrollment counts rather than renewal outcomes, and policy-mechanism adjustment keeps the 2026 higher-disenrollment regime. Point = 1,057,000 expected renewals due * 21.0% = 221,970, rounded to 222,000. Interval method uses sample dispersion of the recent flow values themselves: mean = 225,354.5 and sigma = 12,212; 80% half-width is roughly 1.28*sigma = 15,631, rounded to 16,000, so 222,000 +/- 16,000 gives 206,000 to 238,000.","Counter-considerations: upside risk is renewals due above about 1.13 million at a 21% disenrollment rate or a procedural-discontinuance jump, which would land above the interval. Downside risk is a disenrollment rate below about 19.5% at the expected cohort size or a return toward California's June 2025 mitigation pattern, which would land below the interval. Outside the interval would most likely reflect a discrete California operational or reporting-policy change rather than ordinary monthly noise."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Reference class and base rate: the recent first-print California reference class is Dec 2025-Mar 2026, because the June 2025 California row appears to be a different operating regime with only 5% disenrolled. The recent base rate is about 21% disenrolled on roughly 1.0-1.14 million renewals due, implying a low-220k count.","Prior/update/interval: persistence prior uses recent California first-print implied counts 230,447, 239,076, 210,647, and 221,248. Adjustment components: level holds total due near 1,057,000, momentum is flat because the CA disenrollment rate is 21% in four consecutive prints, one-off adjustment ignores the March enrollment reporting revision because it affected enrollment counts rather than renewal outcomes, and policy-mechanism adjustment keeps the 2026 higher-disenrollment regime. Point = 1,057,000 expected renewals due * 21.0% = 221,970, rounded to 222,000. Interval method uses sample dispersion of the recent flow values themselves: mean = 225,354.5 and sigma = 12,212; 80% half-width is roughly 1.28*sigma = 15,631, rounded to 16,000, so 222,000 +/- 16,000 gives 206,000 to 238,000."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-considerations: upside risk is renewals due above about 1.13 million at a 21% disenrollment rate or a procedural-discontinuance jump, which would land above the interval. Downside risk is a disenrollment rate below about 19.5% at the expected cohort size or a return toward California's June 2025 mitigation pattern, which would land below the interval. Outside the interval would most likely reflect a discrete California operational or reporting-policy change rather than ordinary monthly noise."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["California June 2026 Medicaid/CHIP disenrollment forecast","Tool call: Fetched older California and national renewal reference points from CMS December 2025 and June 2025 snapshots."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: cms-medicaid-pi-beneficiaries-disenrolled-total-california-june-2026\nrunLabel: Headline\nresolutionDate: 2026-09-25\ntraceLineCount: 13\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.continued-claims-week-2026-07-04.2026-07-07T17-40-20Z.b034a6720f644aee","runId":"run.continued-claims-week-2026-07-04.2026-07-07T17-40-20Z.b034a6720f644aee","predictionId":"continued-claims-week-2026-07-04","specId":"spec.continued-claims-week-2026-07-04","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Framing and exact resolver: this forecasts the DOL ETA first-print regular-state-program seasonally adjusted insured unemployment series, also called continued claims, for the week ending July 4, 2026. The target is in millions; the release prose reports persons while the historical table reports thousands for the same SA variant, so all anchors here are converted to millions.","Tool result: The table showed Insured Unemployment (SA) of 1,814,000 for June 20, 1,812,000 for June 13, 1,800,000 for June 6, and prior-year comparable 1,954,000; Insured Unemployment Rate (SA) was 1.2 percent."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this forecasts the DOL ETA first-print regular-state-program seasonally adjusted insured unemployment series, also called continued claims, for the week ending July 4, 2026. The target is in millions; the release prose reports persons while the historical table reports thousands for the same SA variant, so all anchors here are converted to millions.","Tool call: Read the DOL publication schedule on the official claims archive page https://oui.doleta.gov/unemploy/claims_arch.asp."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this forecasts the DOL ETA first-print regular-state-program seasonally adjusted insured unemployment series, also called continued claims, for the week ending July 4, 2026. The target is in millions; the release prose reports persons while the historical table reports thousands for the same SA variant, so all anchors here are converted to millions.","Tool call: Opened DOL UI Weekly Claims latest news release at https://www.dol.gov/ui/data.pdf and read the release header and seasonally adjusted data text."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.08, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = latest 1.814 million for week ending June 20. Historical sample = last 13 one-week SA insured-unemployment changes ending June 20, 2026 from the DOL release table: -45, +22, -1, -32, -18, +18, -5, +14, -14, +15, +14, +12, +2 thousand, with mean about -1.4 thousand and sigma = 20.7 thousand per week. Adjustment components: level +0.000 million, recent momentum +0.012 million over two weeks, easing initial-claims inflow -0.006 million, no special policy effect +0.000 million, giving 1.814 + 0.006 = 1.820 million. For a two-week-ahead level forecast, sigma = sqrt(2) * 0.0207 = 0.0293 million, and 1.28*sigma = 0.0375 million, so the 80% interval is about 1.820 +/- 0.038 = [1.783, 1.858] million.","Counter-considerations: upside risk is that continued claims keep drifting higher from benefit-duration persistence or state-level school-year layoffs, which would land above the interval if July 4 SA insured unemployment is above 1.858 million. Downside risk is that recent lower initial claims feed through faster than usual or June increases are revised away, which would land below the interval if the first print is under 1.783 million. Outside the interval would most likely require either a two-week jump above about 44,000 from the June 20 level or a drop of more than about 31,000."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior = latest 1.814 million for week ending June 20. Historical sample = last 13 one-week SA insured-unemployment changes ending June 20, 2026 from the DOL release table: -45, +22, -1, -32, -18, +18, -5, +14, -14, +15, +14, +12, +2 thousand, with mean about -1.4 thousand and sigma = 20.7 thousand per week. Adjustment components: level +0.000 million, recent momentum +0.012 million over two weeks, easing initial-claims inflow -0.006 million, no special policy effect +0.000 million, giving 1.814 + 0.006 = 1.820 million. For a two-week-ahead level forecast, sigma = sqrt(2) * 0.0207 = 0.0293 million, and 1.28*sigma = 0.0375 million, so the 80% interval is about 1.820 +/- 0.038 = [1.783, 1.858] million."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate / reference class: over recent official weekly SA continued-claims changes, a persistence or local-random-walk prior is usually hard to beat for two weeks ahead. The recent level is near 1.81 million, below the comparable 2025 level of 1.954 million but rising modestly through June 2026.","Counter-considerations: upside risk is that continued claims keep drifting higher from benefit-duration persistence or state-level school-year layoffs, which would land above the interval if July 4 SA insured unemployment is above 1.858 million. Downside risk is that recent lower initial claims feed through faster than usual or June increases are revised away, which would land below the interval if the first print is under 1.783 million. Outside the interval would most likely require either a two-week jump above about 44,000 from the June 20 level or a drop of more than about 31,000."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for DOL ETA SA continued claims, week ending July 4, 2026","Framing and exact resolver: this forecasts the DOL ETA first-print regular-state-program seasonally adjusted insured unemployment series, also called continued claims, for the week ending July 4, 2026. The target is in millions; the release prose reports persons while the historical table reports thousands for the same SA variant, so all anchors here are converted to millions."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: continued-claims-week-2026-07-04\nrunLabel: Headline\nresolutionDate: 2026-07-16\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.average-hourly-earnings-mom-may-2026.2026-06-08T00-00-00-02-00.b3a9e8ee3dcac863","runId":"run.average-hourly-earnings-mom-may-2026.2026-06-08T00-00-00-02-00.b3a9e8ee3dcac863","predictionId":"average-hourly-earnings-mom-may-2026","specId":"spec.average-hourly-earnings-mom-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.24,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Average hourly earnings connects labor-market tightness to household income and price pressure, and resolves on the same schedule as payrolls and unemployment. This target resolves on 2026-06-05 under a first-print rule, with an expected ~1 day lag. The same series can also spawn next release, +3 months, threshold questions.","Tool call: bls.lookup({ series: \"CES0500000003\", months: [\"2026-01\", \"2026-04\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Monthly next release cell","Average hourly earnings connects labor-market tightness to household income and price pressure, and resolves on the same schedule as payrolls and unemployment. This target resolves on 2026-06-05 under a first-print rule, with an expected ~1 day lag. The same series can also spawn next release, +3 months, threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.4, distribution present, forecast step count 1.","evidence":["Forecast: point 0.2, 80% interval [0, 0.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Average hourly earnings connects labor-market tightness to household income and price pressure, and resolves on the same schedule as payrolls and unemployment. This target resolves on 2026-06-05 under a first-print rule, with an expected ~1 day lag. The same series can also spawn next release, +3 months, threshold questions.","April earnings rose 0.2% to $37.41 and recent monthly changes have stayed near 0.2%-0.3%. The agent keeps the center at 0.2% because claims and payroll context do not yet point to wage acceleration."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["April earnings rose 0.2% to $37.41 and recent monthly changes have stayed near 0.2%-0.3%. The agent keeps the center at 0.2% because claims and payroll context do not yet point to wage acceleration.","Forecast: point 0.2, 80% interval [0, 0.4]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: average-hourly-earnings-mom-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-05\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.core-cpi-mom-may-2026.2026-06-06T23-43-56-02-00.739543bf6e74a03a","runId":"run.core-cpi-mom-may-2026.2026-06-06T23-43-56-02-00.739543bf6e74a03a","predictionId":"core-cpi-mom-may-2026","specId":"spec.core-cpi-mom-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Core CPI is the cleaner inflation-pressure target behind tax bracket indexing, poverty guideline indexing, and real-income adjustments. This target resolves on 2026-06-10 under a first-print rule, with an expected ~1 week lag. The same series can also spawn next release, +12 months, threshold questions.","Tool call: bls.lookup({ series: \"CUSR0000SA0L1E\", months: [\"2026-01\", \"2026-04\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Core CPI is the cleaner inflation-pressure target behind tax bracket indexing, poverty guideline indexing, and real-income adjustments. This target resolves on 2026-06-10 under a first-print rule, with an expected ~1 week lag. The same series can also spawn next release, +12 months, threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.3, distribution present, forecast step count 1.","evidence":["Forecast: point 0.3, 80% interval [0.1, 0.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Core CPI is the cleaner inflation-pressure target behind tax bracket indexing, poverty guideline indexing, and real-income adjustments. This target resolves on 2026-06-10 under a first-print rule, with an expected ~1 week lag. The same series can also spawn next release, +12 months, threshold questions."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Core CPI rose 0.4% in April after two 0.2% readings. The ensemble puts the unrounded center near 0.25%: shelter and services remain sticky, but April's rent/OER contribution is expected to fade enough that the modal rounded print is between 0.2% and 0.3%."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { agent_points: [0.24, 0.23, 0.29], ensemble_unrounded_point: 0.25, ensemble_ci80: [0.10, 0.40], likely_rounded_print: 0.3 }","Forecast: point 0.3, 80% interval [0.1, 0.4]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: core-cpi-mom-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-10\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.jolts-job-openings-may-2026.2026-06-08T00-00-00-02-00.50a86ca6e7e6dcd3","runId":"run.jolts-job-openings-may-2026.2026-06-08T00-00-00-02-00.50a86ca6e7e6dcd3","predictionId":"jolts-job-openings-may-2026","specId":"spec.jolts-job-openings-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.22,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["JOLTS openings add a labor-demand target that resolves after payrolls but before many policy outcomes, giving agents a useful intermediate calibration signal. This target resolves on 2026-06-30 under a first-print rule, with an expected ~4 weeks lag. The same series can also spawn next release, +3 months, threshold questions.","Tool call: bls.lookup({ series: \"JTS000000000000000JOL\", months: [\"2026-01\", \"2026-04\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Monthly next release cell","JOLTS openings add a labor-demand target that resolves after payrolls but before many policy outcomes, giving agents a useful intermediate calibration signal. This target resolves on 2026-06-30 under a first-print rule, with an expected ~4 weeks lag. The same series can also spawn next release, +3 months, threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1350, distribution present, forecast step count 1.","evidence":["April's preliminary openings jumped to 7.618 million after softer February-March readings. The agent partially fades that jump while keeping a wide interval because JOLTS first prints are noisy.","Forecast: point 7450, 80% interval [6800, 8150]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["April's preliminary openings jumped to 7.618 million after softer February-March readings. The agent partially fades that jump while keeping a wide interval because JOLTS first prints are noisy."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["JOLTS openings add a labor-demand target that resolves after payrolls but before many policy outcomes, giving agents a useful intermediate calibration signal. This target resolves on 2026-06-30 under a first-print rule, with an expected ~4 weeks lag. The same series can also spawn next release, +3 months, threshold questions."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["April's preliminary openings jumped to 7.618 million after softer February-March readings. The agent partially fades that jump while keeping a wide interval because JOLTS first prints are noisy.","Forecast: point 7450, 80% interval [6800, 8150]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: jolts-job-openings-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.jolts-job-openings-may-2026.2026-06-27T13-11-02Z.jolts-job-openings-may-2026-thesis-analyst-fast-2026-06-27t13-11-02z.a6575efa2a1f409c","runId":"run.jolts-job-openings-may-2026.2026-06-27T13-11-02Z.jolts-job-openings-may-2026-thesis-analyst-fast-2026-06-27t13-11-02z.a6575efa2a1f409c","predictionId":"jolts-job-openings-may-2026","specId":"spec.jolts-job-openings-may-2026","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base-rate/reference-class anchor: the 2025 average from fetched BLS monthly levels is about 7,082 thousand, while the first four months of 2026 average about 7,167 thousand. That keeps the outside-view anchor around 7.1 to 7.2 million rather than treating April's 7.618 million as the new trend.","Model prior: I use a simple persistence plus mean-reversion prior, not a fitted time-series model, because this fast run has few fetched points and JOLTS first prints have substantial survey noise that would make a lightly specified fitted model overconfident."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Forecast for May 2026 first-print BLS JOLTS total job openings","The resolver is the BLS first print for total nonfarm job openings, seasonally adjusted, level in thousands, for May 2026. The forecast value 7350 means 7.350 million openings."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast for May 2026 first-print BLS JOLTS total job openings","The resolver is the BLS first print for total nonfarm job openings, seasonally adjusted, level in thousands, for May 2026. The forecast value 7350 means 7.350 million openings."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1400, distribution present, forecast step count 1.","evidence":["Counter-consideration: JOLTS openings can swing sharply on survey noise and industry composition. If April's spike was genuine vacancy rebuilding, May could print above 8.0 million; if it was sampling noise or employers pulled postings after tariff and demand uncertainty, a print near 6.6 million is plausible.","Recent monthly changes from fetched levels were Feb minus Jan = -318, Mar minus Feb = -35, and Apr minus Mar = +731 thousand; the average absolute move over those three changes is about 361 thousand. I place May 268 thousand below April but above the 2026 average: 7618 - 268 = 7350. For the 80% interval, I use judgmental uncertainty of about +/-700 thousand, roughly twice the recent average absolute move and wide enough to cover a large reversal or continuation: 7350 - 700 = 6650 and 7350 + 700 = 8050."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Model prior: I use a simple persistence plus mean-reversion prior, not a fitted time-series model, because this fast run has few fetched points and JOLTS first prints have substantial survey noise that would make a lightly specified fitted model overconfident.","Level and momentum effects point in opposite directions. April's 7.618 million level is high relative to January through March, but May payrolls were solid and unemployment was unchanged, so I expect only a partial reversal of the April jump rather than a fall back to the March trough."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level and momentum effects point in opposite directions. April's 7.618 million level is high relative to January through March, but May payrolls were solid and unemployment was unchanged, so I expect only a partial reversal of the April jump rather than a fall back to the March trough.","Counter-consideration: JOLTS openings can swing sharply on survey noise and industry composition. If April's spike was genuine vacancy rebuilding, May could print above 8.0 million; if it was sampling noise or employers pulled postings after tariff and demand uncertainty, a print near 6.6 million is plausible."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for May 2026 first-print BLS JOLTS total job openings","The resolver is the BLS first print for total nonfarm job openings, seasonally adjusted, level in thousands, for May 2026. The forecast value 7350 means 7.350 million openings."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: jolts-job-openings-may-2026\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-06-30\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-max-allotment-four-person-fy2027.2026-06-08T00-00-00-02-00.c820754f26f0f0ef","runId":"run.snap-max-allotment-four-person-fy2027.2026-06-08T00-00-00-02-00.c820754f26f0f0ef","predictionId":"snap-max-allotment-four-person-fy2027","specId":"spec.snap-max-allotment-four-person-fy2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.92,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["SNAP maximum allotments are policy settings that feed directly into household resources, SPM poverty, and benefit outlay predictions. This target resolves on 2026-09-30 under a first-print rule, with an expected ~3 months lag. The same series can also spawn threshold, +12 months, program-cost impact questions."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["SNAP maximum allotments are policy settings that feed directly into household resources, SPM poverty, and benefit outlay predictions. This target resolves on 2026-09-30 under a first-print rule, with an expected ~3 months lag. The same series can also spawn threshold, +12 months, program-cost impact questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 40, distribution present, forecast step count 1.","evidence":["Forecast: point 1022, 80% interval [1005, 1045]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The FY2026 value is $994. Crossing $1,020 requires about a 2.6% increase; the agent assigns a central value just above the threshold because food-plan inflation makes that plausible but not assured."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["The FY2026 value is $994. Crossing $1,020 requires about a 2.6% increase; the agent assigns a central value just above the threshold because food-plan inflation makes that plausible but not assured."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 1022, 80% interval [1005, 1045]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-max-allotment-four-person-fy2027\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-max-allotment-four-person-fy2027.2026-06-27T23-13-24Z.snap-max-allotment-four-person-fy2027-thesis-analyst-fast-2026-06-27t23-13-24z.3f4ac16344e7acad","runId":"run.snap-max-allotment-four-person-fy2027.2026-06-27T23-13-24Z.snap-max-allotment-four-person-fy2027-thesis-analyst-fast-2026-06-27t23-13-24z.3f4ac16344e7acad","predictionId":"snap-max-allotment-four-person-fy2027","specId":"spec.snap-max-allotment-four-person-fy2027","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 3 historical point(s) and explicit outside-view language.","evidence":["Tool result: Fetched canonical slug snap-max-allotment-family-4-fy2027; catalog values include FY2024 973, FY2025 975, FY2026e 994, prior point 1010, prior CI 975 to 1045, and ledger resolutionDate 2026-09-30.","Tool result: Fetched 7 CFR 273.10 current as of 6/24/2026; maximum allotments are adjusted annually, posted in an FNS web table, effective October 1, and based on 100% of the preceding June TFP rounded down to the nearest lower dollar."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 6 typed tool call(s), 7 source-context item(s), activity log present.","evidence":["Resolver is the first official USDA FNS FY2027 SNAP COLA memorandum or table for the household-size-4 maximum monthly allotment in the 48 contiguous states and DC. The repo already registers the canonical slug snap-max-allotment-family-4-fy2027 and target date 2026-09-30, so I reuse that rather than creating a near-duplicate.","Tool call: rg and sed over forecast-cells.ts and ledger-targets.generated.ts for the target registration"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Resolver is the first official USDA FNS FY2027 SNAP COLA memorandum or table for the household-size-4 maximum monthly allotment in the 48 contiguous states and DC. The repo already registers the canonical slug snap-max-allotment-family-4-fy2027 and target date 2026-09-30, so I reuse that rather than creating a near-duplicate.","Tool call: Open BLS May 2026 CPI release for current food-at-home momentum"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 55, distribution present, forecast step count 1.","evidence":["Tool result: Fetched ERS June 2026 forecast: food-at-home prices predicted +2.8 percent in 2026 with 95 percent prediction interval 1.4 to 4.4 percent; all food +3.2 percent with interval 2.2 to 4.2 percent.","Point: 994 dollars FY2026 anchor x 1.027 May food-at-home momentum = 1020.8, rounded to 1021 dollars. Interval: translate uncertainty around June 2026 TFP movement, publication rounding down to whole dollars, and modest policy/mechanical risk into about +0.6% to +6.1% from the 994 anchor, giving 994 x 1.006 = 1000 and 994 x 1.061 = 1055. This is wider than the ERS 1.4% to 4.4% food-at-home prediction interval because the resolver is the TFP basket, not CPI itself, and because policy or basket-specific food movements can add tail risk."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Open BLS May 2026 CPI release for current food-at-home momentum","Level, momentum, and mechanism: the best level anchor is the FY2026 catalog anchor of 994 dollars. Current grocery inflation has not collapsed; BLS shows 2.7 percent year-over-year food-at-home inflation in May 2026 and ERS puts 2026 food-at-home inflation at 2.8 percent. The eCFR rule makes this a mechanical TFP/June-cost update unless Congress or USDA changes the TFP basis before the FY2027 table."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Point: 994 dollars FY2026 anchor x 1.027 May food-at-home momentum = 1020.8, rounded to 1021 dollars. Interval: translate uncertainty around June 2026 TFP movement, publication rounding down to whole dollars, and modest policy/mechanical risk into about +0.6% to +6.1% from the 994 anchor, giving 994 x 1.006 = 1000 and 994 x 1.061 = 1055. This is wider than the ERS 1.4% to 4.4% food-at-home prediction interval because the resolver is the TFP basket, not CPI itself, and because policy or basket-specific food movements can add tail risk.","Catalog-prior reconciliation: the local prior point of 1010 and CI of 975 to 1045 looked too low after incorporating the 994 FY2026 anchor plus May 2026 food-at-home CPI at 2.7 percent and ERS 2026 food-at-home midpoint at 2.8 percent, so I shift the point up to 1021 and move the interval to 1000 to 1055 while keeping a similar uncertainty width."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: rg and sed over forecast-cells.ts and ledger-targets.generated.ts for the target registration","Tool result: Fetched canonical slug snap-max-allotment-family-4-fy2027; catalog values include FY2024 973, FY2025 975, FY2026e 994, prior point 1010, prior CI 975 to 1045, and ledger resolutionDate 2026-09-30."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-max-allotment-four-person-fy2027\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-09-30\ntraceLineCount: 21\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.hhs-poverty-guideline-family-four-2027.2026-06-08T00-00-00-02-00.93496d1de1da38c0","runId":"run.hhs-poverty-guideline-family-four-2027.2026-06-08T00-00-00-02-00.93496d1de1da38c0","predictionId":"hhs-poverty-guideline-family-four-2027","specId":"spec.hhs-poverty-guideline-family-four-2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.05,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":["The 2026 value is $33,000. A moderate CPI-U adjustment should lift the 2027 guideline by roughly $800-$1,400, with remaining uncertainty from the poverty-threshold base and rounding."]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["The poverty guideline is a policy setting used across Medicaid, marketplace subsidies, legal aid, and other eligibility thresholds. This target resolves on 2027-01-31 under a first-print rule, with an expected ~7 months lag. The same series can also spawn next release, threshold, program eligibility questions."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Annual next release cell","The poverty guideline is a policy setting used across Medicaid, marketplace subsidies, legal aid, and other eligibility thresholds. This target resolves on 2027-01-31 under a first-print rule, with an expected ~7 months lag. The same series can also spawn next release, threshold, program eligibility questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 960, distribution present, forecast step count 1.","evidence":["The 2026 value is $33,000. A moderate CPI-U adjustment should lift the 2027 guideline by roughly $800-$1,400, with remaining uncertainty from the poverty-threshold base and rounding.","Forecast: point 33920, 80% interval [33520, 34480]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["The 2026 value is $33,000. A moderate CPI-U adjustment should lift the 2027 guideline by roughly $800-$1,400, with remaining uncertainty from the poverty-threshold base and rounding."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 33920, 80% interval [33520, 34480]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: hhs-poverty-guideline-family-four-2027\nrunLabel: Headline\nresolutionDate: 2027-01-31\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: resolution clarity (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.ctc-maximum-per-child-ty2027.2026-06-08T00-00-00-02-00.d936ac8dc4161790","runId":"run.ctc-maximum-per-child-ty2027.2026-06-08T00-00-00-02-00.d936ac8dc4161790","predictionId":"ctc-maximum-per-child-ty2027","specId":"spec.ctc-maximum-per-child-ty2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 3 historical point(s) and explicit outside-view language.","evidence":["The Child Tax Credit maximum is a policy setting with direct consequences for tax liability, refundable credits, child poverty, and PolicyEngine baseline assumptions. This target resolves on 2026-10-31 under a first-print rule, with an expected ~4 months lag. The same series can also spawn threshold, +12 months, poverty impact questions."]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["The Child Tax Credit maximum is a policy setting with direct consequences for tax liability, refundable credits, child poverty, and PolicyEngine baseline assumptions. This target resolves on 2026-10-31 under a first-print rule, with an expected ~4 months lag. The same series can also spawn threshold, +12 months, poverty impact questions."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The Child Tax Credit maximum is a policy setting with direct consequences for tax liability, refundable credits, child poverty, and PolicyEngine baseline assumptions. This target resolves on 2026-10-31 under a first-print rule, with an expected ~4 months lag. The same series can also spawn threshold, +12 months, poverty impact questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 300, distribution present, forecast step count 1.","evidence":["The agent centers on $2,300 because TY2026 guidance places the amount near $2,200 and inflation indexing plus rounding can move the TY2027 setting above $2,250. The interval leaves room for no upward rounding or a larger statutory change.","Forecast: point 2300, 80% interval [2200, 2500]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The agent centers on $2,300 because TY2026 guidance places the amount near $2,200 and inflation indexing plus rounding can move the TY2027 setting above $2,250. The interval leaves room for no upward rounding or a larger statutory change."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The agent centers on $2,300 because TY2026 guidance places the amount near $2,200 and inflation indexing plus rounding can move the TY2027 setting above $2,250. The interval leaves room for no upward rounding or a larger statutory change.","Forecast: point 2300, 80% interval [2200, 2500]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: ctc-maximum-per-child-ty2027\nrunLabel: Headline\nresolutionDate: 2026-10-31\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.ctc-maximum-per-child-ty2027.2026-06-27T23-29-48Z.ctc-maximum-per-child-ty2027-thesis-analyst-fast-2026-06-27t23-29-48z.5bbbe1ce314f509d","runId":"run.ctc-maximum-per-child-ty2027.2026-06-27T23-29-48Z.ctc-maximum-per-child-ty2027-thesis-analyst-fast-2026-06-27t23-29-48z.5bbbe1ce314f509d","predictionId":"ctc-maximum-per-child-ty2027","specId":"spec.ctc-maximum-per-child-ty2027","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 3 historical point(s) and explicit outside-view language.","evidence":["Tool result: Fetched existing related catalog cell ctc-monthly-max-ty2027 with historical monthly values 2021 = 300, 2022 = 167, 2024 = 167, 2025 = 167, and 2026e = 167; records also showed ctc-maximum-per-child-ty2027 as the obvious canonical maximum-per-child slug.","Base-rate/reference class: recent official IRS annual inflation adjustments for this exact parameter show the base moving from the old $2,000 regime to $2,200 under Public Law 119-21, with TY2026 still $2,200 because the first year of chained-CPI growth over the 2024 base did not produce a full $100 rounded-down increase. The outside-view prior is therefore sticky at $2,200 or a one-notch move to $2,300, not a continuous estimate."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["The resolver is the first official IRS dollar value for the maximum Child Tax Credit per qualifying child for tax year 2027. This is the maximum under IRC section 24(a) as modified by section 24(h)(2), not the refundable portion under section 24(h)(5), a phase-in rate, a phaseout threshold, or a monthly equivalent.","Tool call: Opened BLS May 2026 CPI release for inflation momentum relevant to the remaining statutory chained-CPI months."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The resolver is the first official IRS dollar value for the maximum Child Tax Credit per qualifying child for tax year 2027. This is the maximum under IRC section 24(a) as modified by section 24(h)(2), not the refundable portion under section 24(h)(5), a phase-in rate, a phaseout threshold, or a monthly equivalent.","Tool call: Opened IRS Rev. Proc. 2025-32 for tax year 2026 annual inflation adjustments and the IRS tax-year 2026 inflation-adjustment release page."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 200, distribution present, forecast step count 1.","evidence":["Mechanism decomposition: level is the statutory $2,200 base; momentum comes from elevated 2026 inflation, especially the May 2026 C-CPI-U 4.0 percent 12-month increase; the one-off component is energy-price pressure that may fade before August; policy risk is small because Public Law 119-21 already made the credit permanent, but Congress could still amend section 24 before the IRS print.","Counter-consideration: the no-change $2,200 case remains plausible if June-August chained CPI is soft enough, if preliminary C-CPI-U revisions lower the 12-month average, or if IRS applies a technical convention that leaves the cumulative adjustment just below the $100 threshold. An upside outside the interval would require a legislative expansion or unusually high inflation producing a $2,500-or-higher official value; a downside outside the interval would require repeal or a statutory cut."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Opened BLS May 2026 CPI release for inflation momentum relevant to the remaining statutory chained-CPI months.","Base-rate/reference class: recent official IRS annual inflation adjustments for this exact parameter show the base moving from the old $2,000 regime to $2,200 under Public Law 119-21, with TY2026 still $2,200 because the first year of chained-CPI growth over the 2024 base did not produce a full $100 rounded-down increase. The outside-view prior is therefore sticky at $2,200 or a one-notch move to $2,300, not a continuous estimate."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool result: Fetched release schedule: Consumer Price Index for August 2026 is scheduled for September 11, 2026 at 08:30 AM Eastern; this fixes the last month in the September 2025-August 2026 CPI window used for calendar-year 2027 tax inflation adjustments, but the resolving source remains the later IRS first-print tax-year 2027 inflation-adjustment publication.","Mechanism decomposition: level is the statutory $2,200 base; momentum comes from elevated 2026 inflation, especially the May 2026 C-CPI-U 4.0 percent 12-month increase; the one-off component is energy-price pressure that may fade before August; policy risk is small because Public Law 119-21 already made the credit permanent, but Congress could still amend section 24 before the IRS print."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for TY2027 maximum Child Tax Credit per child","Simple discrete nowcast prior: using the May 2026 chained-CPI momentum and the remaining June-August window, I assign roughly 25 percent to a $2,200 IRS print, 60 percent to $2,300, 12 percent to $2,400, and 3 percent to policy or inflation outcomes outside that range. I do not use a richer time-series model because the rounded statutory threshold dominates the forecast and only three monthly CPI inputs remain before the formula is fixed."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: ctc-maximum-per-child-ty2027\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-10-31\ntraceLineCount: 19\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-participation-march-2026.2026-06-08T00-00-00-02-00.a30fcc99296dd29e","runId":"run.snap-participation-march-2026.2026-06-08T00-00-00-02-00.a30fcc99296dd29e","predictionId":"snap-participation-march-2026","specId":"spec.snap-participation-march-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["SNAP participation is a direct administrative calibration target for eligibility, take-up, benefit outlay, and poverty-resource predictions. This target resolves on 2026-07-31 under a fixed-vintage rule, with an expected ~3 months lag. The same series can also spawn next release, +3 months, program-cost impact questions.","Tool call: usda.fns.lookup({ program: \"snap\", table: \"national_view_summary\", measure: \"persons\", months: [\"2025-11\", \"2026-02\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Monthly next release cell","SNAP participation is a direct administrative calibration target for eligibility, take-up, benefit outlay, and poverty-resource predictions. This target resolves on 2026-07-31 under a fixed-vintage rule, with an expected ~3 months lag. The same series can also spawn next release, +3 months, program-cost impact questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.4, distribution present, forecast step count 1.","evidence":["February 2026 participation was about 37.87 million. The agent expects continued decline from recent administrative trend, with a wide enough interval for reporting revisions and state recertification noise.","Forecast: point 37.1, 80% interval [36.4, 37.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["February 2026 participation was about 37.87 million. The agent expects continued decline from recent administrative trend, with a wide enough interval for reporting revisions and state recertification noise.","Forecast: point 37.1, 80% interval [36.4, 37.8]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-participation-march-2026\nrunLabel: Headline\nresolutionDate: 2026-07-31\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: resolution clarity (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-participation-march-2026.2026-06-27T13-28-36Z.snap-participation-march-2026-thesis-analyst-fast-2026-06-27t13-28-36z.93b04b2071d5c976","runId":"run.snap-participation-march-2026.2026-06-27T13-28-36Z.snap-participation-march-2026-thesis-analyst-fast-2026-06-27t13-28-36z.93b04b2071d5c976","predictionId":"snap-participation-march-2026","specId":"spec.snap-participation-march-2026","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base-rate/reference-class anchor: recent official monthly participation is tightly clustered around 41.7 million. A neutral outside-view forecast therefore starts near 41.75 million before adding early-2026 macro and policy adjustments.","Model choice: I did not use a formal time-series model because the latest official points show very low short-run trend signal and the largest uncertainty is administrative/policy implementation; a persistence baseline with explicit judgmental adjustments is adequate for this fast public-release forecast."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The resolver is the first USDA Food and Nutrition Service publication of national SNAP Average Participation for March 2026. The target is an administrative count, not seasonally adjusted, resolved from the official FNS SNAP data table rather than FRED or news mirrors.","Tool result: Fetched official monthly national Average Participation reference points, converted from persons to millions: FY2025 Mar 41.759 million, FY2025 Jun 41.812 million, FY2025 Sep 41.734 million, and FY2025 Nov 41.687 million; the page also showed Latest Available Month November 2025."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Forecast for USDA FNS SNAP March 2026 First-Print Participation","The resolver is the first USDA Food and Nutrition Service publication of national SNAP Average Participation for March 2026. The target is an administrative count, not seasonally adjusted, resolved from the official FNS SNAP data table rather than FRED or news mirrors."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.9, distribution present, forecast step count 1.","evidence":["Tool result: Fetched program context showing SNAP serves about 42 million people nationally and is administered through 50 states plus the District of Columbia, which explains state-reporting lag risk.","Model choice: I did not use a formal time-series model because the latest official points show very low short-run trend signal and the largest uncertainty is administrative/policy implementation; a persistence baseline with explicit judgmental adjustments is adequate for this fast public-release forecast."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Model choice: I did not use a formal time-series model because the latest official points show very low short-run trend signal and the largest uncertainty is administrative/policy implementation; a persistence baseline with explicit judgmental adjustments is adequate for this fast public-release forecast.","Level and momentum: the cited latest visible official points range from 41.687 million to 41.812 million, only a 0.125 million span across the selected recent months, so I keep the level close to the 41.75 million baseline and do not extrapolate a large trend."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool result: Fetched program context showing SNAP serves about 42 million people nationally and is administered through 50 states plus the District of Columbia, which explains state-reporting lag risk.","Model choice: I did not use a formal time-series model because the latest official points show very low short-run trend signal and the largest uncertainty is administrative/policy implementation; a persistence baseline with explicit judgmental adjustments is adequate for this fast public-release forecast."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for USDA FNS SNAP March 2026 First-Print Participation","Tool result: Fetched official monthly national Average Participation reference points, converted from persons to millions: FY2025 Mar 41.759 million, FY2025 Jun 41.812 million, FY2025 Sep 41.734 million, and FY2025 Nov 41.687 million; the page also showed Latest Available Month November 2025."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-participation-march-2026\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-07-31\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.wic-total-participation-march-2026.2026-06-08T00-00-00-02-00.7c6c524af4995d78","runId":"run.wic-total-participation-march-2026.2026-06-08T00-00-00-02-00.7c6c524af4995d78","predictionId":"wic-total-participation-march-2026","specId":"spec.wic-total-participation-march-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["WIC participation tests whether agents can track benefit-program take-up, recertification, birth-cohort effects, and program-operation changes. This target resolves on 2026-07-31 under a fixed-vintage rule, with an expected ~3 months lag. The same series can also spawn next release, +3 months, child participation questions."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Monthly next release cell","WIC participation tests whether agents can track benefit-program take-up, recertification, birth-cohort effects, and program-operation changes. This target resolves on 2026-07-31 under a fixed-vintage rule, with an expected ~3 months lag. The same series can also spawn next release, +3 months, child participation questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.25, distribution present, forecast step count 1.","evidence":["Forecast: point 6.61, 80% interval [6.5, 6.75]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 6.61, 80% interval [6.5, 6.75]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: wic-total-participation-march-2026\nrunLabel: Headline\nresolutionDate: 2026-07-31\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: resolution clarity (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.wic-total-participation-march-2026.2026-06-27T13-31-35Z.wic-total-participation-march-2026-thesis-analyst-fast-2026-06-27t13-31-35z.af7ef7c0021aa3e8","runId":"run.wic-total-participation-march-2026.2026-06-27T13-31-35Z.wic-total-participation-march-2026-thesis-analyst-fast-2026-06-27t13-31-35z.af7ef7c0021aa3e8","predictionId":"wic-total-participation-march-2026","specId":"spec.wic-total-participation-march-2026","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["The resolver is the USDA Food and Nutrition Service WIC Participation and Costs national monthly table, Total Participants, March 2026, first preliminary print. The forecast evidence excludes the March 2026 realized value and uses only the official source family, the prior official vintage, and earlier monthly observations.","Tool result: The official WIC Data Tables page provides monthly national WIC data resources for FY 2026 preliminary reporting and earlier official comparison data; the WIC program served 6,640,819 participants in Feb 2026 in the prior fetched vintage."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The resolver is the USDA Food and Nutrition Service WIC Participation and Costs national monthly table, Total Participants, March 2026, first preliminary print. The forecast evidence excludes the March 2026 realized value and uses only the official source family, the prior official vintage, and earlier monthly observations.","Tool call: Opened the USDA FNS WIC Data Tables page to identify the official source family and monthly national data resources."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is the USDA Food and Nutrition Service WIC Participation and Costs national monthly table, Total Participants, March 2026, first preliminary print. The forecast evidence excludes the March 2026 realized value and uses only the official source family, the prior official vintage, and earlier monthly observations.","Tool call: Fetched the immediately prior official vintage, 37wic-monthly-5.pdf, to establish the latest pre-target information available before the March 2026 first print."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.21, distribution present, forecast step count 1.","evidence":["Point calculation: 0.5 * (6,640,819 + 45,000) + 0.5 * (6,850,836 - 161,356) = 6,687,650, rounded to 6,686,000 after a small downward adjustment for late-2025 and early-2026 softness. The 80% interval is 6,580,000 to 6,795,000, spanning roughly plus 154,000 and minus 106,000 around the point to cover recent first-print seasonal dispersion, reporting timing, and a mildly upside-skewed rebound risk.","Review disposition: Accepted the blocking leakage, update, interval, coherence, and model-prior critiques by removing the realized March 2026 value from evidence and historicalContext, widening the interval to ex-ante forecast uncertainty, and adding a seasonal-persistence prior. Kept the official resolver metadata and June 12 resolution source only for resolution clarity."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Model prior: use a simple seasonal persistence model, averaging two anchors: Feb 2026 plus a roughly 45,000 March seasonal rebound, and Mar 2025 adjusted down by the Feb 2026 year-over-year shortfall versus Feb 2025. This intentionally avoids a more complex time-series model because only a small monthly official reference class is needed for this first-print target."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Point calculation: 0.5 * (6,640,819 + 45,000) + 0.5 * (6,850,836 - 161,356) = 6,687,650, rounded to 6,686,000 after a small downward adjustment for late-2025 and early-2026 softness. The 80% interval is 6,580,000 to 6,795,000, spanning roughly plus 154,000 and minus 106,000 around the point to cover recent first-print seasonal dispersion, reporting timing, and a mildly upside-skewed rebound risk.","Review disposition: Accepted the blocking leakage, update, interval, coherence, and model-prior critiques by removing the realized March 2026 value from evidence and historicalContext, widening the interval to ex-ante forecast uncertainty, and adding a seasonal-persistence prior. Kept the official resolver metadata and June 12 resolution source only for resolution clarity."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The resolver is the USDA Food and Nutrition Service WIC Participation and Costs national monthly table, Total Participants, March 2026, first preliminary print. The forecast evidence excludes the March 2026 realized value and uses only the official source family, the prior official vintage, and earlier monthly observations.","Tool call: Fetched official year-earlier and adjacent-month reference points for seasonal and level context."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: wic-total-participation-march-2026\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-07-31\ntraceLineCount: 19\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-chip-enrollment-march-2026.2026-06-08T00-00-00-02-00.b06dddee869349a9","runId":"run.medicaid-chip-enrollment-march-2026.2026-06-08T00-00-00-02-00.b06dddee869349a9","predictionId":"medicaid-chip-enrollment-march-2026","specId":"spec.medicaid-chip-enrollment-march-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.19,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Medicaid and CHIP enrollment is a near-term administrative bridge between eligibility rules, renewal operations, and later Census coverage outcomes. This target resolves on 2026-07-31 under a fixed-vintage rule, with an expected ~3 months lag. The same series can also spawn next release, +3 months, coverage impact questions."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Monthly next release cell","Medicaid and CHIP enrollment is a near-term administrative bridge between eligibility rules, renewal operations, and later Census coverage outcomes. This target resolves on 2026-07-31 under a fixed-vintage rule, with an expected ~3 months lag. The same series can also spawn next release, +3 months, coverage impact questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.8, distribution present, forecast step count 1.","evidence":["CMS preliminary February enrollment was 74.88 million. The agent expects another decline, with the unwinding tail still visible but slowing.","Forecast: point 74.4, 80% interval [74, 74.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["CMS preliminary February enrollment was 74.88 million. The agent expects another decline, with the unwinding tail still visible but slowing."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 74.4, 80% interval [74, 74.8]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-chip-enrollment-march-2026\nrunLabel: Headline\nresolutionDate: 2026-07-31\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-chip-enrollment-march-2026.2026-06-27T13-24-14Z.medicaid-chip-enrollment-march-2026-thesis-analyst-fast-2026-06-27t13-24-14z.5379a0cf6b8cf164","runId":"run.medicaid-chip-enrollment-march-2026.2026-06-27T13-24-14Z.medicaid-chip-enrollment-march-2026-thesis-analyst-fast-2026-06-27t13-24-14z.5379a0cf6b8cf164","predictionId":"medicaid-chip-enrollment-march-2026","specId":"spec.medicaid-chip-enrollment-march-2026","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base rate: the comparable preliminary series was falling by about 128,000 to 156,000 per month across the latest three month-to-month moves, far below the steep unwinding losses of 2023-2024."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The resolver is CMS's first official preliminary March 2026 Medicaid and CHIP Applications, Eligibility, and Enrollment Data fixed vintage, not an updated vintage and not a third-party mirror.","Tool call: Opened the official Medicaid.gov monthly enrollment reports page and checked the target month link and release timing."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The resolver is CMS's first official preliminary March 2026 Medicaid and CHIP Applications, Eligibility, and Enrollment Data fixed vintage, not an updated vintage and not a third-party mirror.","Tool call: Opened the official Medicaid.gov monthly enrollment reports page and checked the target month link and release timing."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.65, distribution present, forecast step count 1.","evidence":["Recent monthly declines were roughly -152,000, -156,000, and -128,000, with an average near -145,000. I use a milder March decline of -124,000 from 78,184,000, giving 78,060,000. The 80% interval is about 5.6 times the recent average absolute one-month move to allow for state reporting dispersion and first-print noise: 78,060,000 - 810,000 = 77,250,000 and 78,060,000 + 840,000 = 78,900,000.","Counter-consideration: if preliminary March captures more retroactive or late-processed enrollment than usual, the print could sit above February despite the broader downward trend; conversely, a cluster of state methodology changes could push the count below the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level and momentum: starting from 78,184,000 in February, I use a judgmental inside-view adjustment that keeps the decline slightly milder than the recent -145,000 average because the latest move was the smallest of the three fetched changes at about -128,000.","Review disposition: accepted the resolver-date critique by tying resolution to the official March 2026 preliminary link dated June 26, 2026; accepted the interval critique by making the recent-change basis explicit; accepted the update critique by labeling the milder decline as a judgmental adjustment from the latest observed momentum."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["March 2026 CMS Medicaid and CHIP preliminary enrollment forecast","Recent monthly declines were roughly -152,000, -156,000, and -128,000, with an average near -145,000. I use a milder March decline of -124,000 from 78,184,000, giving 78,060,000. The 80% interval is about 5.6 times the recent average absolute one-month move to allow for state reporting dispersion and first-print noise: 78,060,000 - 810,000 = 77,250,000 and 78,060,000 + 840,000 = 78,900,000."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-chip-enrollment-march-2026\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-07-31\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.irs-total-refunds-october-2026.2026-06-08T00-00-00-02-00.2d9bd23270003189","runId":"run.irs-total-refunds-october-2026.2026-06-08T00-00-00-02-00.2d9bd23270003189","predictionId":"irs-total-refunds-october-2026","specId":"spec.irs-total-refunds-october-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.14,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: irs.lookup({ dataset: \"filing_season_statistics\", measure: \"total_amount_refunded\", snapshots: [\"2026-05-08\", \"october_prior_years\"] })","Tool result: { may_8_2026_refunds_billions: 324.757, average_refund: 3276, historical_may_to_october_addition_billions: 41.8 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["IRS cumulative refunds connect filing behavior, withholding, refundable credits, processing pace, and tax-year liability into a near-term administrative target. This target resolves on 2026-10-31 under a first-print rule, with an expected ~4 months lag. The same series can also spawn next release, +3 months, refundable-credit mix questions.","Tool result: { may_8_2026_refunds_billions: 324.757, average_refund: 3276, historical_may_to_october_addition_billions: 41.8 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["IRS cumulative refunds connect filing behavior, withholding, refundable credits, processing pace, and tax-year liability into a near-term administrative target. This target resolves on 2026-10-31 under a first-print rule, with an expected ~4 months lag. The same series can also spawn next release, +3 months, refundable-credit mix questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 22, distribution present, forecast step count 1.","evidence":["Forecast: point 370, 80% interval [360, 382]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 370, 80% interval [360, 382]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: irs-total-refunds-october-2026\nrunLabel: Headline\nresolutionDate: 2026-10-31\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.irs-total-refunds-october-2026.2026-06-27T23-25-31Z.irs-total-refunds-october-2026-thesis-analyst-fast-2026-06-27t23-25-31z.80f75f0c77e236fb","runId":"run.irs-total-refunds-october-2026.2026-06-27T23-25-31Z.irs-total-refunds-october-2026-thesis-analyst-fast-2026-06-27t23-25-31z.80f75f0c77e236fb","predictionId":"irs-total-refunds-october-2026","specId":"spec.irs-total-refunds-october-2026","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.51,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: Opened the IRS Oct. 17, 2025 Filing Season Statistics page for the latest prior-year October analogue.","Base-rate/reference-class step: the cleanest outside view is May-to-first-October additions in the three most recent comparable filing-season pages. Those increments were 42.137, 40.441, and 36.672 billion, averaging 39.75 billion, with a narrow historical range but based on only three observations."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 7 typed tool call(s), 10 source-context item(s), activity log present.","evidence":["Resolver is the IRS Filing Season Statistics current-year individual-return line for total amount refunded in the first October 2026 snapshot whose week-ending date is after the official October 15 extended individual filing deadline. The target is nominal USD billions, not fiscal-year Treasury cash refunds.","Tool result: Fetched official IRS publication surface at irs.gov/newsroom and official individual filing deadline context including October 15 extension timing; the first qualifying 2026 week-ending date after that deadline is October 16, 2026, with the first qualifying IRS Newsroom Filing Season Statistics page to be used once posted."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Resolver is the IRS Filing Season Statistics current-year individual-return line for total amount refunded in the first October 2026 snapshot whose week-ending date is after the official October 15 extended individual filing deadline. The target is nominal USD billions, not fiscal-year Treasury cash refunds.","Tool result: Fetched official IRS publication surface at irs.gov/newsroom and official individual filing deadline context including October 15 extension timing; the first qualifying 2026 week-ending date after that deadline is October 16, 2026, with the first qualifying IRS Newsroom Filing Season Statistics page to be used once posted."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 29, distribution present, forecast step count 1.","evidence":["The 356 to 385 interval implies a May-to-October increment range of 31.243 to 60.243 billion around the 324.757 billion May anchor. The lower tail allows front-loading or processing delays to pull the remaining increment below the recent 36.672 to 42.137 billion band, while the upper tail allows policy-driven late-filer refund claims to add much more than the short three-year reference class.","Counter-consideration: if the 18.1 percent May refund-dollar jump mostly reflects front-loaded direct-deposit refunds rather than higher full-season liability refunds, the remaining May-to-October increment could undershoot the recent band and the outcome could land near the lower end of the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Mechanical base = 324.757 + ((308.986 - 266.849) + (309.929 - 269.488) + (311.651 - 274.979)) / 3 = 324.757 + 39.75 = 364.51. I add about 3.5 billion because 2026 May refunds were already 49.778 billion above May 2025 and the cited tax-year 2026 parameters raise nominal deductions and refundable credit amounts, so only about 7 percent of the year-over-year May refund-dollar gap needs to persist into late filings to justify the adjustment. That gives 368.0."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base-rate/reference-class step: the cleanest outside view is May-to-first-October additions in the three most recent comparable filing-season pages. Those increments were 42.137, 40.441, and 36.672 billion, averaging 39.75 billion, with a narrow historical range but based on only three observations.","Prior-run update: the catalog target had a 370 billion point using a 324.757 billion May 2026 anchor and an approximately 41.8 billion historical add-on. Recomputing the first-October reference class gives a slightly lower mechanical add-on of 39.75 billion, but the unusually refund-heavy 2026 filing season argues against cutting the forecast much."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast IRS October 2026 cumulative refunds","Tool call: Opened the IRS Oct. 18, 2024 Filing Season Statistics page for an additional first-October reference point."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: irs-total-refunds-october-2026\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-10-31\ntraceLineCount: 24\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: resolution clarity (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.uk-monthly-gdp-growth-april-2026.2026-06-04T10-32-04-01-00.6141e6531669d1b8","runId":"run.uk-monthly-gdp-growth-april-2026.2026-06-04T10-32-04-01-00.6141e6531669d1b8","predictionId":"uk-monthly-gdp-growth-april-2026","specId":"spec.uk-monthly-gdp-growth-april-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.19,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 6 source-context item(s), activity log absent.","evidence":["Monthly GDP is the fastest official read on UK growth and feeds directly into fiscal, labour-market, and monetary-policy predictions. This target resolves on 2026-06-12 under a first-print rule, with an expected ~1 week lag. The same series can also spawn next release, +3 months, threshold questions.","Tool call: ons.lookup({ release: \"GDP monthly estimate\", series: \"monthly_real_gdp_growth\", months: [\"2026-01\", \"2026-03\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Monthly GDP is the fastest official read on UK growth and feeds directly into fiscal, labour-market, and monetary-policy predictions. This target resolves on 2026-06-12 under a first-print rule, with an expected ~1 week lag. The same series can also spawn next release, +3 months, threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.8, distribution present, forecast step count 1.","evidence":["Tool call: ukIndicatorAgent.predict({ slugs: [\"uk-monthly-gdp-growth-april-2026\"], sources: [\"ONS GDP monthly estimate\", \"ONS retail sales\", \"ONS real-time indicators\"], runAt: \"2026-06-04T10:32:04+01:00\" })","Tool result: { point: -0.1, ci80: [-0.5, 0.3], context: ['March GDP +0.3%; February +0.4%; January 0.0%', 'April retail sales volumes -1.3%', '27% of trading businesses reported lower turnover'] }"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["March grew 0.3% after 0.4% in February, but the April look-ahead points to softer consumer demand: retail footfall was broadly unchanged, fuel prices jumped, and retail sales volumes later fell sharply in April. The agent therefore fades the Q1 strength."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: -0.1, ci80: [-0.5, 0.3], context: ['March GDP +0.3%; February +0.4%; January 0.0%', 'April retail sales volumes -1.3%', '27% of trading businesses reported lower turnover'] }","March grew 0.3% after 0.4% in February, but the April look-ahead points to softer consumer demand: retail footfall was broadly unchanged, fuel prices jumped, and retail sales volumes later fell sharply in April. The agent therefore fades the Q1 strength."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: uk-monthly-gdp-growth-april-2026\nrunLabel: Headline\nresolutionDate: 2026-06-12\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.uk-cpi-annual-rate-may-2026.2026-06-04T10-32-04-01-00.19aff3c2df28c994","runId":"run.uk-cpi-annual-rate-may-2026.2026-06-04T10-32-04-01-00.19aff3c2df28c994","predictionId":"uk-cpi-annual-rate-may-2026","specId":"spec.uk-cpi-annual-rate-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":["April CPI fell to 2.8% from 3.3%, largely because electricity, gas, food, recreation, and air fares eased. The agent expects a modest May rebound because the May 2025 base month was only +0.2%, while fuel and vehicle-tax base effects lean upward."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 6 source-context item(s), activity log absent.","evidence":["CPI is the key UK monetary-policy and cost-of-living indicator, especially while energy-price shocks and services inflation are in the news. This target resolves on 2026-06-17 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, +3 months, Bank Rate reaction questions.","Tool call: ons.lookup({ release: \"Consumer price inflation\", series: \"CPI 12-month rate\", months: [\"2026-01\", \"2026-04\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","CPI is the key UK monetary-policy and cost-of-living indicator, especially while energy-price shocks and services inflation are in the news. This target resolves on 2026-06-17 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, +3 months, Bank Rate reaction questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.6, distribution present, forecast step count 1.","evidence":["Forecast: point 2.9, 80% interval [2.6, 3.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["April CPI fell to 2.8% from 3.3%, largely because electricity, gas, food, recreation, and air fares eased. The agent expects a modest May rebound because the May 2025 base month was only +0.2%, while fuel and vehicle-tax base effects lean upward."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 2.9, ci80: [2.6, 3.2], context: ['April CPI 2.8% y/y; monthly CPI +0.7%', 'May 2025 monthly CPI +0.2%', 'motor fuels up; electricity and gas down in April'] }","Forecast: point 2.9, 80% interval [2.6, 3.2]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: uk-cpi-annual-rate-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-17\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.uk-unemployment-rate-feb-apr-2026.2026-06-04T10-32-04-01-00.e9e2e6b6909bc445","runId":"run.uk-unemployment-rate-feb-apr-2026.2026-06-04T10-32-04-01-00.e9e2e6b6909bc445","predictionId":"uk-unemployment-rate-feb-apr-2026","specId":"spec.uk-unemployment-rate-feb-apr-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.08,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 6 source-context item(s), activity log absent.","evidence":["The UK labour market is currently one of the clearest stress points: unemployment is up, payroll employment is falling, and wage growth remains central to Bank of England decisions. This target resolves on 2026-06-18 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, quarterly path, claimant threshold questions.","Tool call: ons.lookup({ release: \"UK labour market\", series: \"LFS unemployment rate 16+\", periods: [\"2025-10:2025-12\", \"2026-01:2026-03\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","The UK labour market is currently one of the clearest stress points: unemployment is up, payroll employment is falling, and wage growth remains central to Bank of England decisions. This target resolves on 2026-06-18 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, quarterly path, claimant threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.6, distribution present, forecast step count 1.","evidence":["Forecast: point 5.1, 80% interval [4.8, 5.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["The January-March unemployment rate was 5.0%, but the provisional April PAYE estimate fell by 100,000 on the month and vacancies reached their lowest level since early 2021. The agent nudges the rate up while respecting LFS sampling volatility."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The UK labour market is currently one of the clearest stress points: unemployment is up, payroll employment is falling, and wage growth remains central to Bank of England decisions. This target resolves on 2026-06-18 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, quarterly path, claimant threshold questions.","Tool result: { point: 5.1, ci80: [4.8, 5.4], context: ['Jan-Mar unemployment rate 5.0%', 'April claimant count 1.699m', 'vacancies fell to 705k, lowest since Feb-Apr 2021', 'LFS estimates remain volatile'] }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: uk-unemployment-rate-feb-apr-2026\nrunLabel: Headline\nresolutionDate: 2026-06-18\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.uk-unemployment-rate-apr-jun-2026.2026-06-04T10-32-04-01-00.cc0c0ea338d0fa08","runId":"run.uk-unemployment-rate-apr-jun-2026.2026-06-04T10-32-04-01-00.cc0c0ea338d0fa08","predictionId":"uk-unemployment-rate-apr-jun-2026","specId":"spec.uk-unemployment-rate-apr-jun-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 6 source-context item(s), activity log absent.","evidence":["The UK labour market is currently one of the clearest stress points: unemployment is up, payroll employment is falling, and wage growth remains central to Bank of England decisions. This target resolves on 2026-08-18 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, quarterly path, claimant threshold questions.","Tool call: ons.lookup({ release: \"UK labour market\", series: \"LFS unemployment rate 16+\", periods: [\"2025-10:2025-12\", \"2026-01:2026-03\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The UK labour market is currently one of the clearest stress points: unemployment is up, payroll employment is falling, and wage growth remains central to Bank of England decisions. This target resolves on 2026-08-18 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, quarterly path, claimant threshold questions.","Tool call: ons.lookup({ release: \"UK labour market\", series: \"LFS unemployment rate 16+\", periods: [\"2025-10:2025-12\", \"2026-01:2026-03\"] })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1, distribution present, forecast step count 1.","evidence":["The short-run path keeps unemployment slightly above the January-March print. Payroll and vacancy signals point to weaker labour demand, while the LFS remains noisy enough to keep a wide 80% interval around a 5.2% central estimate.","Forecast: point 5.2, 80% interval [4.7, 5.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The UK labour market is currently one of the clearest stress points: unemployment is up, payroll employment is falling, and wage growth remains central to Bank of England decisions. This target resolves on 2026-08-18 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, quarterly path, claimant threshold questions.","Tool result: { point: 5.2, ci80: [4.7, 5.7], context: ['Jan-Mar unemployment rate 5.0%', 'PAYE employees down on the month', 'vacancies at lowest since early 2021', 'LFS volatility remains high'] }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: uk-unemployment-rate-apr-jun-2026\nrunLabel: Headline\nresolutionDate: 2026-08-18\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.uk-unemployment-rate-apr-jun-2026.2026-06-27T13-39-06Z.uk-unemployment-rate-apr-jun-2026-thesis-analyst-fast-2026-06-27t13-39-06z.f0c3254c07e566e9","runId":"run.uk-unemployment-rate-apr-jun-2026.2026-06-27T13-39-06Z.uk-unemployment-rate-apr-jun-2026-thesis-analyst-fast-2026-06-27t13-39-06z.f0c3254c07e566e9","predictionId":"uk-unemployment-rate-apr-jun-2026","specId":"spec.uk-unemployment-rate-apr-jun-2026","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: Opened ONS Labour market overview, UK: May 2026 for the prior first-print LFS reference point.","Base-rate/reference-class anchor: the model prior is a persistence/recent-mean time-series prior rather than a separate fitted model, because only a short official first-print window is being used in this fast run. The last four available rolling three-month first prints are 5.2, 4.9, 5.0, and 4.9, averaging 5.0."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["The resolver is the first ONS print of the seasonally adjusted UK unemployment rate for people aged 16 years and over covering April to June 2026. ONS labour-market rates are reported to one decimal percent, and later revisions should not change the resolved value.","Tool call: Opened ONS Labour market overview, UK: June 2026 for the latest LFS and labour-market indicators."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast UK Apr-Jun 2026 unemployment first print","The resolver is the first ONS print of the seasonally adjusted UK unemployment rate for people aged 16 years and over covering April to June 2026. ONS labour-market rates are reported to one decimal percent, and later revisions should not change the resolved value."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.8, distribution present, forecast step count 1.","evidence":["Start with recent first-print mean (5.2+4.9+5.0+4.9)/4 = 5.0. Add 0.1 percentage point for weak vacancies, rising claimant count, and spring PAYE weakness, giving 5.1. Use an 80% interval of 4.7 to 5.5: roughly the 5.1 center plus or minus 0.4, widened for LFS volatility and possible seasonal-adjustment/reweighting noise.","Upside scenario: April-June layoffs and hiring freezes show through clearly in the LFS and unemployment prints 5.4 or 5.5. Downside scenario: April payroll weakness is revised away and survey volatility holds unemployment near 4.8 or 4.9. Outside-the-interval scenarios require either a sharp labour-market break above 5.5 or a strong participation/employment surprise below 4.7."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base-rate/reference-class anchor: the model prior is a persistence/recent-mean time-series prior rather than a separate fitted model, because only a short official first-print window is being used in this fast run. The last four available rolling three-month first prints are 5.2, 4.9, 5.0, and 4.9, averaging 5.0.","Level and momentum: unemployment is already near 5%, vacancies have moved from 721,000 to 711,000 to 705,000 to 707,000, and claimant count rose to 1.712 million. These indicators point to a small upward adjustment in the Apr-Jun LFS unemployment target, not a large break."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-consideration: LFS estimates remain volatile and ONS warns against over-reading short-term movements; May payroll was nearly flat after the April drop, so a continuation at 4.9 or a dip to 4.8 remains plausible if survey composition offsets payroll weakness."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast UK Apr-Jun 2026 unemployment first print","Tool call: Opened ONS Labour market overview, UK: May 2026 for the prior first-print LFS reference point."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: uk-unemployment-rate-apr-jun-2026\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-08-18\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.uk-unemployment-rate-jul-sep-2026.2026-06-04T10-32-04-01-00.aec88a55a12d8664","runId":"run.uk-unemployment-rate-jul-sep-2026.2026-06-04T10-32-04-01-00.aec88a55a12d8664","predictionId":"uk-unemployment-rate-jul-sep-2026","specId":"spec.uk-unemployment-rate-jul-sep-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.22,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 6 source-context item(s), activity log absent.","evidence":["The UK labour market is currently one of the clearest stress points: unemployment is up, payroll employment is falling, and wage growth remains central to Bank of England decisions. This target resolves on 2026-11-17 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, quarterly path, claimant threshold questions.","Tool call: ons.lookup({ release: \"UK labour market\", series: \"LFS unemployment rate 16+\", periods: [\"2025-10:2025-12\", \"2026-01:2026-03\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The UK labour market is currently one of the clearest stress points: unemployment is up, payroll employment is falling, and wage growth remains central to Bank of England decisions. This target resolves on 2026-11-17 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, quarterly path, claimant threshold questions.","Tool call: ons.lookup({ release: \"UK labour market\", series: \"LFS unemployment rate 16+\", periods: [\"2025-10:2025-12\", \"2026-01:2026-03\"] })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.3, distribution present, forecast step count 1.","evidence":["By July-September, the agent expects the weaker hiring signal to have mostly passed into the LFS rate, but not into a recessionary break. The center stays at 5.2%, with a wider interval because the horizon is beyond the next few ONS releases.","Forecast: point 5.2, 80% interval [4.6, 5.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["By July-September, the agent expects the weaker hiring signal to have mostly passed into the LFS rate, but not into a recessionary break. The center stays at 5.2%, with a wider interval because the horizon is beyond the next few ONS releases."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["By July-September, the agent expects the weaker hiring signal to have mostly passed into the LFS rate, but not into a recessionary break. The center stays at 5.2%, with a wider interval because the horizon is beyond the next few ONS releases."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The UK labour market is currently one of the clearest stress points: unemployment is up, payroll employment is falling, and wage growth remains central to Bank of England decisions. This target resolves on 2026-11-17 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, quarterly path, claimant threshold questions.","Tool result: { point: 5.2, ci80: [4.6, 5.9], context: ['unemployment near 5%', 'payroll softness should pass through slowly', 'vacancies lower', 'policy easing could stabilize hiring later in 2026'] }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: uk-unemployment-rate-jul-sep-2026\nrunLabel: Headline\nresolutionDate: 2026-11-17\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.uk-unemployment-rate-jul-sep-2026.2026-06-27T23-33-54Z.uk-unemployment-rate-jul-sep-2026-thesis-analyst-fast-2026-06-27t23-33-54z.db491a561e185cb5","runId":"run.uk-unemployment-rate-jul-sep-2026.2026-06-27T23-33-54Z.uk-unemployment-rate-jul-sep-2026-thesis-analyst-fast-2026-06-27t23-33-54z.db491a561e185cb5","predictionId":"uk-unemployment-rate-jul-sep-2026","specId":"spec.uk-unemployment-rate-jul-sep-2026","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base-rate/reference-class anchor: before inside-view adjustments, recent official MGSX history puts the rate around 5 percent. The last three quarterly values were 5.0, 5.2, and 5.0 percent, while recent monthly rolling-period prints were mostly 4.9 to 5.2 percent. This is an outside-view persistence prior centered near 5.0 percent rather than below the 2024 average.","Level, momentum, and one-off effects: the latest February to April print is lower than the prior quarter, but it is still up on the year. Payroll employment and vacancies point to weaker labour demand, while the LFS bulletin explicitly warns that short-term movements remain volatile and should be judged with other indicators."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The resolver is the ONS Labour Force Survey unemployment rate for people aged 16 and over, seasonally adjusted, for the July to September 2026 rolling three-month period. The target is the first one-decimal print in the November 2026 UK Labour Market or Employment in the UK release.","Tool call: Opened the ONS release page for UK Labour Market: November 2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast UK Jul-Sep 2026 first-print unemployment rate","The resolver is the ONS Labour Force Survey unemployment rate for people aged 16 and over, seasonally adjusted, for the July to September 2026 rolling three-month period. The target is the first one-decimal print in the November 2026 UK Labour Market or Employment in the UK release."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.3, distribution present, forecast step count 1.","evidence":["Tool call: Opened the ONS Employment in the UK: June 2026 bulletin for level, uncertainty, and sampling context.","Point calculation: start with a 5.0 percent outside-view anchor from recent quarterly MGSX values, blend in the latest 4.9 percent February-April level, then add about 0.15 percentage points for weak PAYE employment and vacancies over the five-month release horizon: 0.45*5.0 + 0.35*4.9 + 0.20*5.3 = 5.025, rounded and judgmentally tilted to 5.1 because labour-demand indicators are soft. For the 80% interval, the recent rolling MGSX sequence moved within 4.9 to 5.2 percent and the latest bulletin gives about ±0.3 percentage-point sampling variability, so I start near ±0.5 around the point and widen the upper side for lagged unemployment risk, giving 4.5 to 5.8."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, and one-off effects: the latest February to April print is lower than the prior quarter, but it is still up on the year. Payroll employment and vacancies point to weaker labour demand, while the LFS bulletin explicitly warns that short-term movements remain volatile and should be judged with other indicators.","Point calculation: start with a 5.0 percent outside-view anchor from recent quarterly MGSX values, blend in the latest 4.9 percent February-April level, then add about 0.15 percentage points for weak PAYE employment and vacancies over the five-month release horizon: 0.45*5.0 + 0.35*4.9 + 0.20*5.3 = 5.025, rounded and judgmentally tilted to 5.1 because labour-demand indicators are soft. For the 80% interval, the recent rolling MGSX sequence moved within 4.9 to 5.2 percent and the latest bulletin gives about ±0.3 percentage-point sampling variability, so I start near ±0.5 around the point and widen the upper side for lagged unemployment risk, giving 4.5 to 5.8."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool call: Opened the ONS Employment in the UK: June 2026 bulletin for level, uncertainty, and sampling context.","Level, momentum, and one-off effects: the latest February to April print is lower than the prior quarter, but it is still up on the year. Payroll employment and vacancies point to weaker labour demand, while the LFS bulletin explicitly warns that short-term movements remain volatile and should be judged with other indicators."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast UK Jul-Sep 2026 first-print unemployment rate","Tool result: Fetched latest LFS unemployment rate for February to April 2026 = 4.9%, up 0.3 percentage points on the year and down 0.3 percentage points on the latest quarter; PAYE employees fell 103,000 over the year and 31,000 on the quarter for February to April 2026; March to May 2026 vacancies fell 19,000 to 707,000."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: uk-unemployment-rate-jul-sep-2026\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-11-17\ntraceLineCount: 19\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.uk-unemployment-rate-oct-dec-2026.2026-06-04T10-32-04-01-00.c2f931fccc328efe","runId":"run.uk-unemployment-rate-oct-dec-2026.2026-06-04T10-32-04-01-00.c2f931fccc328efe","predictionId":"uk-unemployment-rate-oct-dec-2026","specId":"spec.uk-unemployment-rate-oct-dec-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.24,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: ukIndicatorAgent.predict({ slugs: [\"uk-unemployment-rate-oct-dec-2026\"], sources: [\"ONS UK labour market: May 2026\", \"ONS/HMRC PAYE RTI\", \"ONS vacancies\", \"IFS baseline unemployment path\", \"Nomis LFS release calendar\"], runAt: \"2026-06-04T10:32:04+01:00\" })","Tool result: { point: 5.1, ci80: [4.4, 5.9], context: ['Jan-Mar unemployment rate 5.0%', 'IFS baseline peaks near 5.1% in 2026', 'vacancies and payrolls weak but not collapsing', 'one-decimal ONS resolution'] }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 6 source-context item(s), activity log absent.","evidence":["The UK labour market is currently one of the clearest stress points: unemployment is up, payroll employment is falling, and wage growth remains central to Bank of England decisions. This target resolves on 2027-02-16 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, quarterly path, claimant threshold questions.","Tool call: ons.lookup({ release: \"UK labour market\", series: \"LFS unemployment rate 16+\", periods: [\"2025-10:2025-12\", \"2026-01:2026-03\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The UK labour market is currently one of the clearest stress points: unemployment is up, payroll employment is falling, and wage growth remains central to Bank of England decisions. This target resolves on 2027-02-16 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, quarterly path, claimant threshold questions.","Tool call: ons.lookup({ release: \"UK labour market\", series: \"LFS unemployment rate 16+\", periods: [\"2025-10:2025-12\", \"2026-01:2026-03\"] })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.5, distribution present, forecast step count 1.","evidence":["Forecast: point 5.1, 80% interval [4.4, 5.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Tool result: { point: 5.1, ci80: [4.4, 5.9], context: ['Jan-Mar unemployment rate 5.0%', 'IFS baseline peaks near 5.1% in 2026', 'vacancies and payrolls weak but not collapsing', 'one-decimal ONS resolution'] }","This mirrors the Manifold-style Q4 target: a one-decimal ONS LFS unemployment rate for October-December 2026. The agent keeps the central path near 5.1%, consistent with a labour market that weakens through mid-2026 but stabilizes rather than deteriorating sharply by year-end."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The UK labour market is currently one of the clearest stress points: unemployment is up, payroll employment is falling, and wage growth remains central to Bank of England decisions. This target resolves on 2027-02-16 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, quarterly path, claimant threshold questions.","Tool result: { point: 5.1, ci80: [4.4, 5.9], context: ['Jan-Mar unemployment rate 5.0%', 'IFS baseline peaks near 5.1% in 2026', 'vacancies and payrolls weak but not collapsing', 'one-decimal ONS resolution'] }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: uk-unemployment-rate-oct-dec-2026\nrunLabel: Headline\nresolutionDate: 2027-02-16\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.uk-unemployment-rate-oct-dec-2026.2026-06-16T10-20-43Z.thesis-analyst-live-2026-06-16.c2f931fccc328efe","runId":"run.uk-unemployment-rate-oct-dec-2026.2026-06-16T10-20-43Z.thesis-analyst-live-2026-06-16.c2f931fccc328efe","predictionId":"uk-unemployment-rate-oct-dec-2026","specId":"spec.uk-unemployment-rate-oct-dec-2026","runLabel":"Thesis analyst live run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base rate: among the last 24 fetched quarterly MGSX rates, mean 4.400, median 4.3, population std 0.464, sample std 0.474, 10th percentile 3.830, 90th percentile 5.000, range 3.7 to 5.3. Quarter-on-quarter changes had mean +0.039pp, std 0.295pp, 10th percentile -0.280pp, 90th percentile +0.300pp, range -0.4pp to +0.9pp."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing: the target is ONS Labour market statistics time series MGSX, Unemployment rate aged 16 and over, seasonally adjusted, percent, for October to December 2026, resolving on the first print and rounded to one decimal.","Tool call: Open ONS time series MGSX in LMS"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing: the target is ONS Labour market statistics time series MGSX, Unemployment rate aged 16 and over, seasonally adjusted, percent, for October to December 2026, resolving on the first print and rounded to one decimal.","Tool result: ONS page fetched this run reports release date 19 May 2026, next release 18 June 2026, Series ID MGSX, units %, and latest quarterly values 2025 Q3 5.0, 2025 Q4 5.2, 2026 Q1 5.0."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.5, distribution present, forecast step count 1.","evidence":["Three-quarter-ahead changes over the fetched window had mean +0.038pp, sample std 0.507pp, 10th percentile -0.700pp, and 90th percentile +0.600pp. Point estimate = 0.50*persistence 5.0 + 0.25*last-4-quarter mean 4.85 + 0.25*last-24 mean 4.40 + inside-view 0.50pp for the 2025 upward drift and three-quarter horizon = 5.113, rounded to 5.1. The 80% interval starts from realized 3-quarter movement around the point: 5.1-0.7=4.4 and 5.1+0.6=5.7, then widens the upper tail by 0.2pp for LFS volatility, yielding [4.4, 5.9].","Forecast: point 5.1, 80% interval [4.4, 5.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool result: Live specs URL check was attempted this run, but the environment returned no readable content and shell DNS failed with curl exit 6. Local catalog search found slug uk-unemployment-rate-oct-dec-2026 mapped to ons.labour.unemployment_rate.october_to_december_2026.first_print."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Three-quarter-ahead changes over the fetched window had mean +0.038pp, sample std 0.507pp, 10th percentile -0.700pp, and 90th percentile +0.600pp. Point estimate = 0.50*persistence 5.0 + 0.25*last-4-quarter mean 4.85 + 0.25*last-24 mean 4.40 + inside-view 0.50pp for the 2025 upward drift and three-quarter horizon = 5.113, rounded to 5.1. The 80% interval starts from realized 3-quarter movement around the point: 5.1-0.7=4.4 and 5.1+0.6=5.7, then widens the upper tail by 0.2pp for LFS volatility, yielding [4.4, 5.9].","Forecast: point 5.1, 80% interval [4.4, 5.9]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: uk-unemployment-rate-oct-dec-2026\nrunLabel: Thesis analyst live run\nresolutionDate: 2027-02-16\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.uk-paye-payrolled-employees-may-2026.2026-06-04T10-32-04-01-00.92cfe71c26bcc65c","runId":"run.uk-paye-payrolled-employees-may-2026.2026-06-04T10-32-04-01-00.92cfe71c26bcc65c","predictionId":"uk-paye-payrolled-employees-may-2026","specId":"spec.uk-paye-payrolled-employees-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.08,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 6 source-context item(s), activity log absent.","evidence":["PAYE payrolls are a timely administrative labour-market signal, often cleaner for near-term movement than the survey unemployment rate. This target resolves on 2026-06-18 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, +3 months, labour-market threshold questions.","Tool call: ons.hmrc.lookup({ dataset: \"PAYE RTI\", measure: \"payrolled_employees_early_estimate\", months: [\"2026-01\", \"2026-04\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","PAYE payrolls are a timely administrative labour-market signal, often cleaner for near-term movement than the survey unemployment rate. This target resolves on 2026-06-18 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, +3 months, labour-market threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.32, distribution present, forecast step count 1.","evidence":["Forecast: point 30.15, 80% interval [29.98, 30.3]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["April's early estimate dropped to 30.2 million, down 100,000 on the month. Early tax-year estimates often revise upward, but the agent still expects a lower May first print given weakening labour-demand indicators."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 30.15, ci80: [29.98, 30.30], context: ['April early estimate 30.2m', 'April down 100k on month', 'early tax-year estimates often revise upward'] }","Forecast: point 30.15, 80% interval [29.98, 30.3]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: uk-paye-payrolled-employees-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-18\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.uk-retail-sales-volume-mom-may-2026.2026-06-04T10-32-04-01-00.9db79e1bc69fa65a","runId":"run.uk-retail-sales-volume-mom-may-2026.2026-06-04T10-32-04-01-00.9db79e1bc69fa65a","predictionId":"uk-retail-sales-volume-mom-may-2026","specId":"spec.uk-retail-sales-volume-mom-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.19,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 6 source-context item(s), activity log absent.","evidence":["Retail sales are a fast consumer-demand read and one of the most visible components behind short-run GDP surprises. This target resolves on 2026-06-19 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, +3 months, GDP contribution questions.","Tool call: ons.lookup({ release: \"Retail sales, Great Britain\", series: \"volume_mom\", months: [\"2026-02\", \"2026-04\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Retail sales are a fast consumer-demand read and one of the most visible components behind short-run GDP surprises. This target resolves on 2026-06-19 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, +3 months, GDP contribution questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.2, distribution present, forecast step count 1.","evidence":["Retail sales are a fast consumer-demand read and one of the most visible components behind short-run GDP surprises. This target resolves on 2026-06-19 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, +3 months, GDP contribution questions.","Tool call: ons.lookup({ release: \"Retail sales, Great Britain\", series: \"volume_mom\", months: [\"2026-02\", \"2026-04\"] })"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Retail sales are a fast consumer-demand read and one of the most visible components behind short-run GDP surprises. This target resolves on 2026-06-19 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, +3 months, GDP contribution questions."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 0.5, ci80: [-0.6, 1.6], context: ['April volumes -1.3%', 'automotive fuel volumes -10.2%', 'retail footfall flat month-over-month'] }","April's 1.3% fall looks partly fuel-driven after March stock-up behaviour, with automotive fuel volumes down 10.2%. The agent expects partial rebound in May as that distortion fades, while weak footfall and non-fuel softness keep the interval wide."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: uk-retail-sales-volume-mom-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-19\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.uk-public-sector-net-borrowing-may-2026.2026-06-04T10-32-04-01-00.5b5496056b563d02","runId":"run.uk-public-sector-net-borrowing-may-2026.2026-06-04T10-32-04-01-00.5b5496056b563d02","predictionId":"uk-public-sector-net-borrowing-may-2026","specId":"spec.uk-public-sector-net-borrowing-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.24,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and explicit outside-view language.","evidence":["The OBR monthly profile gives a strong May baseline near £17.7 billion and May 2025 was £18.2 billion. April 2026 was £3.4 billion above the OBR profile, but early-year spending estimates can unwind, so the agent shades modestly above the baseline rather than carrying the full April overshoot forward."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 6 source-context item(s), activity log absent.","evidence":["Borrowing is central to the UK's fiscal room, gilt supply, and the credibility of policy-cost forecasts. This target resolves on 2026-06-19 under a first-print rule, with an expected ~3 weeks lag. The same series can also spawn next release, +3 months, debt-to-GDP impact questions.","Tool call: ons.lookup({ release: \"Public sector finances\", series: \"J5II\", transform: \"-value / 1000\", months: [\"2026-04\", \"2025-05\"], obr_profile: \"March 2026 EFO monthly profiles\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Borrowing is central to the UK's fiscal room, gilt supply, and the credibility of policy-cost forecasts. This target resolves on 2026-06-19 under a first-print rule, with an expected ~3 weeks lag. The same series can also spawn next release, +3 months, debt-to-GDP impact questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 11, distribution present, forecast step count 1.","evidence":["Forecast: point 18.5, 80% interval [13, 24]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["The OBR monthly profile gives a strong May baseline near £17.7 billion and May 2025 was £18.2 billion. April 2026 was £3.4 billion above the OBR profile, but early-year spending estimates can unwind, so the agent shades modestly above the baseline rather than carrying the full April overshoot forward."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Borrowing is central to the UK's fiscal room, gilt supply, and the credibility of policy-cost forecasts. This target resolves on 2026-06-19 under a first-print rule, with an expected ~3 weeks lag. The same series can also spawn next release, +3 months, debt-to-GDP impact questions.","Tool result: { point: 18.5, ci80: [13.0, 24.0], context: ['April borrowing £24.343bn', 'May 2025 borrowing £18.203bn using -J5II / 1000', 'OBR March 2026 monthly profile for May 2026 £17.665bn', 'May release due 2026-06-19'] }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: uk-public-sector-net-borrowing-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-19\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.uk-bank-rate-june-2026-mpc.2026-06-04T10-32-04-01-00.b33aff3526b668a2","runId":"run.uk-bank-rate-june-2026-mpc.2026-06-04T10-32-04-01-00.b33aff3526b668a2","predictionId":"uk-bank-rate-june-2026-mpc","specId":"spec.uk-bank-rate-june-2026-mpc","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.19,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 6 source-context item(s), activity log absent.","evidence":["Bank Rate is the UK policy setting that ties together inflation, labour-market slack, mortgage costs, and fiscal debt-interest forecasts. This target resolves on 2026-06-18 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next decision, +3 months, inflation reaction questions.","Tool call: boe.lookup({ release: \"MPC minutes\", decisions: [\"2026-02\", \"2026-03\", \"2026-04\"], next_decision: \"2026-06-18\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Bank Rate is the UK policy setting that ties together inflation, labour-market slack, mortgage costs, and fiscal debt-interest forecasts. This target resolves on 2026-06-18 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next decision, +3 months, inflation reaction questions.","Tool call: boe.lookup({ release: \"MPC minutes\", decisions: [\"2026-02\", \"2026-03\", \"2026-04\"], next_decision: \"2026-06-18\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.25, distribution present, forecast step count 1.","evidence":["Tool result: { point: 3.75, ci80: [3.75, 4.00], context: ['April MPC voted 8-1 to hold at 3.75%', 'one member voted to raise to 4.00%', 'energy-price uncertainty raises inflation risk', 'labour market continues to loosen'] }","The April MPC voted 8-1 to hold Bank Rate at 3.75%, with one member voting to raise. Inflation and energy risks argue against cuts, while labour-market loosening argues against a broad hiking majority, so the agent centers on another hold."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool result: { point: 3.75, ci80: [3.75, 4.00], context: ['April MPC voted 8-1 to hold at 3.75%', 'one member voted to raise to 4.00%', 'energy-price uncertainty raises inflation risk', 'labour market continues to loosen'] }","The April MPC voted 8-1 to hold Bank Rate at 3.75%, with one member voting to raise. Inflation and energy risks argue against cuts, while labour-market loosening argues against a broad hiking majority, so the agent centers on another hold."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Bank Rate is the UK policy setting that ties together inflation, labour-market slack, mortgage costs, and fiscal debt-interest forecasts. This target resolves on 2026-06-18 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next decision, +3 months, inflation reaction questions.","Tool result: { point: 3.75, ci80: [3.75, 4.00], context: ['April MPC voted 8-1 to hold at 3.75%', 'one member voted to raise to 4.00%', 'energy-price uncertainty raises inflation risk', 'labour market continues to loosen'] }"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: uk-bank-rate-june-2026-mpc\nrunLabel: Headline\nresolutionDate: 2026-06-18\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-unemployment-rate-may-2026.2026-06-04T11-36-25-01-00.ff3a23dc44e4f89b","runId":"run.canada-unemployment-rate-may-2026.2026-06-04T11-36-25-01-00.ff3a23dc44e4f89b","predictionId":"canada-unemployment-rate-may-2026","specId":"spec.canada-unemployment-rate-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 7 source-context item(s), activity log absent.","evidence":["The unemployment rate is the fastest official read on Canadian labour-market slack and feeds directly into household-income, poverty, and Bank of Canada predictions. This target resolves on 2026-06-05 under a first-print rule, with an expected ~1 day lag. The same series can also spawn next release, +3 months, rate-decision reaction questions.","Tool call: statcan.lookup({ release: \"Labour Force Survey\", series: \"unemployment_rate\", months: [\"2026-01\", \"2026-04\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","The unemployment rate is the fastest official read on Canadian labour-market slack and feeds directly into household-income, poverty, and Bank of Canada predictions. This target resolves on 2026-06-05 under a first-print rule, with an expected ~1 day lag. The same series can also spawn next release, +3 months, rate-decision reaction questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.6, distribution present, forecast step count 1.","evidence":["Forecast: point 7, 80% interval [6.7, 7.3]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The April rate rose to 6.9% while employment was little changed for a second month after a weak February. The agent centers May at 7.0% because participation and job-search behavior can keep unemployment elevated even if employment does not fall sharply."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 7.0, ci80: [6.7, 7.3], context: ['April unemployment 6.9%', 'April employment -18k', 'first four months of 2026 net employment -112k', 'March job vacancies held at 503k'] }","Forecast: point 7, 80% interval [6.7, 7.3]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-unemployment-rate-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-05\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-employment-change-may-2026.2026-06-04T11-36-25-01-00.71730184ad913dc9","runId":"run.canada-employment-change-may-2026.2026-06-04T11-36-25-01-00.71730184ad913dc9","predictionId":"canada-employment-change-may-2026","specId":"spec.canada-employment-change-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.08,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":["Employment change is a high-cadence calibration target for labour income, payroll tax bases, and poverty forecasts. This target resolves on 2026-06-05 under a first-print rule, with an expected ~1 day lag. The same series can also spawn next release, +3 months, unemployment threshold questions."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 7 source-context item(s), activity log absent.","evidence":["Employment change is a high-cadence calibration target for labour income, payroll tax bases, and poverty forecasts. This target resolves on 2026-06-05 under a first-print rule, with an expected ~1 day lag. The same series can also spawn next release, +3 months, unemployment threshold questions.","Tool call: statcan.lookup({ release: \"Labour Force Survey\", series: \"employment_change_thousands\", months: [\"2026-01\", \"2026-04\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Employment change is a high-cadence calibration target for labour income, payroll tax bases, and poverty forecasts. This target resolves on 2026-06-05 under a first-print rule, with an expected ~1 day lag. The same series can also spawn next release, +3 months, unemployment threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 110, distribution present, forecast step count 1.","evidence":["The first four months of 2026 show soft but noisy employment, with two small prints around one large February decline. The agent expects another slightly negative May first print while keeping a wide interval around zero.","Forecast: point -10, 80% interval [-60, 50]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["The first four months of 2026 show soft but noisy employment, with two small prints around one large February decline. The agent expects another slightly negative May first print while keeping a wide interval around zero."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Employment change is a high-cadence calibration target for labour income, payroll tax bases, and poverty forecasts. This target resolves on 2026-06-05 under a first-print rule, with an expected ~1 day lag. The same series can also spawn next release, +3 months, unemployment threshold questions.","Tool result: { point: -10, ci80: [-60, 50], context: ['January-April net employment -112k', 'March +14k after February -84k', 'April -18k and full-time -47k', 'monthly LFS first prints are noisy'] }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-employment-change-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-05\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-cpi-annual-rate-may-2026.2026-06-04T11-36-25-01-00.cfa5aea222e44ee8","runId":"run.canada-cpi-annual-rate-may-2026.2026-06-04T11-36-25-01-00.cfa5aea222e44ee8","predictionId":"canada-cpi-annual-rate-may-2026","specId":"spec.canada-cpi-annual-rate-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.32,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":["Tool result: { point: 2.7, ci80: [2.3, 3.1], context: ['April CPI 2.8% y/y', 'March 2.4%; February 1.8%', 'May CPI uses updated 2025 basket weights', 'gasoline base effects remain important'] }","April's acceleration to 2.8% was driven by energy and carbon-levy base effects. The agent expects those pressures to remain visible but not intensify materially in May, centering slightly below April with basket-update uncertainty in the interval."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 7 source-context item(s), activity log absent.","evidence":["Canadian CPI is the key official inflation target for rate decisions, real-income forecasts, and benefit indexation checks. This target resolves on 2026-06-22 under a first-print rule, with an expected ~3 weeks lag. The same series can also spawn next release, +3 months, BoC reaction questions.","Tool call: statcan.lookup({ release: \"Consumer Price Index\", series: \"all_items_12_month_change\", months: [\"2026-01\", \"2026-04\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Canadian CPI is the key official inflation target for rate decisions, real-income forecasts, and benefit indexation checks. This target resolves on 2026-06-22 under a first-print rule, with an expected ~3 weeks lag. The same series can also spawn next release, +3 months, BoC reaction questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.8, distribution present, forecast step count 1.","evidence":["April's acceleration to 2.8% was driven by energy and carbon-levy base effects. The agent expects those pressures to remain visible but not intensify materially in May, centering slightly below April with basket-update uncertainty in the interval.","Forecast: point 2.7, 80% interval [2.3, 3.1]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["April's acceleration to 2.8% was driven by energy and carbon-levy base effects. The agent expects those pressures to remain visible but not intensify materially in May, centering slightly below April with basket-update uncertainty in the interval."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["April's acceleration to 2.8% was driven by energy and carbon-levy base effects. The agent expects those pressures to remain visible but not intensify materially in May, centering slightly below April with basket-update uncertainty in the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Canadian CPI is the key official inflation target for rate decisions, real-income forecasts, and benefit indexation checks. This target resolves on 2026-06-22 under a first-print rule, with an expected ~3 weeks lag. The same series can also spawn next release, +3 months, BoC reaction questions.","Tool result: { point: 2.7, ci80: [2.3, 3.1], context: ['April CPI 2.8% y/y', 'March 2.4%; February 1.8%', 'May CPI uses updated 2025 basket weights', 'gasoline base effects remain important'] }"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-cpi-annual-rate-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-22\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-cpi-annual-rate-may-2026.2026-06-20T09-02-00-04-00.canada-cpi-annual-rate-may-2026-brier-shadow-no-packs.f4fcfc22e29af399","runId":"run.canada-cpi-annual-rate-may-2026.2026-06-20T09-02-00-04-00.canada-cpi-annual-rate-may-2026-brier-shadow-no-packs.f4fcfc22e29af399","predictionId":"canada-cpi-annual-rate-may-2026","specId":"spec.canada-cpi-annual-rate-may-2026","runLabel":"Brier-1 - no packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 0 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The control run treats the target as a persistence forecast around recent headline CPI with a symmetric rounded-release interval."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.8, distribution present, forecast step count 1.","evidence":["The control run treats the target as a persistence forecast around recent headline CPI with a symmetric rounded-release interval.","Forecast: point 2.6, 80% interval [2.2, 3]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The control run treats the target as a persistence forecast around recent headline CPI with a symmetric rounded-release interval.","Forecast: point 2.6, 80% interval [2.2, 3]"]}],"flags":["weak_counterarguments","no_typed_tool_call"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-cpi-annual-rate-may-2026\nrunLabel: Brier-1 - no packs\nresolutionDate: 2026-06-22\ntraceLineCount: 3\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments, no_typed_tool_call."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-cpi-annual-rate-may-2026.2026-06-20T09-02-00-04-00.canada-cpi-annual-rate-may-2026-brier-shadow-with-packs.5f5b5f7e997df924","runId":"run.canada-cpi-annual-rate-may-2026.2026-06-20T09-02-00-04-00.canada-cpi-annual-rate-may-2026-brier-shadow-with-packs.5f5b5f7e997df924","predictionId":"canada-cpi-annual-rate-may-2026","specId":"spec.canada-cpi-annual-rate-may-2026","runLabel":"Brier-1 - packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.46,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":["Tool call: brier.pack.apply({ target: \"statcan.cpi.all_items_annual_rate.canada.may_2026.first_print\", packs: [\"base-rate-first@0.1.0\", \"energy-price-nowcast@0.1.0\", \"cpi-component-decomposition@0.1.0\", \"release-vintage-calibration@0.1.0\"] })","Tool result: { admitted: 4, mode: \"with_packs\", required_checks: [\"headline_base_rate\",\"energy_nowcast\",\"component_recombine\",\"release_rounding\"] }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["Tool call: brier.pack.apply({ target: \"statcan.cpi.all_items_annual_rate.canada.may_2026.first_print\", packs: [\"base-rate-first@0.1.0\", \"energy-price-nowcast@0.1.0\", \"cpi-component-decomposition@0.1.0\", \"release-vintage-calibration@0.1.0\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Tool call: brier.pack.apply({ target: \"statcan.cpi.all_items_annual_rate.canada.may_2026.first_print\", packs: [\"base-rate-first@0.1.0\", \"energy-price-nowcast@0.1.0\", \"cpi-component-decomposition@0.1.0\", \"release-vintage-calibration@0.1.0\"] })","Tool result: { admitted: 4, mode: \"with_packs\", required_checks: [\"headline_base_rate\",\"energy_nowcast\",\"component_recombine\",\"release_rounding\"] }"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.2, distribution present, forecast step count 1.","evidence":["The pack run lifts the center slightly for remaining energy pressure and widens both tails because May is the first print after the basket update.","Forecast: point 2.7, 80% interval [2.1, 3.3]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The pack run lifts the center slightly for remaining energy pressure and widens both tails because May is the first print after the basket update."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 2.7, 80% interval [2.1, 3.3]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-cpi-annual-rate-may-2026\nrunLabel: Brier-1 - packs\nresolutionDate: 2026-06-22\ntraceLineCount: 5\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-monthly-gdp-growth-april-2026.2026-06-04T11-36-25-01-00.89d3681a7f28e8df","runId":"run.canada-monthly-gdp-growth-april-2026.2026-06-04T11-36-25-01-00.89d3681a7f28e8df","predictionId":"canada-monthly-gdp-growth-april-2026","specId":"spec.canada-monthly-gdp-growth-april-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.22,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 7 source-context item(s), activity log absent.","evidence":["Monthly GDP is the quickest official output measure for Canada and helps anchor fiscal revenue, labour demand, and central-bank predictions. This target resolves on 2026-06-30 under a first-print rule, with an expected ~4 weeks lag. The same series can also spawn next release, +3 months, recession threshold questions.","Tool call: statcan.lookup({ release: \"GDP by industry\", series: \"monthly_real_gdp_growth\", months: [\"2026-01\", \"2026-03\"], advance_month: \"2026-04\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Monthly GDP is the quickest official output measure for Canada and helps anchor fiscal revenue, labour demand, and central-bank predictions. This target resolves on 2026-06-30 under a first-print rule, with an expected ~4 weeks lag. The same series can also spawn next release, +3 months, recession threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.6, distribution present, forecast step count 1.","evidence":["Forecast: point 0.4, 80% interval [0.1, 0.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Statistics Canada's advance estimate points to 0.4% April growth. The agent uses that as the modal first official print but keeps room for revision because March's goods-sector contraction and agriculture weakness could shift the final industry mix."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Statistics Canada's advance estimate points to 0.4% April growth. The agent uses that as the modal first official print but keeps room for revision because March's goods-sector contraction and agriculture weakness could shift the final industry mix."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 0.4, ci80: [0.1, 0.7], context: ['March GDP -0.1%', 'April advance estimate +0.4%', 'growth indicated in mining, manufacturing, transportation and warehousing'] }","Statistics Canada's advance estimate points to 0.4% April growth. The agent uses that as the modal first official print but keeps room for revision because March's goods-sector contraction and agriculture weakness could shift the final industry mix."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-monthly-gdp-growth-april-2026\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-monthly-gdp-growth-april-2026.2026-06-17T02-05-41Z.canada-monthly-gdp-growth-april-2026-thesis-analyst-fast-2026-06-17t02-05-41z.89d3681a7f28e8df","runId":"run.canada-monthly-gdp-growth-april-2026.2026-06-17T02-05-41Z.canada-monthly-gdp-growth-april-2026-thesis-analyst-fast-2026-06-17t02-05-41z.89d3681a7f28e8df","predictionId":"canada-monthly-gdp-growth-april-2026","specId":"spec.canada-monthly-gdp-growth-april-2026","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: Read prior Statistics Canada GDP by industry releases for recent base rates and advance-estimate accuracy.","Base-rate/reference class: recent first prints around this series have been small, with December +0.2%, January +0.1%, February +0.2%, and March -0.1%; however, the April advance estimate is materially stronger at +0.4%."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["Tool call: Read the Statistics Canada March 2026 GDP by industry Daily release for latest official monthly growth and April advance estimate.","Tool result: April manufacturing sales rose +4.2% to $77.1 billion and constant-dollar manufacturing sales rose +1.8%; merchandise exports rose +1.6% to $75.2 billion and real exports rose +3.0%."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Resolver is Statistics Canada's first-print seasonally adjusted monthly percent change for real GDP by industry at basic prices for April 2026, not a later revised table value.","Tool call: Checked Statistics Canada major economic release calendar for the April 2026 GDP by industry release date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.6, distribution present, forecast step count 1.","evidence":["Counter-consideration: the advance estimate can miss by a tenth or more, and April's petroleum-price shock boosts nominal indicators more than real GDP; missing retail and some service indicators could pull the final first print below the advance.","Use the StatCan April advance estimate (+0.4) as anchor; prior advance misses from the latest two comparable months were roughly 0.0 and -0.1 percentage point. Strong constant-dollar manufacturing (+1.8) and real exports (+3.0) support staying at +0.4. Set an 80% interval of 0.1 to 0.7, allowing about +/-0.3 around the advance for source revisions and service-sector offset risk."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base-rate/reference class: recent first prints around this series have been small, with December +0.2%, January +0.1%, February +0.2%, and March -0.1%; however, the April advance estimate is materially stronger at +0.4%.","Use the StatCan April advance estimate (+0.4) as anchor; prior advance misses from the latest two comparable months were roughly 0.0 and -0.1 percentage point. Strong constant-dollar manufacturing (+1.8) and real exports (+3.0) support staying at +0.4. Set an 80% interval of 0.1 to 0.7, allowing about +/-0.3 around the advance for source revisions and service-sector offset risk."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: Canada real GDP by industry monthly growth for April 2026","Use the StatCan April advance estimate (+0.4) as anchor; prior advance misses from the latest two comparable months were roughly 0.0 and -0.1 percentage point. Strong constant-dollar manufacturing (+1.8) and real exports (+3.0) support staying at +0.4. Set an 80% interval of 0.1 to 0.7, allowing about +/-0.3 around the advance for source revisions and service-sector offset risk."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-monthly-gdp-growth-april-2026\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-06-30\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-monthly-gdp-growth-april-2026.2026-06-27T12-54-53Z.canada-monthly-gdp-growth-april-2026-thesis-analyst-fast-2026-06-27t12-54-53z.89d3681a7f28e8df","runId":"run.canada-monthly-gdp-growth-april-2026.2026-06-27T12-54-53Z.canada-monthly-gdp-growth-april-2026-thesis-analyst-fast-2026-06-27t12-54-53z.89d3681a7f28e8df","predictionId":"canada-monthly-gdp-growth-april-2026","specId":"spec.canada-monthly-gdp-growth-april-2026","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: Fetched prior Statistics Canada The Daily releases for January, February, and December context.","Base rate/reference class: recent official first prints around this series are small positives, with December +0.2, January -0.0, February +0.2, and March -0.1. The simple recent first-print average is about +0.1, but the agency's own April advance estimate is a strong near-term signal and usually deserves heavy weight."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 7 source-context item(s), activity log present.","evidence":["Base rate/reference class: recent official first prints around this series are small positives, with December +0.2, January -0.0, February +0.2, and March -0.1. The simple recent first-print average is about +0.1, but the agency's own April advance estimate is a strong near-term signal and usually deserves heavy weight.","Inside-view decomposition: level effects are modest because Q1 GDP by industry was only +0.1 for the quarter. Momentum is mixed after March weakness, but the named April advance components point to rebounds in mining, quarrying, oil and gas extraction, manufacturing, and transportation and warehousing. One-off factors include March maintenance/weather disruptions in energy and auto-related volatility that can reverse. Policy/trade mechanisms remain a drag risk through tariffs and manufacturing/export uncertainty."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Resolver is the first Statistics Canada print for seasonally adjusted real GDP by industry, all industries, month-to-month percent change for April 2026. The target is the June 30, 2026 Daily/table release, not later revised history.","Tool call: Checked Statistics Canada 2026-2027 major economic release dates PDF for Gross domestic product by industry."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.6, distribution present, forecast step count 1.","evidence":["Inside-view decomposition: level effects are modest because Q1 GDP by industry was only +0.1 for the quarter. Momentum is mixed after March weakness, but the named April advance components point to rebounds in mining, quarrying, oil and gas extraction, manufacturing, and transportation and warehousing. One-off factors include March maintenance/weather disruptions in energy and auto-related volatility that can reverse. Policy/trade mechanisms remain a drag risk through tariffs and manufacturing/export uncertainty.","I anchor at the recent first-print base rate near +0.1, put most weight on StatCan's April advance estimate of +0.4, and choose 0.4 as the rounded point. No separate ARIMA or ETS model was fit; the model prior is a recent-first-print persistence average updated toward the official advance estimate. The 80% interval is for the one-decimal rounded first print. Recent advance-to-first-print misses in visible releases were about 0.0 to 0.1 percentage point, but sector volatility and tariff/energy uncertainty justify a wider 80% interval of 0.1 to 0.7. Upside outside the interval would require a broad mining/manufacturing surge above +0.7; downside outside the interval would require advance-estimate reversal to 0.0 or lower."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Inside-view decomposition: level effects are modest because Q1 GDP by industry was only +0.1 for the quarter. Momentum is mixed after March weakness, but the named April advance components point to rebounds in mining, quarrying, oil and gas extraction, manufacturing, and transportation and warehousing. One-off factors include March maintenance/weather disruptions in energy and auto-related volatility that can reverse. Policy/trade mechanisms remain a drag risk through tariffs and manufacturing/export uncertainty."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: recent official first prints around this series are small positives, with December +0.2, January -0.0, February +0.2, and March -0.1. The simple recent first-print average is about +0.1, but the agency's own April advance estimate is a strong near-term signal and usually deserves heavy weight.","Inside-view decomposition: level effects are modest because Q1 GDP by industry was only +0.1 for the quarter. Momentum is mixed after March weakness, but the named April advance components point to rebounds in mining, quarrying, oil and gas extraction, manufacturing, and transportation and warehousing. One-off factors include March maintenance/weather disruptions in energy and auto-related volatility that can reverse. Policy/trade mechanisms remain a drag risk through tariffs and manufacturing/export uncertainty."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for Canada April 2026 real GDP by industry monthly growth","Inside-view decomposition: level effects are modest because Q1 GDP by industry was only +0.1 for the quarter. Momentum is mixed after March weakness, but the named April advance components point to rebounds in mining, quarrying, oil and gas extraction, manufacturing, and transportation and warehousing. One-off factors include March maintenance/weather disruptions in energy and auto-related volatility that can reverse. Policy/trade mechanisms remain a drag risk through tariffs and manufacturing/export uncertainty."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-monthly-gdp-growth-april-2026\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-06-30\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-overnight-rate-june-2026-boc.2026-06-04T11-36-25-01-00.98d3522509943078","runId":"run.canada-overnight-rate-june-2026-boc.2026-06-04T11-36-25-01-00.98d3522509943078","predictionId":"canada-overnight-rate-june-2026-boc","specId":"spec.canada-overnight-rate-june-2026-boc","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.95,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 7 source-context item(s), activity log absent.","evidence":["The overnight-rate target is Canada's central monetary-policy setting and connects inflation, labour slack, debt-service costs, and exchange-rate forecasts. This target resolves on 2026-06-10 under a first-print rule, with an expected ~1 week lag. The same series can also spawn next decision, +3 months, inflation reaction questions.","Tool call: bank_of_canada.lookup({ series: \"target_overnight_rate\", decisions: [\"2026-01-28\", \"2026-03-18\", \"2026-04-29\"], next_decision: \"2026-06-10\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The overnight-rate target is Canada's central monetary-policy setting and connects inflation, labour slack, debt-service costs, and exchange-rate forecasts. This target resolves on 2026-06-10 under a first-print rule, with an expected ~1 week lag. The same series can also spawn next decision, +3 months, inflation reaction questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.25, distribution present, forecast step count 1.","evidence":["The Bank has held at 2.25% for three decisions. Inflation has moved back above 2% while labour slack has risen, so the agent puts most mass on another hold with a smaller cut tail rather than a hike.","Forecast: point 2.25, 80% interval [2, 2.25]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The overnight-rate target is Canada's central monetary-policy setting and connects inflation, labour slack, debt-service costs, and exchange-rate forecasts. This target resolves on 2026-06-10 under a first-print rule, with an expected ~1 week lag. The same series can also spawn next decision, +3 months, inflation reaction questions.","Tool result: { point: 2.25, ci80: [2.00, 2.25], context: ['overnight target held at 2.25% on Jan 28, Mar 18, and Apr 29', 'April CPI 2.8%', 'April unemployment 6.9%', 'June 10 fixed announcement date'] }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-overnight-rate-june-2026-boc\nrunLabel: Headline\nresolutionDate: 2026-06-10\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-unemployment-rate-may-2026.2026-06-04T11-36-25-01-00.d12f2ff7a6b7ce3c","runId":"run.australia-unemployment-rate-may-2026.2026-06-04T11-36-25-01-00.d12f2ff7a6b7ce3c","predictionId":"australia-unemployment-rate-may-2026","specId":"spec.australia-unemployment-rate-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.46,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 7 source-context item(s), activity log absent.","evidence":["The unemployment rate is a central near-term input for Australian monetary policy, household-income forecasts, and benefit-pressure predictions. This target resolves on 2026-06-25 under a first-print rule, with an expected ~3 weeks lag. The same series can also spawn next release, +3 months, RBA reaction questions."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","The unemployment rate is a central near-term input for Australian monetary policy, household-income forecasts, and benefit-pressure predictions. This target resolves on 2026-06-25 under a first-print rule, with an expected ~3 weeks lag. The same series can also spawn next release, +3 months, RBA reaction questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.6, distribution present, forecast step count 1.","evidence":["April's seasonally adjusted rate rose to 4.5% while the trend rate remained 4.3%. The agent centers on 4.5% because a reversal is possible, but survey transition risk and the April rise argue against aggressively fading it.","Forecast: point 4.5, 80% interval [4.2, 4.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The unemployment rate is a central near-term input for Australian monetary policy, household-income forecasts, and benefit-pressure predictions. This target resolves on 2026-06-25 under a first-print rule, with an expected ~3 weeks lag. The same series can also spawn next release, +3 months, RBA reaction questions.","April's seasonally adjusted rate rose to 4.5% while the trend rate remained 4.3%. The agent centers on 4.5% because a reversal is possible, but survey transition risk and the April rise argue against aggressively fading it."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["April's seasonally adjusted rate rose to 4.5% while the trend rate remained 4.3%. The agent centers on 4.5% because a reversal is possible, but survey transition risk and the April rise argue against aggressively fading it."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The unemployment rate is a central near-term input for Australian monetary policy, household-income forecasts, and benefit-pressure predictions. This target resolves on 2026-06-25 under a first-print rule, with an expected ~3 weeks lag. The same series can also spawn next release, +3 months, RBA reaction questions.","Tool result: { point: 4.5, ci80: [4.2, 4.8], context: ['April unemployment 4.5%; trend 4.3%', 'April employment -18.6k', 'May release delayed to June 25 for quality assurance during survey modernisation'] }"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-unemployment-rate-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-25\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-unemployment-rate-may-2026.2026-06-20T09-10-00-04-00.australia-unemployment-rate-may-2026-brier-shadow-no-packs.7119b7a068b2153a","runId":"run.australia-unemployment-rate-may-2026.2026-06-20T09-10-00-04-00.australia-unemployment-rate-may-2026-brier-shadow-no-packs.7119b7a068b2153a","predictionId":"australia-unemployment-rate-may-2026","specId":"spec.australia-unemployment-rate-may-2026","runLabel":"Brier-1 - no packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 0 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.8, distribution present, forecast step count 1.","evidence":["Forecast: point 4.5, 80% interval [4.1, 4.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 4.5, 80% interval [4.1, 4.9]"]}],"flags":["weak_counterarguments","no_typed_tool_call"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-unemployment-rate-may-2026\nrunLabel: Brier-1 - no packs\nresolutionDate: 2026-06-25\ntraceLineCount: 3\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments, no_typed_tool_call."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-unemployment-rate-may-2026.2026-06-20T09-10-00-04-00.australia-unemployment-rate-may-2026-brier-shadow-with-packs.d12f2ff7a6b7ce3c","runId":"run.australia-unemployment-rate-may-2026.2026-06-20T09-10-00-04-00.australia-unemployment-rate-may-2026-brier-shadow-with-packs.d12f2ff7a6b7ce3c","predictionId":"australia-unemployment-rate-may-2026","specId":"spec.australia-unemployment-rate-may-2026","runLabel":"Brier-1 - packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.43,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":["Tool call: brier.pack.apply({ target: \"abs.labour.unemployment_rate.australia.may_2026.first_print\", packs: [\"base-rate-first@0.1.0\", \"labor-market-momentum@0.1.0\", \"release-vintage-calibration@0.1.0\"] })","Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"unemployment_base_rate\",\"employment_consistency\",\"participation_check\",\"rounded_rate_grid\"] }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"unemployment_base_rate\",\"employment_consistency\",\"participation_check\",\"rounded_rate_grid\"] }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: brier.pack.apply({ target: \"abs.labour.unemployment_rate.australia.may_2026.first_print\", packs: [\"base-rate-first@0.1.0\", \"labor-market-momentum@0.1.0\", \"release-vintage-calibration@0.1.0\"] })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.6, distribution present, forecast step count 1.","evidence":["The pack run keeps the same center but trims extreme tails because employment and participation checks do not imply a move far from 4.5 percent.","Forecast: point 4.5, 80% interval [4.2, 4.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: brier.pack.apply({ target: \"abs.labour.unemployment_rate.australia.may_2026.first_print\", packs: [\"base-rate-first@0.1.0\", \"labor-market-momentum@0.1.0\", \"release-vintage-calibration@0.1.0\"] })","The pack run keeps the same center but trims extreme tails because employment and participation checks do not imply a move far from 4.5 percent."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The pack run keeps the same center but trims extreme tails because employment and participation checks do not imply a move far from 4.5 percent."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 4.5, 80% interval [4.2, 4.8]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-unemployment-rate-may-2026\nrunLabel: Brier-1 - packs\nresolutionDate: 2026-06-25\ntraceLineCount: 5\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-unemployment-rate-may-2026.2026-06-17T02-03-58Z.australia-unemployment-rate-may-2026-thesis-analyst-fast-2026-06-17t02-03-58z.d12f2ff7a6b7ce3c","runId":"run.australia-unemployment-rate-may-2026.2026-06-17T02-03-58Z.australia-unemployment-rate-may-2026-thesis-analyst-fast-2026-06-17t02-03-58z.d12f2ff7a6b7ce3c","predictionId":"australia-unemployment-rate-may-2026","specId":"spec.australia-unemployment-rate-may-2026","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.27,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 3 historical point(s) and explicit outside-view language.","evidence":["Base-rate/reference-class: adjacent-month Australian unemployment prints usually move by 0.0 to 0.2 percentage points at one-decimal precision outside shocks. The latest four seasonally adjusted prints, 4.1, 4.3, 4.3, and 4.5, imply a level around the mid-4s, while the April trend estimate of 4.3 suggests not all of the April spike should be extrapolated."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["The resolver is the ABS Labour Force, Australia May 2026 release, using the seasonally adjusted national unemployment rate on the first official print. The ABS publication page says the May 2026 release is scheduled for 25/06/2026 at 11:30am AEST, so the resolution date is 2026-06-25.","Counter-consideration: April could mark genuine labour-market weakening, with employment down 18,600 and unemployed people up 33,000, so a further increase to 4.6 or 4.7 is plausible. Against that, hours worked rose 16 million and participation slipped to 66.7%, so the unemployment rate may stabilize rather than keep rising immediately."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast Australia May 2026 unemployment first print","The resolver is the ABS Labour Force, Australia May 2026 release, using the seasonally adjusted national unemployment rate on the first official print. The ABS publication page says the May 2026 release is scheduled for 25/06/2026 at 11:30am AEST, so the resolution date is 2026-06-25."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.6, distribution present, forecast step count 1.","evidence":["Use April seasonally adjusted 4.5 as the anchor. Blend 60% latest print 4.5, 25% recent average of Jan-Apr prints (4.1+4.3+4.3+4.5)/4 = 4.3, and 15% April trend 4.3: 0.60*4.5 + 0.25*4.3 + 0.15*4.3 = 4.42, then round the forecast to the ABS one-decimal print grid and lean slightly toward persistence after April's jump, giving 4.5. An 80% interval of 4.2 to 4.8 allows roughly minus 0.3 to plus 0.3 around the point.","Forecast: point 4.5, 80% interval [4.2, 4.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast Australia May 2026 unemployment first print","Base-rate/reference-class: adjacent-month Australian unemployment prints usually move by 0.0 to 0.2 percentage points at one-decimal precision outside shocks. The latest four seasonally adjusted prints, 4.1, 4.3, 4.3, and 4.5, imply a level around the mid-4s, while the April trend estimate of 4.3 suggests not all of the April spike should be extrapolated."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-unemployment-rate-may-2026\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-06-25\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-employment-change-may-2026.2026-06-04T11-36-25-01-00.712520838c0b785e","runId":"run.australia-employment-change-may-2026.2026-06-04T11-36-25-01-00.712520838c0b785e","predictionId":"australia-employment-change-may-2026","specId":"spec.australia-employment-change-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.46,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 7 source-context item(s), activity log absent.","evidence":["Employment change is a fast, noisy target that helps calibrate household income, tax receipts, and welfare-demand predictions. This target resolves on 2026-06-25 under a first-print rule, with an expected ~3 weeks lag. The same series can also spawn next release, +3 months, unemployment threshold questions."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Employment change is a fast, noisy target that helps calibrate household income, tax receipts, and welfare-demand predictions. This target resolves on 2026-06-25 under a first-print rule, with an expected ~3 weeks lag. The same series can also spawn next release, +3 months, unemployment threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 120, distribution present, forecast step count 1.","evidence":["The April seasonally adjusted drop contrasts with a positive trend estimate and higher hours worked. The agent expects partial reversion in May but keeps a wide interval because rotation-group and modernisation effects raise first-print uncertainty.","Forecast: point 15, 80% interval [-45, 75]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The April seasonally adjusted drop contrasts with a positive trend estimate and higher hours worked. The agent expects partial reversion in May but keeps a wide interval because rotation-group and modernisation effects raise first-print uncertainty."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The April seasonally adjusted drop contrasts with a positive trend estimate and higher hours worked. The agent expects partial reversion in May but keeps a wide interval because rotation-group and modernisation effects raise first-print uncertainty."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 15, ci80: [-45, 75], context: ['April seasonally adjusted employment -18.6k', 'April trend employment +22.1k', 'hours worked +16m', 'May collection has two incoming rotation groups'] }","The April seasonally adjusted drop contrasts with a positive trend estimate and higher hours worked. The agent expects partial reversion in May but keeps a wide interval because rotation-group and modernisation effects raise first-print uncertainty."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-employment-change-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-25\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-employment-change-may-2026.2026-06-20T09-08-00-04-00.australia-employment-change-may-2026-brier-shadow-no-packs.b8d73b347d308a08","runId":"run.australia-employment-change-may-2026.2026-06-20T09-08-00-04-00.australia-employment-change-may-2026-brier-shadow-no-packs.b8d73b347d308a08","predictionId":"australia-employment-change-may-2026","specId":"spec.australia-employment-change-may-2026","runLabel":"Brier-1 - no packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 0 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 130, distribution present, forecast step count 1.","evidence":["Forecast: point 10, 80% interval [-55, 75]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 10, 80% interval [-55, 75]"]}],"flags":["weak_counterarguments","no_typed_tool_call"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-employment-change-may-2026\nrunLabel: Brier-1 - no packs\nresolutionDate: 2026-06-25\ntraceLineCount: 3\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments, no_typed_tool_call."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-employment-change-may-2026.2026-06-20T09-08-00-04-00.australia-employment-change-may-2026-brier-shadow-with-packs.d90da5fc77da3cc0","runId":"run.australia-employment-change-may-2026.2026-06-20T09-08-00-04-00.australia-employment-change-may-2026-brier-shadow-with-packs.d90da5fc77da3cc0","predictionId":"australia-employment-change-may-2026","specId":"spec.australia-employment-change-may-2026","runLabel":"Brier-1 - packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.43,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":["Tool call: brier.pack.apply({ target: \"abs.labour.employment_change.australia.may_2026.first_print\", packs: [\"base-rate-first@0.1.0\", \"labor-market-momentum@0.1.0\", \"release-vintage-calibration@0.1.0\"] })","Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"employment_base_rate\",\"hours_worked\",\"unemployment_consistency\",\"survey_release_noise\"] }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"employment_base_rate\",\"hours_worked\",\"unemployment_consistency\",\"survey_release_noise\"] }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: brier.pack.apply({ target: \"abs.labour.employment_change.australia.may_2026.first_print\", packs: [\"base-rate-first@0.1.0\", \"labor-market-momentum@0.1.0\", \"release-vintage-calibration@0.1.0\"] })","Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"employment_base_rate\",\"hours_worked\",\"unemployment_consistency\",\"survey_release_noise\"] }"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 120, distribution present, forecast step count 1.","evidence":["The pack run leans slightly positive because employment trend and hours do not confirm a sharp break, but keeps a large lower tail for survey noise.","Forecast: point 20, 80% interval [-35, 85]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: brier.pack.apply({ target: \"abs.labour.employment_change.australia.may_2026.first_print\", packs: [\"base-rate-first@0.1.0\", \"labor-market-momentum@0.1.0\", \"release-vintage-calibration@0.1.0\"] })","The pack run leans slightly positive because employment trend and hours do not confirm a sharp break, but keeps a large lower tail for survey noise."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The pack run leans slightly positive because employment trend and hours do not confirm a sharp break, but keeps a large lower tail for survey noise."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 20, 80% interval [-35, 85]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-employment-change-may-2026\nrunLabel: Brier-1 - packs\nresolutionDate: 2026-06-25\ntraceLineCount: 5\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-employment-change-may-2026.2026-06-17T02-05-03Z.australia-employment-change-may-2026-thesis-analyst-fast-2026-06-17t02-05-03z.3812528b320bfe22","runId":"run.australia-employment-change-may-2026.2026-06-17T02-05-03Z.australia-employment-change-may-2026-thesis-analyst-fast-2026-06-17t02-05-03z.3812528b320bfe22","predictionId":"australia-employment-change-may-2026","specId":"spec.australia-employment-change-may-2026","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Tool call: Read the same ABS table for prior May observations to form a May reference class.","Base-rate/reference class: the three most recent May changes were +79.6 thousand, +19.5 thousand, and -21.2 thousand, averaging about +26.0 thousand. Recent non-May momentum before April was also positive, with February and March gains around +28.9 thousand and +23.3 thousand."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Tool call: Checked the ABS April 2026 latest-release key statistics for the most recent official first-print labour-market state.","Tool call: Read the same ABS table for prior May observations to form a May reference class."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The resolver is the first ABS Labour Force, Australia May 2026 release, specifically the seasonally adjusted monthly change in employed people. The unit here is thousands of people, matching the ABS headline convention.","Tool call: Checked the ABS Labour Force, Australia all-releases page for the scheduled May 2026 publication date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 110, distribution present, forecast step count 1.","evidence":["Recent trend growth from ABS trend levels was +22.1 thousand in April; the 2023-2025 May average was +26.0 thousand; the latest seasonally adjusted print was -18.6 thousand. I weight underlying trend and May base rate more than April noise: about 0.45*22.1 + 0.35*26.0 + 0.20*(-18.6) = 15.3 thousand, rounded upward to 20 thousand because population growth and the trend series remain positive. An 80% interval of roughly +/-55 thousand gives -35 to +75 thousand.","Counter-consideration: April's unemployment-rate rise to 4.5% and the ABS note that May has two incoming rotation groups raise downside and survey-volatility risk, so I keep a wide interval that includes another negative employment change."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base-rate/reference class: the three most recent May changes were +79.6 thousand, +19.5 thousand, and -21.2 thousand, averaging about +26.0 thousand. Recent non-May momentum before April was also positive, with February and March gains around +28.9 thousand and +23.3 thousand.","Recent trend growth from ABS trend levels was +22.1 thousand in April; the 2023-2025 May average was +26.0 thousand; the latest seasonally adjusted print was -18.6 thousand. I weight underlying trend and May base rate more than April noise: about 0.45*22.1 + 0.35*26.0 + 0.20*(-18.6) = 15.3 thousand, rounded upward to 20 thousand because population growth and the trend series remain positive. An 80% interval of roughly +/-55 thousand gives -35 to +75 thousand."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-consideration: April's unemployment-rate rise to 4.5% and the ABS note that May has two incoming rotation groups raise downside and survey-volatility risk, so I keep a wide interval that includes another negative employment change."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: ABS May 2026 employment change","Recent trend growth from ABS trend levels was +22.1 thousand in April; the 2023-2025 May average was +26.0 thousand; the latest seasonally adjusted print was -18.6 thousand. I weight underlying trend and May base rate more than April noise: about 0.45*22.1 + 0.35*26.0 + 0.20*(-18.6) = 15.3 thousand, rounded upward to 20 thousand because population growth and the trend series remain positive. An 80% interval of roughly +/-55 thousand gives -35 to +75 thousand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-employment-change-may-2026\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-06-25\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-annual-rate-may-2026.2026-06-04T11-36-25-01-00.9e7b93c4d0d3e872","runId":"run.australia-cpi-annual-rate-may-2026.2026-06-04T11-36-25-01-00.9e7b93c4d0d3e872","predictionId":"australia-cpi-annual-rate-may-2026","specId":"spec.australia-cpi-annual-rate-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.32,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 7 source-context item(s), activity log absent.","evidence":["Monthly CPI is the fastest official Australian inflation read and directly informs cash-rate, real-income, and indexation forecasts. This target resolves on 2026-06-24 under a first-print rule, with an expected ~3 weeks lag. The same series can also spawn next release, +3 months, RBA reaction questions.","Tool call: abs.lookup({ release: \"Consumer Price Index, Australia\", series: \"all_groups_annual_movement\", months: [\"2026-01\", \"2026-04\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Monthly CPI is the fastest official Australian inflation read and directly informs cash-rate, real-income, and indexation forecasts. This target resolves on 2026-06-24 under a first-print rule, with an expected ~3 weeks lag. The same series can also spawn next release, +3 months, RBA reaction questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.8, distribution present, forecast step count 1.","evidence":["April CPI cooled from March but remained well above the RBA target band, with housing and transport still elevated. The agent expects a small further easing in May while keeping upside risk from fuel and administered-price categories.","Forecast: point 4.1, 80% interval [3.7, 4.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["April CPI cooled from March but remained well above the RBA target band, with housing and transport still elevated. The agent expects a small further easing in May while keeping upside risk from fuel and administered-price categories."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Monthly CPI is the fastest official Australian inflation read and directly informs cash-rate, real-income, and indexation forecasts. This target resolves on 2026-06-24 under a first-print rule, with an expected ~3 weeks lag. The same series can also spawn next release, +3 months, RBA reaction questions.","Tool result: { point: 4.1, ci80: [3.7, 4.5], context: ['April CPI 4.2% y/y; March 4.6%', 'April monthly CPI +0.4% original, -0.1% seasonally adjusted', 'trimmed mean 3.4%'] }"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-annual-rate-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-24\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-annual-rate-may-2026.2026-06-20T09-04-00-04-00.australia-cpi-annual-rate-may-2026-brier-shadow-no-packs.b7764552c628f46e","runId":"run.australia-cpi-annual-rate-may-2026.2026-06-20T09-04-00-04-00.australia-cpi-annual-rate-may-2026-brier-shadow-no-packs.b7764552c628f46e","predictionId":"australia-cpi-annual-rate-may-2026","specId":"spec.australia-cpi-annual-rate-may-2026","runLabel":"Brier-1 - no packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 0 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.2, distribution present, forecast step count 1.","evidence":["The control run persists April all-groups CPI and gives the noisy monthly indicator a wide symmetric interval.","Forecast: point 4.2, 80% interval [3.6, 4.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The control run persists April all-groups CPI and gives the noisy monthly indicator a wide symmetric interval.","Forecast: point 4.2, 80% interval [3.6, 4.8]"]}],"flags":["weak_counterarguments","no_typed_tool_call"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-annual-rate-may-2026\nrunLabel: Brier-1 - no packs\nresolutionDate: 2026-06-24\ntraceLineCount: 3\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments, no_typed_tool_call."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-annual-rate-may-2026.2026-06-20T09-04-00-04-00.australia-cpi-annual-rate-may-2026-brier-shadow-with-packs.6626aeab6b4b77bf","runId":"run.australia-cpi-annual-rate-may-2026.2026-06-20T09-04-00-04-00.australia-cpi-annual-rate-may-2026-brier-shadow-with-packs.6626aeab6b4b77bf","predictionId":"australia-cpi-annual-rate-may-2026","specId":"spec.australia-cpi-annual-rate-may-2026","runLabel":"Brier-1 - packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.89,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":["Tool call: brier.pack.apply({ target: \"abs.cpi.all_groups_annual_rate.australia.may_2026.first_print\", packs: [\"base-rate-first@0.1.0\", \"energy-price-nowcast@0.1.0\", \"cpi-component-decomposition@0.1.0\", \"release-vintage-calibration@0.1.0\"] })","Tool result: { admitted: 4, mode: \"with_packs\", required_checks: [\"all_groups_base_rate\",\"housing_transport_components\",\"energy_nowcast\",\"monthly_cpi_transition\"] }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: brier.pack.apply({ target: \"abs.cpi.all_groups_annual_rate.australia.may_2026.first_print\", packs: [\"base-rate-first@0.1.0\", \"energy-price-nowcast@0.1.0\", \"cpi-component-decomposition@0.1.0\", \"release-vintage-calibration@0.1.0\"] })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.6, distribution present, forecast step count 1.","evidence":["The pack run gives more weight to housing, transport, and administered-price components, but keeps a broad interval for monthly-indicator volatility.","Forecast: point 4.6, 80% interval [3.8, 5.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The pack run gives more weight to housing, transport, and administered-price components, but keeps a broad interval for monthly-indicator volatility."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The pack run gives more weight to housing, transport, and administered-price components, but keeps a broad interval for monthly-indicator volatility.","Forecast: point 4.6, 80% interval [3.8, 5.4]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-annual-rate-may-2026\nrunLabel: Brier-1 - packs\nresolutionDate: 2026-06-24\ntraceLineCount: 5\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-annual-rate-may-2026.2026-06-17T02-02-48Z.australia-cpi-annual-rate-may-2026-thesis-analyst-fast-2026-06-17t02-02-48z.66771066a1ed088b","runId":"run.australia-cpi-annual-rate-may-2026.2026-06-17T02-02-48Z.australia-cpi-annual-rate-may-2026-thesis-analyst-fast-2026-06-17t02-02-48z.66771066a1ed088b","predictionId":"australia-cpi-annual-rate-may-2026","specId":"spec.australia-cpi-annual-rate-may-2026","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.08,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":["Base-rate/reference-class anchor: recent monthly complete-CPI annual readings sit mostly from 3.4% to 4.6%, while the May 2025 base month was unusually soft at -0.5% month over month. Replacing that base with even a modest positive May 2026 month tends to lift the annual rate from April's 4.2%.","Counter-consideration: April already showed a fuel-driven pullback from March and seasonally adjusted all-groups CPI fell 0.1%, so a weak May fuel or travel print could keep the annual rate nearer the low 4s despite the favorable base effect."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The resolver is the ABS Consumer Price Index, Australia first release for May 2026, using the All groups CPI annual movement in original terms. The old Monthly CPI Indicator ceased after September 2025, and the complete Monthly CPI is now the headline monthly CPI publication.","Tool call: Opened the ABS Consumer Price Index, Australia latest release page for April 2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The resolver is the ABS Consumer Price Index, Australia first release for May 2026, using the All groups CPI annual movement in original terms. The old Monthly CPI Indicator ceased after September 2025, and the complete Monthly CPI is now the headline monthly CPI publication.","Tool call: Opened the ABS Consumer Price Index, Australia latest release page for April 2026."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.4, distribution present, forecast step count 1.","evidence":["Tool result: Fetched transition details: ABS said the Monthly CPI starts 26/11/2025 for October 2025, the old Indicator would no longer be produced after 29/10/2025, and the new monthly data series go back to April 2024.","Tool call: Read ABS April 2026 component and analytical series detail."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: ABS All groups CPI annual inflation for May 2026","Approximate annual-rate bridge: Apr 2026 over Apr 2025 is 1.042. If May 2026 monthly CPI rises about 0.2% and May 2025 was -0.5%, then May annual CPI is 1.042 * 1.002 / 0.995 - 1 = 0.0494, or 4.9% after one-decimal rounding. An 80% interval allowing roughly -0.5% to +0.8% May monthly outcomes maps to about 4.2% to 5.6%."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-annual-rate-may-2026\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-06-24\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cash-rate-june-2026-rba.2026-06-04T11-36-25-01-00.b5881999155b0f27","runId":"run.australia-cash-rate-june-2026-rba.2026-06-04T11-36-25-01-00.b5881999155b0f27","predictionId":"australia-cash-rate-june-2026-rba","specId":"spec.australia-cash-rate-june-2026-rba","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":1,"rationale":"Score 1/4: 1 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 7 source-context item(s), activity log absent.","evidence":["The RBA cash rate target is Australia's main monetary-policy setting and links inflation, mortgage costs, labour-market slack, and government fiscal forecasts. This target resolves on 2026-06-16 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next decision, +3 months, inflation reaction questions."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The RBA cash rate target is Australia's main monetary-policy setting and links inflation, mortgage costs, labour-market slack, and government fiscal forecasts. This target resolves on 2026-06-16 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next decision, +3 months, inflation reaction questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.25, distribution present, forecast step count 1.","evidence":["Inflation is still above target and trimmed mean remains elevated, while the unemployment rise argues against over-tightening. The agent centers on a hold, with the main tail being a 25 basis point increase rather than a cut.","Forecast: point 4.35, 80% interval [4.35, 4.6]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The RBA cash rate target is Australia's main monetary-policy setting and links inflation, mortgage costs, labour-market slack, and government fiscal forecasts. This target resolves on 2026-06-16 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next decision, +3 months, inflation reaction questions.","Tool result: { point: 4.35, ci80: [4.35, 4.60], context: ['cash rate target 4.35% effective 2026-05-06', 'next update 2026-06-16 14:30', 'April CPI 4.2%', 'April unemployment 4.5%'] }"]}],"flags":["weak_base_rate_use","weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cash-rate-june-2026-rba\nrunLabel: Headline\nresolutionDate: 2026-06-16\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (1/4). Flags: weak_base_rate_use, weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.euro-area-ecb-deposit-facility-rate-june-2026.2026-06-06T05-41-31-01-00.e3888b3064c078ed","runId":"run.euro-area-ecb-deposit-facility-rate-june-2026.2026-06-06T05-41-31-01-00.e3888b3064c078ed","predictionId":"euro-area-ecb-deposit-facility-rate-june-2026","specId":"spec.euro-area-ecb-deposit-facility-rate-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.19,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 4 source-context item(s), activity log absent.","evidence":["The ECB deposit facility rate is the euro area's main short-rate policy setting and directly shapes borrowing costs, exchange-rate pressure, and fiscal-debt-interest forecasts. This target resolves on 2026-06-11 under a first-print rule, with an expected ~1 week lag. The same series can also spawn next decision, +3 months, inflation reaction questions.","Tool call: ecb.lookup({ series: \"deposit_facility_rate\", decisions: [\"2026-03-19\", \"2026-04-30\"], next_decision: \"2026-06-11 14:15 CET\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The ECB deposit facility rate is the euro area's main short-rate policy setting and directly shapes borrowing costs, exchange-rate pressure, and fiscal-debt-interest forecasts. This target resolves on 2026-06-11 under a first-print rule, with an expected ~1 week lag. The same series can also spawn next decision, +3 months, inflation reaction questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.25, distribution present, forecast step count 1.","evidence":["The ECB held in April and framed policy as data-dependent. May inflation moved above target with energy and services pressure, so the agent rules out a cut in the central interval and gives the main tail to a 25 basis point hike, but keeps a hold as the modal outcome.","Forecast: point 2, 80% interval [2, 2.25]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The ECB deposit facility rate is the euro area's main short-rate policy setting and directly shapes borrowing costs, exchange-rate pressure, and fiscal-debt-interest forecasts. This target resolves on 2026-06-11 under a first-print rule, with an expected ~1 week lag. The same series can also spawn next decision, +3 months, inflation reaction questions.","The ECB held in April and framed policy as data-dependent. May inflation moved above target with energy and services pressure, so the agent rules out a cut in the central interval and gives the main tail to a 25 basis point hike, but keeps a hold as the modal outcome."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The ECB held in April and framed policy as data-dependent. May inflation moved above target with energy and services pressure, so the agent rules out a cut in the central interval and gives the main tail to a 25 basis point hike, but keeps a hold as the modal outcome."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The ECB deposit facility rate is the euro area's main short-rate policy setting and directly shapes borrowing costs, exchange-rate pressure, and fiscal-debt-interest forecasts. This target resolves on 2026-06-11 under a first-print rule, with an expected ~1 week lag. The same series can also spawn next decision, +3 months, inflation reaction questions.","Tool result: { point: 2.00, ci80: [2.00, 2.25], context: ['April decision held deposit facility at 2.00%', 'May flash HICP 3.2%; energy 10.9%; services 3.5%', 'June decisions scheduled for 2026-06-11 14:15 CET'] }"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: euro-area-ecb-deposit-facility-rate-june-2026\nrunLabel: Headline\nresolutionDate: 2026-06-11\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.euro-area-hicp-annual-rate-may-2026-final.2026-06-06T05-41-31-01-00.551502d61103eb3c","runId":"run.euro-area-hicp-annual-rate-may-2026-final.2026-06-06T05-41-31-01-00.551502d61103eb3c","predictionId":"euro-area-hicp-annual-rate-may-2026-final","specId":"spec.euro-area-hicp-annual-rate-may-2026-final","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.19,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 5 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 4 source-context item(s), activity log absent.","evidence":["HICP is the ECB's headline inflation measure and a high-frequency input for real-income, benefit-indexation, and monetary-policy predictions. This target resolves on 2026-06-17 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, +3 months, ECB reaction questions.","Tool result: { point: 3.2, ci80: [3.1, 3.3], context: ['May flash all-items HICP 3.2%', 'April final HICP 3.0%', 'flash-to-final revisions are usually small'] }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · final release","HICP is the ECB's headline inflation measure and a high-frequency input for real-income, benefit-indexation, and monetary-policy predictions. This target resolves on 2026-06-17 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, +3 months, ECB reaction questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.2, distribution present, forecast step count 1.","evidence":["Eurostat's May flash already gives the all-items rate at 3.2%. The final release can move by a tenth if national detail revises, but the agent treats 3.2% as the overwhelmingly modal final first print.","Forecast: point 3.2, 80% interval [3.1, 3.3]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Eurostat's May flash already gives the all-items rate at 3.2%. The final release can move by a tenth if national detail revises, but the agent treats 3.2% as the overwhelmingly modal final first print."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 3.2, ci80: [3.1, 3.3], context: ['May flash all-items HICP 3.2%', 'April final HICP 3.0%', 'flash-to-final revisions are usually small'] }","Forecast: point 3.2, 80% interval [3.1, 3.3]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: euro-area-hicp-annual-rate-may-2026-final\nrunLabel: Headline\nresolutionDate: 2026-06-17\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.euro-area-hicp-annual-rate-june-2026-flash.2026-06-06T05-41-31-01-00.f311985c1075553a","runId":"run.euro-area-hicp-annual-rate-june-2026-flash.2026-06-06T05-41-31-01-00.f311985c1075553a","predictionId":"euro-area-hicp-annual-rate-june-2026-flash","specId":"spec.euro-area-hicp-annual-rate-june-2026-flash","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.22,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 5 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 4 source-context item(s), activity log absent.","evidence":["HICP is the ECB's headline inflation measure and a high-frequency input for real-income, benefit-indexation, and monetary-policy predictions. This target resolves on 2026-07-01 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, +3 months, ECB reaction questions."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · flash release","HICP is the ECB's headline inflation measure and a high-frequency input for real-income, benefit-indexation, and monetary-policy predictions. This target resolves on 2026-07-01 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, +3 months, ECB reaction questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.6, distribution present, forecast step count 1.","evidence":["May's 3.2% reading was pushed up by energy and services. The agent expects only mild easing in June because the energy shock remains visible, but assigns a wider interval than the May final forecast because the June flash is not yet observed.","Forecast: point 3.1, 80% interval [2.8, 3.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["May's 3.2% reading was pushed up by energy and services. The agent expects only mild easing in June because the energy shock remains visible, but assigns a wider interval than the May final forecast because the June flash is not yet observed."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["May's 3.2% reading was pushed up by energy and services. The agent expects only mild easing in June because the energy shock remains visible, but assigns a wider interval than the May final forecast because the June flash is not yet observed."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 3.1, ci80: [2.8, 3.4], context: ['May flash HICP 3.2%', 'energy annual rate 10.9%', 'services 3.5%', 'next flash release 2026-07-01'] }","May's 3.2% reading was pushed up by energy and services. The agent expects only mild easing in June because the energy shock remains visible, but assigns a wider interval than the May final forecast because the June flash is not yet observed."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: euro-area-hicp-annual-rate-june-2026-flash\nrunLabel: Headline\nresolutionDate: 2026-07-01\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.euro-area-hicp-annual-rate-june-2026-flash.2026-06-27T13-13-42Z.euro-area-hicp-annual-rate-june-2026-flash-thesis-analyst-fast-2026-06-27t13-13-42z.b86a7005b50fa541","runId":"run.euro-area-hicp-annual-rate-june-2026-flash.2026-06-27T13-13-42Z.euro-area-hicp-annual-rate-june-2026-flash-thesis-analyst-fast-2026-06-27t13-13-42z.b86a7005b50fa541","predictionId":"euro-area-hicp-annual-rate-june-2026-flash","specId":"spec.euro-area-hicp-annual-rate-june-2026-flash","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Reference-class base rate: the latest five official monthly prints average 2.2 percent, while the latest value is 1.9 percent. The model prior is persistence or random walk from the latest flash print with light mean reversion toward the recent official average; no fitted time-series model is used for this one-month flash target.","Counter-consideration: the forecast could be too high if June fuel and electricity effects are sharply negative or if services repricing fades abruptly; it could be too low if travel, accommodation, or food prices rebound and energy base effects stop dragging."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The target is the first Eurostat euro-indicators flash print for euro area all-items HICP annual inflation in June 2026. The resolver is the official flash release rounded to one decimal, with later final HICP data or revisions ignored.","Reference-class base rate: the latest five official monthly prints average 2.2 percent, while the latest value is 1.9 percent. The model prior is persistence or random walk from the latest flash print with light mean reversion toward the recent official average; no fitted time-series model is used for this one-month flash target."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The target is the first Eurostat euro-indicators flash print for euro area all-items HICP annual inflation in June 2026. The resolver is the official flash release rounded to one decimal, with later final HICP data or revisions ignored.","Tool call: Checked Eurostat euro-indicators release calendar for the June 2026 euro area inflation flash estimate."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.6, distribution present, forecast step count 1.","evidence":["Starting from the latest print of 1.9, add 0.1 for mean reversion toward the five-month official average of 2.2, add 0.0 for mixed energy/core pressures after offsetting services persistence against energy drag, giving 2.0 after one-decimal rounding. I use a judgmental 80 percent interval of plus or minus 0.3 percentage point, wide enough for normal monthly flash volatility and rounding risk but not for a broad energy shock, giving 1.7 to 2.3.","Upside scenario: services and food remain sticky and energy stops subtracting, producing a rounded 2.3 or slightly higher. Downside scenario: energy and goods weaken together, pulling the rounded print to 1.7 or below. Outside-interval scenarios require a broad energy shock or a surprisingly synchronized rebound across services, food, and energy."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level and momentum: the headline level is already near 2 percent. Momentum from January to May is negative by 0.4 percentage point, but the last observation at 1.9 is close enough to target that a large further fall would need another downside surprise in energy or package holidays.","Mechanisms: services persistence and food keep upside pressure in the core-like part of the basket, while energy remains the main downside and volatility channel. ECB policy works with a lag and is more relevant to medium-term demand than to this one-month flash print."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level and momentum: the headline level is already near 2 percent. Momentum from January to May is negative by 0.4 percentage point, but the last observation at 1.9 is close enough to target that a large further fall would need another downside surprise in energy or package holidays.","Starting from the latest print of 1.9, add 0.1 for mean reversion toward the five-month official average of 2.2, add 0.0 for mixed energy/core pressures after offsetting services persistence against energy drag, giving 2.0 after one-decimal rounding. I use a judgmental 80 percent interval of plus or minus 0.3 percentage point, wide enough for normal monthly flash volatility and rounding risk but not for a broad energy shock, giving 1.7 to 2.3."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Euro area June 2026 HICP flash forecast","Level and momentum: the headline level is already near 2 percent. Momentum from January to May is negative by 0.4 percentage point, but the last observation at 1.9 is close enough to target that a large further fall would need another downside surprise in energy or package holidays."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: euro-area-hicp-annual-rate-june-2026-flash\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-07-01\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.euro-area-unemployment-rate-may-2026.2026-06-06T05-41-31-01-00.a21de549c4f6899d","runId":"run.euro-area-unemployment-rate-may-2026.2026-06-06T05-41-31-01-00.a21de549c4f6899d","predictionId":"euro-area-unemployment-rate-may-2026","specId":"spec.euro-area-unemployment-rate-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 4 source-context item(s), activity log absent.","evidence":["Euro area unemployment anchors labour-income, social-benefit, fiscal, and monetary-policy forecasts across member states. This target resolves on 2026-07-02 under a first-print rule, with an expected ~1 month lag. The same series can also spawn next release, +3 months, slack threshold questions.","Tool result: { jan: 6.1, feb: 6.2, mar_revised: 6.3, apr: 6.3, apr_unemployed_millions: 11.075, next_release: '2026-07-02' }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Euro area unemployment anchors labour-income, social-benefit, fiscal, and monetary-policy forecasts across member states. This target resolves on 2026-07-02 under a first-print rule, with an expected ~1 month lag. The same series can also spawn next release, +3 months, slack threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.2, distribution present, forecast step count 1.","evidence":["Monthly euro area unemployment has been stable around 6.2%-6.3% even as inflation and growth risks shifted. The agent centers May at 6.3% and keeps the interval tight because one-month changes in the harmonised rate are usually one tenth or less.","Forecast: point 6.3, 80% interval [6.2, 6.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Monthly euro area unemployment has been stable around 6.2%-6.3% even as inflation and growth risks shifted. The agent centers May at 6.3% and keeps the interval tight because one-month changes in the harmonised rate are usually one tenth or less."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Monthly euro area unemployment has been stable around 6.2%-6.3% even as inflation and growth risks shifted. The agent centers May at 6.3% and keeps the interval tight because one-month changes in the harmonised rate are usually one tenth or less."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Euro area unemployment anchors labour-income, social-benefit, fiscal, and monetary-policy forecasts across member states. This target resolves on 2026-07-02 under a first-print rule, with an expected ~1 month lag. The same series can also spawn next release, +3 months, slack threshold questions.","Tool result: { point: 6.3, ci80: [6.2, 6.4], context: ['April unemployment 6.3%', 'March revised to 6.3%', 'April unemployed count 11.075m', 'next monthly release 2026-07-02'] }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: euro-area-unemployment-rate-may-2026\nrunLabel: Headline\nresolutionDate: 2026-07-02\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.euro-area-unemployment-rate-may-2026.2026-06-17T02-11-36Z.euro-area-unemployment-rate-may-2026-thesis-analyst-fast-2026-06-17t02-11-36z.b758e133d776e4f9","runId":"run.euro-area-unemployment-rate-may-2026.2026-06-17T02-11-36Z.euro-area-unemployment-rate-may-2026-thesis-analyst-fast-2026-06-17t02-11-36z.b758e133d776e4f9","predictionId":"euro-area-unemployment-rate-may-2026","specId":"spec.euro-area-unemployment-rate-may-2026","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: monthly euro area unemployment rates usually move slowly at one-decimal precision; the last five official points shown for the euro area are 6.3, 6.3, 6.4, 6.3, and 6.3, making 6.3 the modal and median recent print.","Use recent monthly persistence as the anchor: median(6.3, 6.3, 6.4, 6.3, 6.3) = 6.3. Apply no directional adjustment because the April unemployment headcount fell but macro growth weakened. Set an 80% interval of +/-0.2 percentage points around 6.3, giving 6.1 to 6.5."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The target is Eurostat's first official May 2026 euro area seasonally adjusted unemployment rate, total sex and age 15-74, in percent. The April 2026 Eurostat release states the next unemployment release is on 2 July 2026, so that is the verified resolution date for the May 2026 first print.","Tool result: Fetched euro area rates: Apr-25 6.3, Jan-26 6.3, Feb-26 6.4, Mar-26 6.3, Apr-26 6.3; fetched unemployed persons: Apr-26 11075 thousand and Mar-26 11159 thousand."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Euro area unemployment rate, May 2026 first print","The target is Eurostat's first official May 2026 euro area seasonally adjusted unemployment rate, total sex and age 15-74, in percent. The April 2026 Eurostat release states the next unemployment release is on 2 July 2026, so that is the verified resolution date for the May 2026 first print."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.4, distribution present, forecast step count 1.","evidence":["Tool result: Fetched official listing values: GDP Q1 2026 down 0.2% in euro area, employment Q1 2026 up 0.1%, May 2026 euro area inflation flash 3.2%, April 2026 retail trade down 0.4%.","Counter-consideration: Q1 GDP contraction of 0.2%, weaker retail trade, and higher May inflation at 3.2% could weaken demand and push unemployment up. These forces justify keeping upside mass at 6.4-6.5 rather than making the interval too narrow."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Use recent monthly persistence as the anchor: median(6.3, 6.3, 6.4, 6.3, 6.3) = 6.3. Apply no directional adjustment because the April unemployment headcount fell but macro growth weakened. Set an 80% interval of +/-0.2 percentage points around 6.3, giving 6.1 to 6.5."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Use recent monthly persistence as the anchor: median(6.3, 6.3, 6.4, 6.3, 6.3) = 6.3. Apply no directional adjustment because the April unemployment headcount fell but macro growth weakened. Set an 80% interval of +/-0.2 percentage points around 6.3, giving 6.1 to 6.5."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Base rate/reference class: monthly euro area unemployment rates usually move slowly at one-decimal precision; the last five official points shown for the euro area are 6.3, 6.3, 6.4, 6.3, and 6.3, making 6.3 the modal and median recent print.","The April level is stable year-on-year and month-on-month, while the number of euro area unemployed fell by 84 thousand from March to April. That argues against forecasting a near-term jump in the rounded May rate."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: euro-area-unemployment-rate-may-2026\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-07-02\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.japan-boj-policy-rate-june-2026.2026-06-06T05-41-31-01-00.69ad79c7595c8466","runId":"run.japan-boj-policy-rate-june-2026.2026-06-06T05-41-31-01-00.69ad79c7595c8466","predictionId":"japan-boj-policy-rate-june-2026","specId":"spec.japan-boj-policy-rate-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.46,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 4 source-context item(s), activity log absent.","evidence":["The BOJ policy-rate guideline is Japan's central monetary-policy setting and connects inflation, wages, yen pressure, and public-debt-service forecasts. This target resolves on 2026-06-16 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next decision, +3 months, inflation reaction questions.","Tool call: boj.lookup({ release: \"Statement on Monetary Policy\", decisions: [\"2026-01-23\", \"2026-03-19\", \"2026-04-28\"], next_meeting: \"2026-06-15/16\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The BOJ policy-rate guideline is Japan's central monetary-policy setting and connects inflation, wages, yen pressure, and public-debt-service forecasts. This target resolves on 2026-06-16 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next decision, +3 months, inflation reaction questions.","Tool call: boj.lookup({ release: \"Statement on Monetary Policy\", decisions: [\"2026-01-23\", \"2026-03-19\", \"2026-04-28\"], next_meeting: \"2026-06-15/16\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.25, distribution present, forecast step count 1.","evidence":["Three April dissents wanted a 1.0% guideline, but the majority held at 0.75%. The agent keeps a hold as the modal outcome because national CPI is still modest, while the dissent pattern and upside price-risk language keep a live hike tail.","Forecast: point 0.75, 80% interval [0.75, 1]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The BOJ policy-rate guideline is Japan's central monetary-policy setting and connects inflation, wages, yen pressure, and public-debt-service forecasts. This target resolves on 2026-06-16 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next decision, +3 months, inflation reaction questions.","Three April dissents wanted a 1.0% guideline, but the majority held at 0.75%. The agent keeps a hold as the modal outcome because national CPI is still modest, while the dissent pattern and upside price-risk language keep a live hike tail."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Three April dissents wanted a 1.0% guideline, but the majority held at 0.75%. The agent keeps a hold as the modal outcome because national CPI is still modest, while the dissent pattern and upside price-risk language keep a live hike tail."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The BOJ policy-rate guideline is Japan's central monetary-policy setting and connects inflation, wages, yen pressure, and public-debt-service forecasts. This target resolves on 2026-06-16 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next decision, +3 months, inflation reaction questions.","Tool result: { point: 0.75, ci80: [0.75, 1.00], context: ['April guideline around 0.75%', 'April vote 6-3; three members preferred 1.00%', 'June meeting June 15-16', 'April national CPI 1.4%'] }"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: japan-boj-policy-rate-june-2026\nrunLabel: Headline\nresolutionDate: 2026-06-16\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.japan-cpi-annual-rate-may-2026.2026-06-06T05-41-31-01-00.322d1a50037ed203","runId":"run.japan-cpi-annual-rate-may-2026.2026-06-06T05-41-31-01-00.322d1a50037ed203","predictionId":"japan-cpi-annual-rate-may-2026","specId":"spec.japan-cpi-annual-rate-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.32,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 4 source-context item(s), activity log absent.","evidence":["Japan's national CPI is the official inflation read behind BOJ policy-rate decisions, wage bargaining, and real-income forecasts. This target resolves on 2026-06-19 under a first-print rule, with an expected ~3 weeks lag. The same series can also spawn next release, +3 months, BOJ reaction questions.","Tool call: statjp.lookup({ release: \"Consumer Price Index\", series: \"national_all_items_annual_rate\", months: [\"2026-02\", \"2026-04\"], next_release: \"2026-06-19\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Japan's national CPI is the official inflation read behind BOJ policy-rate decisions, wage bargaining, and real-income forecasts. This target resolves on 2026-06-19 under a first-print rule, with an expected ~3 weeks lag. The same series can also spawn next release, +3 months, BOJ reaction questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.8, distribution present, forecast step count 1.","evidence":["April national CPI was 1.4%. The agent expects a small May rebound from food, energy, and yen pass-through risk, but keeps the interval wide because Tokyo-to-national translation and subsidy effects can shift the first print.","Forecast: point 1.5, 80% interval [1.1, 1.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["April national CPI was 1.4%. The agent expects a small May rebound from food, energy, and yen pass-through risk, but keeps the interval wide because Tokyo-to-national translation and subsidy effects can shift the first print."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["April national CPI was 1.4%. The agent expects a small May rebound from food, energy, and yen pass-through risk, but keeps the interval wide because Tokyo-to-national translation and subsidy effects can shift the first print."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Japan's national CPI is the official inflation read behind BOJ policy-rate decisions, wage bargaining, and real-income forecasts. This target resolves on 2026-06-19 under a first-print rule, with an expected ~3 weeks lag. The same series can also spawn next release, +3 months, BOJ reaction questions.","Tool result: { point: 1.5, ci80: [1.1, 1.9], context: ['April national all-items CPI 1.4%', 'May national CPI release scheduled for 2026-06-19', 'Tokyo preliminary CPI usually leads national CPI'] }"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: japan-cpi-annual-rate-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-19\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.japan-tokyo-cpi-annual-rate-june-2026-prelim.2026-06-06T05-41-31-01-00.816901f948651144","runId":"run.japan-tokyo-cpi-annual-rate-june-2026-prelim.2026-06-06T05-41-31-01-00.816901f948651144","predictionId":"japan-tokyo-cpi-annual-rate-june-2026-prelim","specId":"spec.japan-tokyo-cpi-annual-rate-june-2026-prelim","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.08,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 4 source-context item(s), activity log absent.","evidence":["Tokyo CPI is Japan's fastest official inflation indicator and gives agents an early signal before national CPI resolves. This target resolves on 2026-06-26 under a first-print rule, with an expected ~4 weeks lag. The same series can also spawn next release, national CPI nowcast, BOJ reaction questions.","Tool call: statjp.lookup({ release: \"Consumer Price Index, Ku-area of Tokyo preliminary\", series: \"all_items_annual_rate\", months: [\"2026-04\", \"2026-05\"], next_release: \"2026-06-26\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · preliminary release","Tokyo CPI is Japan's fastest official inflation indicator and gives agents an early signal before national CPI resolves. This target resolves on 2026-06-26 under a first-print rule, with an expected ~4 weeks lag. The same series can also spawn next release, national CPI nowcast, BOJ reaction questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.8, distribution present, forecast step count 1.","evidence":["Forecast: point 1.6, 80% interval [1.2, 2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Tokyo preliminary CPI is close to the national trend but can move first on administered prices and services. The agent predicts a modest June increase while leaving room for unchanged inflation if utility subsidies dominate."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 1.6, ci80: [1.2, 2.0], context: ['Tokyo May preliminary CPI around 1.4%', 'national April CPI 1.4%', 'June Tokyo release scheduled 2026-06-26'] }","Forecast: point 1.6, 80% interval [1.2, 2]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: japan-tokyo-cpi-annual-rate-june-2026-prelim\nrunLabel: Headline\nresolutionDate: 2026-06-26\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.japan-tokyo-cpi-annual-rate-june-2026-prelim.2026-06-17T02-06-54Z.japan-tokyo-cpi-annual-rate-june-2026-prelim-thesis-analyst-fast-2026-06-17t02-06-54z.820af3753e70b32d","runId":"run.japan-tokyo-cpi-annual-rate-june-2026-prelim.2026-06-17T02-06-54Z.japan-tokyo-cpi-annual-rate-june-2026-prelim-thesis-analyst-fast-2026-06-17t02-06-54z.820af3753e70b32d","predictionId":"japan-tokyo-cpi-annual-rate-june-2026-prelim","specId":"spec.japan-tokyo-cpi-annual-rate-june-2026-prelim","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.27,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":["Tool call: Checked the e-Stat CPI database view for the current Tokyo table metadata and available time dimension.","Base-rate/reference class: for monthly Tokyo all-items YoY CPI when the latest four prints are 2.9 to 3.5 percent and the target is one month ahead, a persistence forecast centered near the latest two-month average is usually stronger than extrapolating a new trend."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Tool call: Checked the Statistics Bureau CPI landing page for the official CPI data and schedule entry points.","Tool result: Official CPI page lists Consumer Price Index results and links to Japan / Ku-area of Tokyo latest monthly results; page update notes include 23 January 2026 and the CPI area result entry."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is the Statistics Bureau of Japan/e-Stat first preliminary Ku-area of Tokyo CPI for June 2026, specifically all items, change over the year, rounded to one decimal percent.","Tool call: Checked the official CPI release schedule for the June 2026 Tokyo preliminary release date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.6, distribution present, forecast step count 1.","evidence":["Latest two-month average = (3.4 + 3.5) / 2 = 3.45, rounded to the agency precision gives 3.5. Recent four-month range is 0.6 percentage points; an 80 percent interval of roughly plus or minus 0.8 around 3.5 gives 2.7 to 4.3.","Counter-consideration: headline all-items CPI can move more than core measures because fresh food, energy, and subsidy timing can shift the monthly YoY rate; this keeps the interval wider than the recent four-month range."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Counter-consideration: headline all-items CPI can move more than core measures because fresh food, energy, and subsidy timing can shift the monthly YoY rate; this keeps the interval wider than the recent four-month range."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast Tokyo all-items CPI YoY for June 2026","Tool call: Checked the Statistics Bureau CPI landing page for the official CPI data and schedule entry points."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: japan-tokyo-cpi-annual-rate-june-2026-prelim\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-06-26\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.japan-unemployment-rate-may-2026.2026-06-06T05-41-31-01-00.e37f19c9ee504438","runId":"run.japan-unemployment-rate-may-2026.2026-06-06T05-41-31-01-00.e37f19c9ee504438","predictionId":"japan-unemployment-rate-may-2026","specId":"spec.japan-unemployment-rate-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 4 source-context item(s), activity log absent.","evidence":["Japan's unemployment rate is a compact labour-market slack target for wage, consumption, and monetary-policy forecasts. This target resolves on 2026-06-30 under a first-print rule, with an expected ~1 month lag. The same series can also spawn next release, +3 months, wage pressure questions."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Japan's unemployment rate is a compact labour-market slack target for wage, consumption, and monetary-policy forecasts. This target resolves on 2026-06-30 under a first-print rule, with an expected ~1 month lag. The same series can also spawn next release, +3 months, wage pressure questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.5, distribution present, forecast step count 1.","evidence":["The April rate fell to 2.5% after March's 2.7%. Japan's unemployment rate usually moves slowly, so the agent holds the central estimate at 2.5% with a two-to-three-tenths uncertainty band.","Forecast: point 2.5, 80% interval [2.3, 2.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Japan's unemployment rate is a compact labour-market slack target for wage, consumption, and monetary-policy forecasts. This target resolves on 2026-06-30 under a first-print rule, with an expected ~1 month lag. The same series can also spawn next release, +3 months, wage pressure questions."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["The April rate fell to 2.5% after March's 2.7%. Japan's unemployment rate usually moves slowly, so the agent holds the central estimate at 2.5% with a two-to-three-tenths uncertainty band."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Japan's unemployment rate is a compact labour-market slack target for wage, consumption, and monetary-policy forecasts. This target resolves on 2026-06-30 under a first-print rule, with an expected ~1 month lag. The same series can also spawn next release, +3 months, wage pressure questions.","Tool result: { point: 2.5, ci80: [2.3, 2.8], context: ['April unemployment 2.5%', 'March 2.7%', 'May release scheduled for 2026-06-30'] }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: japan-unemployment-rate-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.japan-unemployment-rate-may-2026.2026-06-17T02-09-06Z.japan-unemployment-rate-may-2026-thesis-analyst-fast-2026-06-17t02-09-06z.e37f19c9ee504438","runId":"run.japan-unemployment-rate-may-2026.2026-06-17T02-09-06Z.japan-unemployment-rate-may-2026-thesis-analyst-fast-2026-06-17t02-09-06z.e37f19c9ee504438","predictionId":"japan-unemployment-rate-may-2026","specId":"spec.japan-unemployment-rate-may-2026","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.54,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 3 historical point(s) and explicit outside-view language.","evidence":["The resolver is the Statistics Bureau of Japan Labour Force Survey Basic Tabulation, seasonally adjusted unemployment rate for total persons aged 15 years or over, May 2026 first print, not a later revised e-Stat historical value.","Base-rate/reference-class: over the last five fetched monthly observations, the mean is 2.62 percent and every value lies between 2.5 and 2.7 percent, so the best prior for one month ahead is persistence near 2.6 with low volatility."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["The resolver is the Statistics Bureau of Japan Labour Force Survey Basic Tabulation, seasonally adjusted unemployment rate for total persons aged 15 years or over, May 2026 first print, not a later revised e-Stat historical value.","Tool call: Checked the Statistics Bureau Labour Force Survey landing and survey-results pages for the official series surface and latest monthly release status."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is the Statistics Bureau of Japan Labour Force Survey Basic Tabulation, seasonally adjusted unemployment rate for total persons aged 15 years or over, May 2026 first print, not a later revised e-Stat historical value.","Tool call: Checked the Statistics Bureau Labour Force Survey landing and survey-results pages for the official series surface and latest monthly release status."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.5, distribution present, forecast step count 1.","evidence":["Use a persistence-weighted estimate: 60 percent on April 2026 at 2.5 and 40 percent on the recent five-month mean 2.62 gives 0.6*2.5 + 0.4*2.62 = 2.548, rounded to the agency precision as 2.5 percent. Set an 80 percent interval around recent monthly variation and one-print risk at 2.3 to 2.8 percent.","Forecast: point 2.5, 80% interval [2.3, 2.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Use a persistence-weighted estimate: 60 percent on April 2026 at 2.5 and 40 percent on the recent five-month mean 2.62 gives 0.6*2.5 + 0.4*2.62 = 2.548, rounded to the agency precision as 2.5 percent. Set an 80 percent interval around recent monthly variation and one-print risk at 2.3 to 2.8 percent."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast Japan May 2026 LFS unemployment rate","Use a persistence-weighted estimate: 60 percent on April 2026 at 2.5 and 40 percent on the recent five-month mean 2.62 gives 0.6*2.5 + 0.4*2.62 = 2.548, rounded to the agency precision as 2.5 percent. Set an 80 percent interval around recent monthly variation and one-print risk at 2.3 to 2.8 percent."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: japan-unemployment-rate-may-2026\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-06-30\ntraceLineCount: 12\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.japan-unemployment-rate-may-2026.2026-06-27T12-57-12Z.japan-unemployment-rate-may-2026-thesis-analyst-fast-2026-06-27t12-57-12z.e37f19c9ee504438","runId":"run.japan-unemployment-rate-may-2026.2026-06-27T12-57-12Z.japan-unemployment-rate-may-2026-thesis-analyst-fast-2026-06-27t12-57-12z.e37f19c9ee504438","predictionId":"japan-unemployment-rate-may-2026","specId":"spec.japan-unemployment-rate-may-2026","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 3 historical point(s) and explicit outside-view language.","evidence":["Base-rate/reference-class anchor: before using the April movement as inside-view evidence, the official-source reference class points to a low-volatility unemployment-rate range around 2.5 to 2.7 percent. The 2024 and 2025 annual rates were both 2.5 percent, so the outside-view prior is 2.5 percent with a short-run range centered near 2.6 percent.","Model prior: I use a persistence-plus-short-moving-average prior rather than a formal time-series model because the forecast target is one month ahead and the official published value is rounded to one decimal point. Persistence from April gets the largest weight, with the Jan-Apr average and annual level as shrinkage anchors."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The resolver is the Statistics Bureau of Japan Labour Force Survey Basic Tabulation complete unemployment rate, seasonally adjusted, for May 2026, taken from the first official monthly release and rounded as the agency publishes it to one decimal percentage point.","Tool call: Opened the official 2026 Labour Force Survey release schedule PDF."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast Japan May 2026 first-print unemployment rate","The resolver is the Statistics Bureau of Japan Labour Force Survey Basic Tabulation complete unemployment rate, seasonally adjusted, for May 2026, taken from the first official monthly release and rounded as the agency publishes it to one decimal percentage point."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.5, distribution present, forecast step count 1.","evidence":["Tool call: Read the latest official PDF summary for labor-market level and momentum details.","Counter-consideration: April's 0.2 point drop could partially reverse if labor-force participation rose or if the unemployed count continued its year-over-year increase; an upside print of 2.7 to 2.8 percent is plausible. The downside scenario is continued strong employment absorption pushing the rounded rate to 2.3 or 2.4 percent. Outside the interval would likely require an unusually sharp one-month labor-force or employment shock."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Model prior: I use a persistence-plus-short-moving-average prior rather than a formal time-series model because the forecast target is one month ahead and the official published value is rounded to one decimal point. Persistence from April gets the largest weight, with the Jan-Apr average and annual level as shrinkage anchors.","Tool call: Read the latest official PDF summary for labor-market level and momentum details."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, and one-off effects: the latest 2.5 percent level is already at the two-year annual average. The month-to-month momentum is downward from March to April, but the year-over-year unemployed count is still positive, which argues against a confident break below 2.5 percent. No policy-mechanism or calendar event points to a large May discontinuity.","Point calculation: use a judgmental persistence-weighted blend, 70% on April 2.5, 20% on the 2026 Jan-Apr average of (2.7+2.6+2.7+2.5)/4 = 2.625, and 10% on the 2024-2025 annual anchor of 2.5, giving 0.70*2.5 + 0.20*2.625 + 0.10*2.5 = 2.525. Because the April fall and annual anchor both favor 2.5 while the short average favors only a small upward pull, I set the judgmental published point estimate at 2.5 rather than mechanically rounding 2.525 up. The 80% interval starts from the Jan-Apr rounded range of 2.5-2.7 and is widened judgmentally to 2.3-2.8 for one-month release noise and rounded-value uncertainty."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast Japan May 2026 first-print unemployment rate","The resolver is the Statistics Bureau of Japan Labour Force Survey Basic Tabulation complete unemployment rate, seasonally adjusted, for May 2026, taken from the first official monthly release and rounded as the agency publishes it to one decimal percentage point."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: japan-unemployment-rate-may-2026\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-06-30\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-ppi-final-demand-mom-may-2026.2026-06-06T23-38-51-02-00.fa146519f2c68c9f","runId":"run.us-ppi-final-demand-mom-may-2026.2026-06-06T23-38-51-02-00.fa146519f2c68c9f","predictionId":"us-ppi-final-demand-mom-may-2026","specId":"spec.us-ppi-final-demand-mom-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.22,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 8 source-context item(s), activity log absent.","evidence":["PPI is a timely input to goods, services, and trade-margin inflation and helps explain the producer side of later PCE price estimates. This target resolves on 2026-06-11 under a first-print rule, with an expected 5 days lag. The same series can also spawn next release, +3 months, PCE pass-through questions.","Tool call: bls.lookup({ release: \"PPI\", series: \"final_demand, SA\", months: [\"2026-02\", \"2026-04\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","PPI is a timely input to goods, services, and trade-margin inflation and helps explain the producer side of later PCE price estimates. This target resolves on 2026-06-11 under a first-print rule, with an expected 5 days lag. The same series can also spawn next release, +3 months, PCE pass-through questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.5, distribution present, forecast step count 1.","evidence":["April's 1.4% final-demand jump was unusually broad, with goods, energy, and trade margins all elevated. The forecast assumes partial mean reversion but keeps a wide interval because PPI energy and trade-margin components are highly volatile.","Forecast: point 0.5, 80% interval [-0.2, 1.3]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["April's 1.4% final-demand jump was unusually broad, with goods, energy, and trade margins all elevated. The forecast assumes partial mean reversion but keeps a wide interval because PPI energy and trade-margin components are highly volatile."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["April's 1.4% final-demand jump was unusually broad, with goods, energy, and trade margins all elevated. The forecast assumes partial mean reversion but keeps a wide interval because PPI energy and trade-margin components are highly volatile."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["April's 1.4% final-demand jump was unusually broad, with goods, energy, and trade margins all elevated. The forecast assumes partial mean reversion but keeps a wide interval because PPI energy and trade-margin components are highly volatile.","Forecast: point 0.5, 80% interval [-0.2, 1.3]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-ppi-final-demand-mom-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-11\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-industrial-production-mom-may-2026.2026-06-06T23-38-51-02-00.8ff89b7696efc334","runId":"run.us-industrial-production-mom-may-2026.2026-06-06T23-38-51-02-00.8ff89b7696efc334","predictionId":"us-industrial-production-mom-may-2026","specId":"spec.us-industrial-production-mom-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.46,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 8 source-context item(s), activity log absent.","evidence":["Industrial production is the fastest official read on goods-sector output, manufacturing capacity pressure, and recession-sensitive activity outside services. This target resolves on 2026-06-15 under a first-print rule, with an expected 8 days lag. The same series can also spawn next release, +3 months, manufacturing split questions."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Industrial production is the fastest official read on goods-sector output, manufacturing capacity pressure, and recession-sensitive activity outside services. This target resolves on 2026-06-15 under a first-print rule, with an expected 8 days lag. The same series can also spawn next release, +3 months, manufacturing split questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.4, distribution present, forecast step count 1.","evidence":["April's 0.7% gain was helped by manufacturing, motor vehicles, and utilities. The May forecast fades the utilities impulse and keeps the center modestly positive because manufacturing excluding vehicles still grew in April, while mining and survey data keep a meaningful downside tail.","Forecast: point 0.2, 80% interval [-0.5, 0.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Industrial production is the fastest official read on goods-sector output, manufacturing capacity pressure, and recession-sensitive activity outside services. This target resolves on 2026-06-15 under a first-print rule, with an expected 8 days lag. The same series can also spawn next release, +3 months, manufacturing split questions.","April's 0.7% gain was helped by manufacturing, motor vehicles, and utilities. The May forecast fades the utilities impulse and keeps the center modestly positive because manufacturing excluding vehicles still grew in April, while mining and survey data keep a meaningful downside tail."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["April's 0.7% gain was helped by manufacturing, motor vehicles, and utilities. The May forecast fades the utilities impulse and keeps the center modestly positive because manufacturing excluding vehicles still grew in April, while mining and survey data keep a meaningful downside tail.","Forecast: point 0.2, 80% interval [-0.5, 0.9]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-industrial-production-mom-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-capacity-utilization-may-2026.2026-06-06T23-38-51-02-00.3011388d9eea4524","runId":"run.us-capacity-utilization-may-2026.2026-06-06T23-38-51-02-00.3011388d9eea4524","predictionId":"us-capacity-utilization-may-2026","specId":"spec.us-capacity-utilization-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.22,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 8 source-context item(s), activity log absent.","evidence":["Capacity utilization measures how much productive slack remains in goods-producing sectors, connecting output pressure to inflation, investment, and labor demand. This target resolves on 2026-06-15 under a first-print rule, with an expected 8 days lag. The same series can also spawn next release, +3 months, manufacturing split questions."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Capacity utilization measures how much productive slack remains in goods-producing sectors, connecting output pressure to inflation, investment, and labor demand. This target resolves on 2026-06-15 under a first-print rule, with an expected 8 days lag. The same series can also spawn next release, +3 months, manufacturing split questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.3, distribution present, forecast step count 1.","evidence":["April utilization was 76.1194%, rounded to 76.1% in the release, after total industrial production rose 0.7%. Two independent agent estimates centered at 76.2% and 76.3%; the catalog records the rounded ensemble center of 76.3% while keeping a lower tail for weather-sensitive utilities, vehicles, and mining volatility.","Forecast: point 76.3, 80% interval [75.6, 76.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Capacity utilization measures how much productive slack remains in goods-producing sectors, connecting output pressure to inflation, investment, and labor demand. This target resolves on 2026-06-15 under a first-print rule, with an expected 8 days lag. The same series can also spawn next release, +3 months, manufacturing split questions."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: agent.ensemble({ task: \"forecast May 2026 total capacity utilization\", independent_agents: 2 })","Tool result: { agent_1_point: 76.2, agent_1_p10: 75.5, agent_1_p50: 76.2, agent_1_p90: 76.9, agent_2_point: 76.3, agent_2_p10: 75.7, agent_2_p50: 76.3, agent_2_p90: 76.8, ensemble_point: 76.3 }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-capacity-utilization-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-15\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-import-price-index-mom-may-2026.2026-06-06T23-38-51-02-00.01f65c25fe12a532","runId":"run.us-import-price-index-mom-may-2026.2026-06-06T23-38-51-02-00.01f65c25fe12a532","predictionId":"us-import-price-index-mom-may-2026","specId":"spec.us-import-price-index-mom-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 8 source-context item(s), activity log absent.","evidence":["Import prices are an early official signal for tradable-goods inflation, tariff pass-through, and foreign-price pressure before CPI and PCE fully absorb it. This target resolves on 2026-06-16 under a first-print rule, with an expected 9 days lag. The same series can also spawn next release, +3 months, nonfuel split questions.","Tool call: bls.lookup({ release: \"Import and Export Price Indexes\", series: \"all_imports_mom\", months: [\"2026-01\", \"2026-04\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Import prices are an early official signal for tradable-goods inflation, tariff pass-through, and foreign-price pressure before CPI and PCE fully absorb it. This target resolves on 2026-06-16 under a first-print rule, with an expected 9 days lag. The same series can also spawn next release, +3 months, nonfuel split questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.8, distribution present, forecast step count 1.","evidence":["Forecast: point 0.6, 80% interval [-0.3, 1.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Import prices are an early official signal for tradable-goods inflation, tariff pass-through, and foreign-price pressure before CPI and PCE fully absorb it. This target resolves on 2026-06-16 under a first-print rule, with an expected 9 days lag. The same series can also spawn next release, +3 months, nonfuel split questions.","April's all-import price increase was fuel-led and unusually hot. The forecast assumes some fuel-price mean reversion but keeps a positive center because nonfuel import prices were also firm and the latest three-month sequence points to broad imported inflation pressure."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["April's all-import price increase was fuel-led and unusually hot. The forecast assumes some fuel-price mean reversion but keeps a positive center because nonfuel import prices were also firm and the latest three-month sequence points to broad imported inflation pressure."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["April's all-import price increase was fuel-led and unusually hot. The forecast assumes some fuel-price mean reversion but keeps a positive center because nonfuel import prices were also firm and the latest three-month sequence points to broad imported inflation pressure.","Forecast: point 0.6, 80% interval [-0.3, 1.5]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-import-price-index-mom-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-16\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-housing-starts-may-2026.2026-06-06T23-38-51-02-00.5c86937883be2ced","runId":"run.us-housing-starts-may-2026.2026-06-06T23-38-51-02-00.5c86937883be2ced","predictionId":"us-housing-starts-may-2026","specId":"spec.us-housing-starts-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 8 source-context item(s), activity log absent.","evidence":["Housing starts are a fast official read on construction, rates-sensitive investment, and future shelter supply. This target resolves on 2026-06-16 under a first-print rule, with an expected 10 days lag. The same series can also spawn next release, +3 months, single-family split questions.","Tool call: census.lookup({ release: \"New Residential Construction\", series: \"housing_starts_saar\", months: [\"2026-01\", \"2026-04\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Housing starts are a fast official read on construction, rates-sensitive investment, and future shelter supply. This target resolves on 2026-06-16 under a first-print rule, with an expected 10 days lag. The same series can also spawn next release, +3 months, single-family split questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.4, distribution present, forecast step count 1.","evidence":["Forecast: point 1.42, 80% interval [1.22, 1.62]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Starts fell modestly in April while permits rose, giving mixed short-run signals. The forecast centers slightly below April because mortgage-rate pressure and single-family softness outweigh the permit rebound, but survey noise keeps the band wide."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Starts fell modestly in April while permits rose, giving mixed short-run signals. The forecast centers slightly below April because mortgage-rate pressure and single-family softness outweigh the permit rebound, but survey noise keeps the band wide."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Starts fell modestly in April while permits rose, giving mixed short-run signals. The forecast centers slightly below April because mortgage-rate pressure and single-family softness outweigh the permit rebound, but survey noise keeps the band wide.","Forecast: point 1.42, 80% interval [1.22, 1.62]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-housing-starts-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-16\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-total-business-inventories-april-2026.2026-06-06T23-38-51-02-00.3cdee8e0afcb01c9","runId":"run.us-total-business-inventories-april-2026.2026-06-06T23-38-51-02-00.3cdee8e0afcb01c9","predictionId":"us-total-business-inventories-april-2026","specId":"spec.us-total-business-inventories-april-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.22,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 8 source-context item(s), activity log absent.","evidence":["Business inventories connect goods demand, supply-chain buffers, nominal GDP source data, and inventory-cycle pressure on production. This target resolves on 2026-06-17 under a first-print rule, with an expected 11 days lag. The same series can also spawn next release, +3 months, inventory-sales ratio questions.","Tool call: census.lookup({ release: \"Manufacturing and Trade Inventories and Sales\", series: \"total_business_inventories_level\", months: [\"2026-02\", \"2026-03\"], component_inputs: [\"M3 manufacturing\", \"Advance wholesale\", \"Advance retail\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Business inventories connect goods demand, supply-chain buffers, nominal GDP source data, and inventory-cycle pressure on production. This target resolves on 2026-06-17 under a first-print rule, with an expected 11 days lag. The same series can also spawn next release, +3 months, inventory-sales ratio questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 16, distribution present, forecast step count 1.","evidence":["Tool call: census.lookup({ release: \"Manufacturing and Trade Inventories and Sales\", series: \"total_business_inventories_level\", months: [\"2026-02\", \"2026-03\"], component_inputs: [\"M3 manufacturing\", \"Advance wholesale\", \"Advance retail\"] })","Tool result: { feb_level_billions: 2686.3, mar_level_billions: 2709.7, mar_inventory_sales_ratio: 1.32, apr_m3_manufacturing_inventories_billions: 959.125, apr_advance_wholesale_inventories_billions: 938.640, apr_advance_retail_inventories_billions: 827.304, apr_release: '2026-06-17 10:00 ET' }"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Business inventories connect goods demand, supply-chain buffers, nominal GDP source data, and inventory-cycle pressure on production. This target resolves on 2026-06-17 under a first-print rule, with an expected 11 days lag. The same series can also spawn next release, +3 months, inventory-sales ratio questions."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The available April component inputs imply a mechanical total near $2,725.1 billion: manufacturing inventories at $959.1 billion, advance wholesale inventories at $938.6 billion, and advance retail inventories at $827.3 billion. The interval mainly allows for wholesale and retail revisions before the MTIS first print.","Forecast: point 2725, 80% interval [2716.5, 2732.5]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-total-business-inventories-april-2026\nrunLabel: Headline\nresolutionDate: 2026-06-17\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-government-social-benefits-may-2026.2026-06-06T23-38-51-02-00.87c8d26875111e13","runId":"run.us-government-social-benefits-may-2026.2026-06-06T23-38-51-02-00.87c8d26875111e13","predictionId":"us-government-social-benefits-may-2026","specId":"spec.us-government-social-benefits-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 8 source-context item(s), activity log absent.","evidence":["Government social benefits are the official monthly income-account counterpart to major transfer programs, making them a direct calibration target for benefit and poverty simulations. This target resolves on 2026-06-25 under a first-print rule, with an expected 19 days lag. The same series can also spawn next release, +3 months, Medicaid split questions.","Tool call: bea.lookup({ dataset: \"NIPA Table 2.6\", series: \"A063RC government social benefits to persons\", months: [\"2026-01\", \"2026-04\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Government social benefits are the official monthly income-account counterpart to major transfer programs, making them a direct calibration target for benefit and poverty simulations. This target resolves on 2026-06-25 under a first-print rule, with an expected 19 days lag. The same series can also spawn next release, +3 months, Medicaid split questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 90, distribution present, forecast step count 1.","evidence":["The series has hovered just below $5.0 trillion SAAR since February, with April at $4,984.8 billion after a small increase from March. The estimate follows the independent benefits-target agent's $4,997 billion center because Social Security and health-program payments continue to trend upward, while the interval allows for payment-timing noise in Medicare, Medicaid, unemployment insurance, and other benefits.","Forecast: point 4997, 80% interval [4955, 5045]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The series has hovered just below $5.0 trillion SAAR since February, with April at $4,984.8 billion after a small increase from March. The estimate follows the independent benefits-target agent's $4,997 billion center because Social Security and health-program payments continue to trend upward, while the interval allows for payment-timing noise in Medicare, Medicaid, unemployment insurance, and other benefits."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The series has hovered just below $5.0 trillion SAAR since February, with April at $4,984.8 billion after a small increase from March. The estimate follows the independent benefits-target agent's $4,997 billion center because Social Security and health-program payments continue to trend upward, while the interval allows for payment-timing noise in Medicare, Medicaid, unemployment insurance, and other benefits.","Forecast: point 4997, 80% interval [4955, 5045]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-government-social-benefits-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-25\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-government-social-benefits-may-2026.2026-06-20T09-18-00-04-00.us-government-social-benefits-may-2026-brier-shadow-no-packs.69738dafadec96bc","runId":"run.us-government-social-benefits-may-2026.2026-06-20T09-18-00-04-00.us-government-social-benefits-may-2026-brier-shadow-no-packs.69738dafadec96bc","predictionId":"us-government-social-benefits-may-2026","specId":"spec.us-government-social-benefits-may-2026","runLabel":"Brier-1 - no packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 0 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 125, distribution present, forecast step count 1.","evidence":["Forecast: point 4990, 80% interval [4935, 5060]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 4990, 80% interval [4935, 5060]"]}],"flags":["weak_counterarguments","no_typed_tool_call"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-government-social-benefits-may-2026\nrunLabel: Brier-1 - no packs\nresolutionDate: 2026-06-25\ntraceLineCount: 3\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments, no_typed_tool_call."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-government-social-benefits-may-2026.2026-06-20T09-18-00-04-00.us-government-social-benefits-may-2026-brier-shadow-with-packs.c5963a98457751a3","runId":"run.us-government-social-benefits-may-2026.2026-06-20T09-18-00-04-00.us-government-social-benefits-may-2026-brier-shadow-with-packs.c5963a98457751a3","predictionId":"us-government-social-benefits-may-2026","specId":"spec.us-government-social-benefits-may-2026","runLabel":"Brier-1 - packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.08,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":["Tool call: brier.pack.apply({ target: \"bea.government_social_benefits.level.may_2026.first_print\", packs: [\"base-rate-first@0.1.0\", \"release-vintage-calibration@0.1.0\"] })","Tool result: { admitted: 2, mode: \"with_packs\", required_checks: [\"benefits_base_rate\",\"social_security_calendar\",\"medicare_medicaid_timing\",\"ui_claims_cross_check\"] }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: brier.pack.apply({ target: \"bea.government_social_benefits.level.may_2026.first_print\", packs: [\"base-rate-first@0.1.0\", \"release-vintage-calibration@0.1.0\"] })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 105, distribution present, forecast step count 1.","evidence":["The pack run decomposes total benefits by major program and keeps a modestly tighter interval because most components are monthly payment schedules.","Forecast: point 4998, 80% interval [4950, 5055]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The pack run decomposes total benefits by major program and keeps a modestly tighter interval because most components are monthly payment schedules."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The pack run decomposes total benefits by major program and keeps a modestly tighter interval because most components are monthly payment schedules.","Forecast: point 4998, 80% interval [4950, 5055]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-government-social-benefits-may-2026\nrunLabel: Brier-1 - packs\nresolutionDate: 2026-06-25\ntraceLineCount: 5\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-government-social-benefits-may-2026.2026-06-17T02-25-33Z.us-government-social-benefits-may-2026-thesis-analyst-fast-2026-06-17t02-25-33z.ce8485b32aeb491c","runId":"run.us-government-social-benefits-may-2026.2026-06-17T02-25-33Z.us-government-social-benefits-may-2026-thesis-analyst-fast-2026-06-17t02-25-33z.ce8485b32aeb491c","predictionId":"us-government-social-benefits-may-2026","specId":"spec.us-government-social-benefits-may-2026","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.54,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: Checked BEA April release PDF and historical-comparisons material for current monthly context.","Tool call: Checked BEA Table 2.6 historical comparison workbook for recent government social benefits levels."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Forecast BEA government social benefits to persons for May 2026","The resolver is the BEA first print for May 2026 in Personal Income and Outlays, specifically NIPA Table 2.6 government social benefits to persons, seasonally adjusted annual rate in billions of dollars."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is the BEA first print for May 2026 in Personal Income and Outlays, specifically NIPA Table 2.6 government social benefits to persons, seasonally adjusted annual rate in billions of dollars.","Tool call: Checked BEA release schedule for the May 2026 Personal Income and Outlays release."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 43, distribution present, forecast step count 1.","evidence":["Starting from the April first-print level of 4307.5, add a trend increment of about 7.5 billion: 4307.5 + 7.5 = 4315.0. Use an 80 percent interval of roughly -20.0/+23.0 around the point to cover ordinary monthly noise and first-print uncertainty, giving 4295.0 to 4338.0.","Forecast: point 4315, 80% interval [4295, 4338]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Starting from the April first-print level of 4307.5, add a trend increment of about 7.5 billion: 4307.5 + 7.5 = 4315.0. Use an 80 percent interval of roughly -20.0/+23.0 around the point to cover ordinary monthly noise and first-print uncertainty, giving 4295.0 to 4338.0."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast BEA government social benefits to persons for May 2026","Starting from the April first-print level of 4307.5, add a trend increment of about 7.5 billion: 4307.5 + 7.5 = 4315.0. Use an 80 percent interval of roughly -20.0/+23.0 around the point to cover ordinary monthly noise and first-print uncertainty, giving 4295.0 to 4338.0."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-government-social-benefits-may-2026\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-06-25\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-social-security-benefits-may-2026.2026-06-06T23-38-51-02-00.4e7a1e6173be29c9","runId":"run.us-social-security-benefits-may-2026.2026-06-06T23-38-51-02-00.4e7a1e6173be29c9","predictionId":"us-social-security-benefits-may-2026","specId":"spec.us-social-security-benefits-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 8 source-context item(s), activity log absent.","evidence":["Social Security is the largest cash-transfer component in personal income, so it anchors retirement-income, poverty, and fiscal calibration forecasts. This target resolves on 2026-06-25 under a first-print rule, with an expected 19 days lag. The same series can also spawn next release, +3 months, aggregate benefits questions.","Tool result: { jan_billions_saar: 1623.2, feb_billions_saar: 1628.6, mar_billions_saar: 1636.9, apr_billions_saar: 1643.7, may_release: '2026-06-25 08:30 ET' }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Social Security is the largest cash-transfer component in personal income, so it anchors retirement-income, poverty, and fiscal calibration forecasts. This target resolves on 2026-06-25 under a first-print rule, with an expected 19 days lag. The same series can also spawn next release, +3 months, aggregate benefits questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 24, distribution present, forecast step count 1.","evidence":["The line has risen every month in 2026, from $1,623.2 billion SAAR in January to $1,643.7 billion in April. The forecast extends that smooth trend to $1,650 billion, with a narrow interval because Social Security benefit flows are large, regular, and less volatile than health-program payment timing.","Forecast: point 1650, 80% interval [1638, 1662]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The line has risen every month in 2026, from $1,623.2 billion SAAR in January to $1,643.7 billion in April. The forecast extends that smooth trend to $1,650 billion, with a narrow interval because Social Security benefit flows are large, regular, and less volatile than health-program payment timing."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Social Security is the largest cash-transfer component in personal income, so it anchors retirement-income, poverty, and fiscal calibration forecasts. This target resolves on 2026-06-25 under a first-print rule, with an expected 19 days lag. The same series can also spawn next release, +3 months, aggregate benefits questions.","The line has risen every month in 2026, from $1,623.2 billion SAAR in January to $1,643.7 billion in April. The forecast extends that smooth trend to $1,650 billion, with a narrow interval because Social Security benefit flows are large, regular, and less volatile than health-program payment timing."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-social-security-benefits-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-25\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-social-security-benefits-may-2026.2026-06-20T09-26-00-04-00.us-social-security-benefits-may-2026-brier-shadow-no-packs.1f4337ea0b1ac273","runId":"run.us-social-security-benefits-may-2026.2026-06-20T09-26-00-04-00.us-social-security-benefits-may-2026-brier-shadow-no-packs.1f4337ea0b1ac273","predictionId":"us-social-security-benefits-may-2026","specId":"spec.us-social-security-benefits-may-2026","runLabel":"Brier-1 - no packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and explicit outside-view language.","evidence":["The control run extrapolates Social Security benefits from recent levels and a broad beneficiary-growth prior."]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 0 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 36, distribution present, forecast step count 1.","evidence":["Forecast: point 1650, 80% interval [1632, 1668]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 1650, 80% interval [1632, 1668]"]}],"flags":["weak_counterarguments","no_typed_tool_call"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-social-security-benefits-may-2026\nrunLabel: Brier-1 - no packs\nresolutionDate: 2026-06-25\ntraceLineCount: 3\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments, no_typed_tool_call."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-social-security-benefits-may-2026.2026-06-20T09-26-00-04-00.us-social-security-benefits-may-2026-brier-shadow-with-packs.d7fc803aafb5598d","runId":"run.us-social-security-benefits-may-2026.2026-06-20T09-26-00-04-00.us-social-security-benefits-may-2026-brier-shadow-with-packs.d7fc803aafb5598d","predictionId":"us-social-security-benefits-may-2026","specId":"spec.us-social-security-benefits-may-2026","runLabel":"Brier-1 - packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.08,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":["Tool call: brier.pack.apply({ target: \"bea.government_social_benefits.social_security.may_2026.first_print\", packs: [\"base-rate-first@0.1.0\", \"release-vintage-calibration@0.1.0\"] })","Tool result: { admitted: 2, mode: \"with_packs\", required_checks: [\"social_security_base_rate\",\"beneficiary_count\",\"cola_embedded\",\"payment_calendar\"] }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: brier.pack.apply({ target: \"bea.government_social_benefits.social_security.may_2026.first_print\", packs: [\"base-rate-first@0.1.0\", \"release-vintage-calibration@0.1.0\"] })","The pack run tightens the interval because the COLA and payment calendar are mostly known before the BEA release."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 23, distribution present, forecast step count 1.","evidence":["The pack run tightens the interval because the COLA and payment calendar are mostly known before the BEA release.","Forecast: point 1651, 80% interval [1640, 1663]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The pack run tightens the interval because the COLA and payment calendar are mostly known before the BEA release."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The pack run tightens the interval because the COLA and payment calendar are mostly known before the BEA release.","Forecast: point 1651, 80% interval [1640, 1663]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-social-security-benefits-may-2026\nrunLabel: Brier-1 - packs\nresolutionDate: 2026-06-25\ntraceLineCount: 5\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-social-security-benefits-may-2026.2026-06-17T02-28-12Z.us-social-security-benefits-may-2026-thesis-analyst-fast-2026-06-17t02-28-12z.cf96b21cc17d8b49","runId":"run.us-social-security-benefits-may-2026.2026-06-17T02-28-12Z.us-social-security-benefits-may-2026-thesis-analyst-fast-2026-06-17t02-28-12z.cf96b21cc17d8b49","predictionId":"us-social-security-benefits-may-2026","specId":"spec.us-social-security-benefits-may-2026","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":["Base-rate/reference-class: outside one-time administrative jumps, this series usually moves gradually month to month; recent ordinary May changes include 2023 Apr-May +3.5 and 2024 Apr-May +2.1, while 2025 Apr-May -122.6 was an exceptional unwind from spring volatility."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The target is BEA's first-print May 2026 value for Personal current transfer receipts: Government social benefits to persons: Social security, reported in billions of dollars at a seasonally adjusted annual rate.","Tool call: Checked FRED's BEA-sourced W823RC1 series page for latest observations and metadata."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The target is BEA's first-print May 2026 value for Personal current transfer receipts: Government social benefits to persons: Social security, reported in billions of dollars at a seasonally adjusted annual rate.","Tool call: Checked the BEA release schedule for Personal Income and Outlays, May 2026."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 25, distribution present, forecast step count 1.","evidence":["Recent 2026 monthly changes were +5.4 from January to February, +8.3 from February to March, and +6.8 from March to April, averaging about +6.8. Applying +6.8 to Apr 2026 value 1643.7 gives 1650.5. I use an 80% interval of 1638.0 to 1663.0, wide enough for normal first-print noise and smaller administrative timing shifts.","Forecast: point 1650.5, 80% interval [1638, 1663]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Counter-consideration: 2025 showed unusually large Social Security volatility around March to May, so a pure smooth-trend forecast could be too narrow if BEA records another timing or retroactive-payment effect. I still center on smooth growth because 2026 through April shows no comparable spike."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast BEA May 2026 Social Security Benefits","Recent 2026 monthly changes were +5.4 from January to February, +8.3 from February to March, and +6.8 from March to April, averaging about +6.8. Applying +6.8 to Apr 2026 value 1643.7 gives 1650.5. I use an 80% interval of 1638.0 to 1663.0, wide enough for normal first-print noise and smaller administrative timing shifts."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-social-security-benefits-may-2026\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-06-25\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-medicare-benefits-may-2026.2026-06-06T23-38-51-02-00.a4e2e7c259e06a10","runId":"run.us-medicare-benefits-may-2026.2026-06-06T23-38-51-02-00.a4e2e7c259e06a10","predictionId":"us-medicare-benefits-may-2026","specId":"spec.us-medicare-benefits-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 8 source-context item(s), activity log absent.","evidence":["Medicare benefit flows are a major public-transfer and health-spending calibration target, connecting beneficiary mix and payment rules to household income accounts. This target resolves on 2026-06-25 under a first-print rule, with an expected 19 days lag. The same series can also spawn next release, +3 months, aggregate benefits questions.","Tool result: { jan_billions_saar: 1290.6, feb_billions_saar: 1301.0, mar_billions_saar: 1311.4, apr_billions_saar: 1321.7, may_release: '2026-06-25 08:30 ET' }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Medicare benefit flows are a major public-transfer and health-spending calibration target, connecting beneficiary mix and payment rules to household income accounts. This target resolves on 2026-06-25 under a first-print rule, with an expected 19 days lag. The same series can also spawn next release, +3 months, aggregate benefits questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 28, distribution present, forecast step count 1.","evidence":["Forecast: point 1332, 80% interval [1318, 1346]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Medicare has advanced by roughly $10 billion SAAR each month in 2026, ending April at $1,321.7 billion. The forecast extends that trend to $1,332 billion while allowing a wider band than Social Security because health-program claims and plan payments are more timing-sensitive."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Medicare has advanced by roughly $10 billion SAAR each month in 2026, ending April at $1,321.7 billion. The forecast extends that trend to $1,332 billion while allowing a wider band than Social Security because health-program claims and plan payments are more timing-sensitive.","Forecast: point 1332, 80% interval [1318, 1346]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-medicare-benefits-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-25\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-medicare-benefits-may-2026.2026-06-20T09-22-00-04-00.us-medicare-benefits-may-2026-brier-shadow-no-packs.7ad3492c262cd5f9","runId":"run.us-medicare-benefits-may-2026.2026-06-20T09-22-00-04-00.us-medicare-benefits-may-2026-brier-shadow-no-packs.7ad3492c262cd5f9","predictionId":"us-medicare-benefits-may-2026","specId":"spec.us-medicare-benefits-may-2026","runLabel":"Brier-1 - no packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 0 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 36, distribution present, forecast step count 1.","evidence":["Forecast: point 1330, 80% interval [1312, 1348]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 1330, 80% interval [1312, 1348]"]}],"flags":["weak_counterarguments","no_typed_tool_call"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-medicare-benefits-may-2026\nrunLabel: Brier-1 - no packs\nresolutionDate: 2026-06-25\ntraceLineCount: 3\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments, no_typed_tool_call."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-medicare-benefits-may-2026.2026-06-20T09-22-00-04-00.us-medicare-benefits-may-2026-brier-shadow-with-packs.c9477e6f59376fda","runId":"run.us-medicare-benefits-may-2026.2026-06-20T09-22-00-04-00.us-medicare-benefits-may-2026-brier-shadow-with-packs.c9477e6f59376fda","predictionId":"us-medicare-benefits-may-2026","specId":"spec.us-medicare-benefits-may-2026","runLabel":"Brier-1 - packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.19,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":["Tool call: brier.pack.apply({ target: \"bea.government_social_benefits.medicare.may_2026.first_print\", packs: [\"base-rate-first@0.1.0\", \"release-vintage-calibration@0.1.0\"] })","Tool result: { admitted: 2, mode: \"with_packs\", required_checks: [\"medicare_base_rate\",\"payment_calendar\",\"ma_payment_timing\",\"bea_release_noise\"] }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: brier.pack.apply({ target: \"bea.government_social_benefits.medicare.may_2026.first_print\", packs: [\"base-rate-first@0.1.0\", \"release-vintage-calibration@0.1.0\"] })","Tool result: { admitted: 2, mode: \"with_packs\", required_checks: [\"medicare_base_rate\",\"payment_calendar\",\"ma_payment_timing\",\"bea_release_noise\"] }"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 24, distribution present, forecast step count 1.","evidence":["The pack run keeps the center near the control but narrows the interval because Medicare payment schedules are less noisy than aggregate benefits.","Forecast: point 1332, 80% interval [1320, 1344]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The pack run keeps the center near the control but narrows the interval because Medicare payment schedules are less noisy than aggregate benefits."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The pack run keeps the center near the control but narrows the interval because Medicare payment schedules are less noisy than aggregate benefits."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The pack run keeps the center near the control but narrows the interval because Medicare payment schedules are less noisy than aggregate benefits.","Forecast: point 1332, 80% interval [1320, 1344]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-medicare-benefits-may-2026\nrunLabel: Brier-1 - packs\nresolutionDate: 2026-06-25\ntraceLineCount: 5\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-medicare-benefits-may-2026.2026-06-17T02-30-40Z.us-medicare-benefits-may-2026-thesis-analyst-fast-2026-06-17t02-30-40z.db67f245ae2e03b6","runId":"run.us-medicare-benefits-may-2026.2026-06-17T02-30-40Z.us-medicare-benefits-may-2026-thesis-analyst-fast-2026-06-17t02-30-40z.db67f245ae2e03b6","predictionId":"us-medicare-benefits-may-2026","specId":"spec.us-medicare-benefits-may-2026","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and explicit outside-view language.","evidence":["Reference-class/base-rate: this administered-benefit line has recently moved in very smooth monthly steps. The last four month-to-month changes are +10.5, +10.4, +10.4, and +10.3 billion, so a one-month extrapolation is a strong baseline."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The resolver is the first BEA Personal Income and Outlays release value for May 2026 Medicare government social benefits in NIPA Table 2.6, reported as seasonally adjusted annual-rate billions of dollars.","Tool result: FRED/BEA W824RC1 shows Apr 2026 1321.7, Mar 2026 1311.4, Feb 2026 1301.0, Jan 2026 1290.6, Dec 2025 1280.1; units are billions of dollars, seasonally adjusted annual rate, monthly, updated May 28, 2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is the first BEA Personal Income and Outlays release value for May 2026 Medicare government social benefits in NIPA Table 2.6, reported as seasonally adjusted annual-rate billions of dollars.","Tool call: Checked BEA release schedule for Personal Income and Outlays, May 2026."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 12, distribution present, forecast step count 1.","evidence":["Using the recent monthly increments, average change from Dec 2025 to Apr 2026 is (1321.7 - 1280.1) / 4 = 10.4. Point forecast = 1321.7 + 10.3 rounded to one decimal = 1332.0. I use an 80% interval of +/-6.0 around the point to allow first-print source-data noise and possible BEA monthly allocation changes.","Forecast: point 1332, 80% interval [1326, 1338]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Counter-consideration: the run-up could deviate if BEA incorporates updated Medicare administrative source data or seasonal factors in the May first print; however, the recent level path and annual-rate reporting make a sharp break less likely than another near-10-billion step."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast BEA Medicare government social benefits for May 2026","Using the recent monthly increments, average change from Dec 2025 to Apr 2026 is (1321.7 - 1280.1) / 4 = 10.4. Point forecast = 1321.7 + 10.3 rounded to one decimal = 1332.0. I use an 80% interval of +/-6.0 around the point to allow first-print source-data noise and possible BEA monthly allocation changes."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-medicare-benefits-may-2026\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-06-25\ntraceLineCount: 12\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-medicaid-benefits-may-2026.2026-06-06T23-38-51-02-00.75d73aadc6fe4414","runId":"run.us-medicaid-benefits-may-2026.2026-06-06T23-38-51-02-00.75d73aadc6fe4414","predictionId":"us-medicaid-benefits-may-2026","specId":"spec.us-medicaid-benefits-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 8 source-context item(s), activity log absent.","evidence":["Medicaid is the cleanest near-term BEA bridge from public benefit rules and enrollment operations into official household income accounts. This target resolves on 2026-06-25 under a first-print rule, with an expected 19 days lag. The same series can also spawn next release, +3 months, aggregate benefits questions.","Tool result: { jan_billions_saar: 1050.4, feb_billions_saar: 1049.6, mar_billions_saar: 1045.8, apr_billions_saar: 1039.0, may_release: '2026-06-25 08:30 ET' }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Medicaid is the cleanest near-term BEA bridge from public benefit rules and enrollment operations into official household income accounts. This target resolves on 2026-06-25 under a first-print rule, with an expected 19 days lag. The same series can also spawn next release, +3 months, aggregate benefits questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 28, distribution present, forecast step count 1.","evidence":["Medicaid benefits declined from $1,050.4 billion SAAR in January to $1,039.0 billion in April, consistent with continued post-unwinding normalization and payment-timing noise. Two independent agents centered May at $1,039.5 billion and $1,042.0 billion; the catalog records the rounded ensemble center of $1,041 billion with a combined $1,029-$1,057 billion 80% interval.","Forecast: point 1041, 80% interval [1029, 1057]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: agent.ensemble({ task: \"forecast May 2026 BEA Medicaid benefits\", independent_agents: 2 })","Tool result: { agent_1_point: 1039.5, agent_1_p10: 1029.0, agent_1_p25: 1034.0, agent_1_p50: 1039.5, agent_1_p75: 1045.0, agent_1_p90: 1053.0, agent_2_point: 1042.0, agent_2_p10: 1029.0, agent_2_p50: 1042.0, agent_2_p90: 1057.0, ensemble_point: 1041.0 }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-medicaid-benefits-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-25\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-medicaid-benefits-may-2026.2026-06-20T09-20-00-04-00.us-medicaid-benefits-may-2026-brier-shadow-no-packs.40bad49af49275cc","runId":"run.us-medicaid-benefits-may-2026.2026-06-20T09-20-00-04-00.us-medicaid-benefits-may-2026-brier-shadow-no-packs.40bad49af49275cc","predictionId":"us-medicaid-benefits-may-2026","specId":"spec.us-medicaid-benefits-may-2026","runLabel":"Brier-1 - no packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 0 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 40, distribution present, forecast step count 1.","evidence":["The control run extrapolates Medicaid benefits from recent levels with a generic managed-care timing interval.","Forecast: point 1038, 80% interval [1018, 1058]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The control run extrapolates Medicaid benefits from recent levels with a generic managed-care timing interval.","Forecast: point 1038, 80% interval [1018, 1058]"]}],"flags":["weak_counterarguments","no_typed_tool_call"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-medicaid-benefits-may-2026\nrunLabel: Brier-1 - no packs\nresolutionDate: 2026-06-25\ntraceLineCount: 3\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments, no_typed_tool_call."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-medicaid-benefits-may-2026.2026-06-20T09-20-00-04-00.us-medicaid-benefits-may-2026-brier-shadow-with-packs.735eb2bf91f9ec80","runId":"run.us-medicaid-benefits-may-2026.2026-06-20T09-20-00-04-00.us-medicaid-benefits-may-2026-brier-shadow-with-packs.735eb2bf91f9ec80","predictionId":"us-medicaid-benefits-may-2026","specId":"spec.us-medicaid-benefits-may-2026","runLabel":"Brier-1 - packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.05,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":["Tool call: brier.pack.apply({ target: \"bea.government_social_benefits.medicaid.may_2026.first_print\", packs: [\"base-rate-first@0.1.0\", \"release-vintage-calibration@0.1.0\"] })","Tool result: { admitted: 2, mode: \"with_packs\", required_checks: [\"medicaid_base_rate\",\"enrollment_trend\",\"managed_care_timing\",\"bea_release_noise\"] }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: brier.pack.apply({ target: \"bea.government_social_benefits.medicaid.may_2026.first_print\", packs: [\"base-rate-first@0.1.0\", \"release-vintage-calibration@0.1.0\"] })","Tool result: { admitted: 2, mode: \"with_packs\", required_checks: [\"medicaid_base_rate\",\"enrollment_trend\",\"managed_care_timing\",\"bea_release_noise\"] }"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 35, distribution present, forecast step count 1.","evidence":["The pack run lifts the center slightly for enrollment and payment timing while leaving the upper tail open for capitation volatility.","Forecast: point 1041, 80% interval [1025, 1060]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 1041, 80% interval [1025, 1060]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-medicaid-benefits-may-2026\nrunLabel: Brier-1 - packs\nresolutionDate: 2026-06-25\ntraceLineCount: 5\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-medicaid-benefits-may-2026.2026-06-17T02-31-13Z.us-medicaid-benefits-may-2026-thesis-analyst-fast-2026-06-17t02-31-13z.39ee018922fc2ff9","runId":"run.us-medicaid-benefits-may-2026.2026-06-17T02-31-13Z.us-medicaid-benefits-may-2026-thesis-analyst-fast-2026-06-17t02-31-13z.39ee018922fc2ff9","predictionId":"us-medicaid-benefits-may-2026","specId":"spec.us-medicaid-benefits-may-2026","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.22,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":["Base-rate/reference class: the latest four month-to-month moves are +5.4, -0.8, -3.8, and -6.8 billion SAAR, so a one-month forecast should mostly anchor on the latest level with a single-digit monthly move rather than extrapolate a large regime shift."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The resolver is the first BEA Personal Income and Outlays print for May 2026, specifically the monthly SAAR Medicaid component of government social benefits to persons, not any later revised NIPA vintage.","Tool call: Checked FRED mirror of BEA series W729RC1 for the latest Medicaid monthly SAAR observations."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast for BEA Medicaid government social benefits, May 2026 first print","The resolver is the first BEA Personal Income and Outlays print for May 2026, specifically the monthly SAAR Medicaid component of government social benefits to persons, not any later revised NIPA vintage."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 38, distribution present, forecast step count 1.","evidence":["Recent average monthly change from Dec 2025 to Apr 2026 is (1039.0 - 1045.0) / 4 = -1.5 billion. A slightly softer near-term adjustment from April gives 1039.0 - 1.5 = 1037.5. An 80% interval of roughly +/-19 billion around the point gives 1018.0 to 1056.0 after rounding to one decimal.","Forecast: point 1037.5, 80% interval [1018, 1056]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Counter-consideration: the April drop of 6.8 billion could mark continued post-enrollment or administrative-payment weakness, but January through February were nearly flat and this BEA component has enough smoothing that a further large May drop is less likely than a modest decline."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for BEA Medicaid government social benefits, May 2026 first print","Base-rate/reference class: the latest four month-to-month moves are +5.4, -0.8, -3.8, and -6.8 billion SAAR, so a one-month forecast should mostly anchor on the latest level with a single-digit monthly move rather than extrapolate a large regime shift."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-medicaid-benefits-may-2026\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-06-25\ntraceLineCount: 12\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-wages-and-salaries-may-2026.2026-06-06T23-38-51-02-00.56301f7913c70767","runId":"run.us-wages-and-salaries-may-2026.2026-06-06T23-38-51-02-00.56301f7913c70767","predictionId":"us-wages-and-salaries-may-2026","specId":"spec.us-wages-and-salaries-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.19,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 8 source-context item(s), activity log absent.","evidence":["Wages and salaries are the main labor-income bridge between payroll data, tax receipts, benefit eligibility, and household disposable-income forecasts. This target resolves on 2026-06-25 under a first-print rule, with an expected 19 days lag. The same series can also spawn next release, +3 months, tax receipts bridge questions.","Tool result: { jan_billions_saar: 13214.7, feb_billions_saar: 13231.5, mar_billions_saar: 13278.7, apr_billions_saar: 13311.1, may_release: '2026-06-25 08:30 ET' }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Wages and salaries are the main labor-income bridge between payroll data, tax receipts, benefit eligibility, and household disposable-income forecasts. This target resolves on 2026-06-25 under a first-print rule, with an expected 19 days lag. The same series can also spawn next release, +3 months, tax receipts bridge questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 105, distribution present, forecast step count 1.","evidence":["Forecast: point 13350, 80% interval [13300, 13405]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Wages and salaries are the main labor-income bridge between payroll data, tax receipts, benefit eligibility, and household disposable-income forecasts. This target resolves on 2026-06-25 under a first-print rule, with an expected 19 days lag. The same series can also spawn next release, +3 months, tax receipts bridge questions.","Wages and salaries rose steadily through April, and the resolved May payroll report showed 172,000 additional jobs with average hourly earnings up 0.3%. The forecast extends the recent trend to $13,350 billion SAAR while allowing downside from hours or composition and upside from stronger aggregate payroll income."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-wages-and-salaries-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-25\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-wages-and-salaries-may-2026.2026-06-20T09-28-00-04-00.us-wages-and-salaries-may-2026-brier-shadow-no-packs.58c215a2d5f18576","runId":"run.us-wages-and-salaries-may-2026.2026-06-20T09-28-00-04-00.us-wages-and-salaries-may-2026-brier-shadow-no-packs.58c215a2d5f18576","predictionId":"us-wages-and-salaries-may-2026","specId":"spec.us-wages-and-salaries-may-2026","runLabel":"Brier-1 - no packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 0 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 130, distribution present, forecast step count 1.","evidence":["Forecast: point 13345, 80% interval [13280, 13410]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 13345, 80% interval [13280, 13410]"]}],"flags":["weak_counterarguments","no_typed_tool_call"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-wages-and-salaries-may-2026\nrunLabel: Brier-1 - no packs\nresolutionDate: 2026-06-25\ntraceLineCount: 3\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments, no_typed_tool_call."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-wages-and-salaries-may-2026.2026-06-20T09-28-00-04-00.us-wages-and-salaries-may-2026-brier-shadow-with-packs.e8735f06ad784f28","runId":"run.us-wages-and-salaries-may-2026.2026-06-20T09-28-00-04-00.us-wages-and-salaries-may-2026-brier-shadow-with-packs.e8735f06ad784f28","predictionId":"us-wages-and-salaries-may-2026","specId":"spec.us-wages-and-salaries-may-2026","runLabel":"Brier-1 - packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.3,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":["Tool call: brier.pack.apply({ target: \"bea.wages_and_salaries.level.may_2026.first_print\", packs: [\"base-rate-first@0.1.0\", \"labor-market-momentum@0.1.0\", \"release-vintage-calibration@0.1.0\"] })","Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"wages_base_rate\",\"payroll_bridge\",\"hours_earnings\",\"bea_release_noise\"] }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: brier.pack.apply({ target: \"bea.wages_and_salaries.level.may_2026.first_print\", packs: [\"base-rate-first@0.1.0\", \"labor-market-momentum@0.1.0\", \"release-vintage-calibration@0.1.0\"] })","Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"wages_base_rate\",\"payroll_bridge\",\"hours_earnings\",\"bea_release_noise\"] }"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 95, distribution present, forecast step count 1.","evidence":["The pack run uses payrolls, earnings, and hours to lift the center modestly while preserving downside risk from source-data translation.","Forecast: point 13362, 80% interval [13315, 13410]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool call: brier.pack.apply({ target: \"bea.wages_and_salaries.level.may_2026.first_print\", packs: [\"base-rate-first@0.1.0\", \"labor-market-momentum@0.1.0\", \"release-vintage-calibration@0.1.0\"] })"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The pack run uses payrolls, earnings, and hours to lift the center modestly while preserving downside risk from source-data translation."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 13362, 80% interval [13315, 13410]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-wages-and-salaries-may-2026\nrunLabel: Brier-1 - packs\nresolutionDate: 2026-06-25\ntraceLineCount: 5\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-wages-and-salaries-may-2026.2026-06-17T02-32-16Z.us-wages-and-salaries-may-2026-thesis-analyst-fast-2026-06-17t02-32-16z.196d6bb575f0d44a","runId":"run.us-wages-and-salaries-may-2026.2026-06-17T02-32-16Z.us-wages-and-salaries-may-2026-thesis-analyst-fast-2026-06-17t02-32-16z.196d6bb575f0d44a","predictionId":"us-wages-and-salaries-may-2026","specId":"spec.us-wages-and-salaries-may-2026","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.41,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: Checked BEA's Personal Income page for the current prior release and release sequencing.","Base-rate/reference-class step: the recent BEA monthly sequence rose from 13,148.0 in Dec 2025 to 13,311.1 in Apr 2026, a four-month gain of 163.1, or about 40.8 billion dollars per month. The last three one-month changes were +16.8, +47.2, and +32.4 billion dollars."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["The target is the BEA monthly personal income account concept Wages and salaries, NIPA Table 2.6 line 3, for May 2026, measured in billions of current dollars at a seasonally adjusted annual rate. The resolver is the first official BEA print in the Personal Income and Outlays release, not a later revised vintage.","Tool result: FRED/BEA mirror shows A576RC1 Apr 2026 13,311.1, Mar 2026 13,278.7, Feb 2026 13,231.5, Jan 2026 13,214.7, and Dec 2025 13,148.0 billions of dollars SAAR."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast for BEA wages and salaries, May 2026 first print","The target is the BEA monthly personal income account concept Wages and salaries, NIPA Table 2.6 line 3, for May 2026, measured in billions of current dollars at a seasonally adjusted annual rate. The resolver is the first official BEA print in the Personal Income and Outlays release, not a later revised vintage."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 80, distribution present, forecast step count 1.","evidence":["A wage-bill proxy for May adds employment growth of about 172,000 divided by roughly 159 million payroll jobs, or about 0.11 percent, to 0.3 percent hourly earnings growth and 0.0 percent hours growth. Applying about 0.41 percent to 13,311.1 gives roughly 13,365.4. I round the point to 13,365.0 and set an 80 percent interval of 13,325.0 to 13,405.0, wider than recent monthly noise because BEA mapping and first-print source inputs can differ from CES payroll measures.","Forecast: point 13365, 80% interval [13325, 13405]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["A wage-bill proxy for May adds employment growth of about 172,000 divided by roughly 159 million payroll jobs, or about 0.11 percent, to 0.3 percent hourly earnings growth and 0.0 percent hours growth. Applying about 0.41 percent to 13,311.1 gives roughly 13,365.4. I round the point to 13,365.0 and set an 80 percent interval of 13,325.0 to 13,405.0, wider than recent monthly noise because BEA mapping and first-print source inputs can differ from CES payroll measures."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for BEA wages and salaries, May 2026 first print","A wage-bill proxy for May adds employment growth of about 172,000 divided by roughly 159 million payroll jobs, or about 0.11 percent, to 0.3 percent hourly earnings growth and 0.0 percent hours growth. Applying about 0.41 percent to 13,311.1 gives roughly 13,365.4. I round the point to 13,365.0 and set an 80 percent interval of 13,325.0 to 13,405.0, wider than recent monthly noise because BEA mapping and first-print source inputs can differ from CES payroll measures."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-wages-and-salaries-may-2026\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-06-25\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-personal-current-taxes-may-2026.2026-06-06T23-38-51-02-00.86ed22e0754757f2","runId":"run.us-personal-current-taxes-may-2026.2026-06-06T23-38-51-02-00.86ed22e0754757f2","predictionId":"us-personal-current-taxes-may-2026","specId":"spec.us-personal-current-taxes-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.08,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 8 source-context item(s), activity log absent.","evidence":["Personal current taxes are the official monthly household-tax line, connecting income growth and withholding to disposable-income and fiscal forecasts. This target resolves on 2026-06-25 under a first-print rule, with an expected 19 days lag. The same series can also spawn next release, +3 months, disposable-income bridge questions.","Tool result: { jan_billions_saar: 3214.2, feb_billions_saar: 3215.8, mar_billions_saar: 3230.4, apr_billions_saar: 3250.3, may_release: '2026-06-25 08:30 ET' }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Personal current taxes are the official monthly household-tax line, connecting income growth and withholding to disposable-income and fiscal forecasts. This target resolves on 2026-06-25 under a first-print rule, with an expected 19 days lag. The same series can also spawn next release, +3 months, disposable-income bridge questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 53.5, distribution present, forecast step count 1.","evidence":["Tool result: { completed_agents: 2, point_estimates_billions_saar: [3266.5, 3267.0], ensemble_point_billions_saar: 3266.8, ensemble_interval80_billions_saar: [3247.5, 3301], agent_quantiles: [{ p05: 3239, p10: 3248, p25: 3258.5, p50: 3266.5, p75: 3277, p90: 3292, p95: 3305 }, { p10: 3247, p25: 3257, p50: 3266, p75: 3284, p90: 3305 }] }","Two independent agents centered near $3,267 billion SAAR after comparing April's $3,250.3 billion first-print level with recent April-to-May tax increments, Jan-Apr year-over-year growth, and the resolved May payroll report. The ensemble keeps a wider right tail for withholding, refund, and nonwithheld-payment timing around the first BEA estimate."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Personal current taxes are the official monthly household-tax line, connecting income growth and withholding to disposable-income and fiscal forecasts. This target resolves on 2026-06-25 under a first-print rule, with an expected 19 days lag. The same series can also spawn next release, +3 months, disposable-income bridge questions.","Tool call: agent.ensemble({ task: \"forecast May 2026 BEA personal current taxes\", independent_agents: 2 })"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-personal-current-taxes-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-25\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-personal-current-taxes-may-2026.2026-06-20T09-24-00-04-00.us-personal-current-taxes-may-2026-brier-shadow-no-packs.659464a73f7283ad","runId":"run.us-personal-current-taxes-may-2026.2026-06-20T09-24-00-04-00.us-personal-current-taxes-may-2026-brier-shadow-no-packs.659464a73f7283ad","predictionId":"us-personal-current-taxes-may-2026","specId":"spec.us-personal-current-taxes-may-2026","runLabel":"Brier-1 - no packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 0 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 75, distribution present, forecast step count 1.","evidence":["Forecast: point 3262, 80% interval [3235, 3310]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 3262, 80% interval [3235, 3310]"]}],"flags":["weak_counterarguments","no_typed_tool_call"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-personal-current-taxes-may-2026\nrunLabel: Brier-1 - no packs\nresolutionDate: 2026-06-25\ntraceLineCount: 3\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments, no_typed_tool_call."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-personal-current-taxes-may-2026.2026-06-20T09-24-00-04-00.us-personal-current-taxes-may-2026-brier-shadow-with-packs.c8bf9f9dec6e3bdf","runId":"run.us-personal-current-taxes-may-2026.2026-06-20T09-24-00-04-00.us-personal-current-taxes-may-2026-brier-shadow-with-packs.c8bf9f9dec6e3bdf","predictionId":"us-personal-current-taxes-may-2026","specId":"spec.us-personal-current-taxes-may-2026","runLabel":"Brier-1 - packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.05,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":["Tool call: brier.pack.apply({ target: \"bea.personal_current_taxes.level.may_2026.first_print\", packs: [\"base-rate-first@0.1.0\", \"release-vintage-calibration@0.1.0\"] })","Tool result: { admitted: 2, mode: \"with_packs\", required_checks: [\"taxes_base_rate\",\"withholding_receipts\",\"wage_bridge\",\"nonwithheld_timing\"] }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: brier.pack.apply({ target: \"bea.personal_current_taxes.level.may_2026.first_print\", packs: [\"base-rate-first@0.1.0\", \"release-vintage-calibration@0.1.0\"] })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 53, distribution present, forecast step count 1.","evidence":["The pack run raises the center slightly using wages and Treasury receipts, while trimming tails around BEA's tax accounting convention.","Forecast: point 3268, 80% interval [3248, 3301]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 3268, 80% interval [3248, 3301]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-personal-current-taxes-may-2026\nrunLabel: Brier-1 - packs\nresolutionDate: 2026-06-25\ntraceLineCount: 5\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-disposable-personal-income-may-2026.2026-06-06T23-38-51-02-00.fbaa86ff9646b959","runId":"run.us-disposable-personal-income-may-2026.2026-06-06T23-38-51-02-00.fbaa86ff9646b959","predictionId":"us-disposable-personal-income-may-2026","specId":"spec.us-disposable-personal-income-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.22,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 8 source-context item(s), activity log absent.","evidence":["Disposable personal income is the official after-tax household income line, directly connecting labor income, taxes, transfers, inflation, and consumption capacity. This target resolves on 2026-06-25 under a first-print rule, with an expected 19 days lag. The same series can also spawn next release, +3 months, real DPI comparison questions.","Tool result: { jan_billions_saar: 23389.2, feb_billions_saar: 23374.6, mar_billions_saar: 23492.1, apr_billions_saar: 23472.2, apr_percent_change: -0.1, may_release: '2026-06-25 08:30 ET' }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Disposable personal income is the official after-tax household income line, directly connecting labor income, taxes, transfers, inflation, and consumption capacity. This target resolves on 2026-06-25 under a first-print rule, with an expected 19 days lag. The same series can also spawn next release, +3 months, real DPI comparison questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 170, distribution present, forecast step count 1.","evidence":["Forecast: point 23512, 80% interval [23445, 23615]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["April disposable personal income slipped to $23,472.2 billion SAAR after March's jump. The May forecast moves back above April because wages, Social Security, and Medicare benefits are expected to rise, partly offset by higher personal current taxes."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["April disposable personal income slipped to $23,472.2 billion SAAR after March's jump. The May forecast moves back above April because wages, Social Security, and Medicare benefits are expected to rise, partly offset by higher personal current taxes."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["April disposable personal income slipped to $23,472.2 billion SAAR after March's jump. The May forecast moves back above April because wages, Social Security, and Medicare benefits are expected to rise, partly offset by higher personal current taxes.","Forecast: point 23512, 80% interval [23445, 23615]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-disposable-personal-income-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-25\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-disposable-personal-income-may-2026.2026-06-20T09-16-00-04-00.us-disposable-personal-income-may-2026-brier-shadow-no-packs.9e1e0917f29c9578","runId":"run.us-disposable-personal-income-may-2026.2026-06-20T09-16-00-04-00.us-disposable-personal-income-may-2026-brier-shadow-no-packs.9e1e0917f29c9578","predictionId":"us-disposable-personal-income-may-2026","specId":"spec.us-disposable-personal-income-may-2026","runLabel":"Brier-1 - no packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 0 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 205, distribution present, forecast step count 1.","evidence":["Forecast: point 23500, 80% interval [23420, 23625]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 23500, 80% interval [23420, 23625]"]}],"flags":["weak_counterarguments","no_typed_tool_call"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-disposable-personal-income-may-2026\nrunLabel: Brier-1 - no packs\nresolutionDate: 2026-06-25\ntraceLineCount: 3\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments, no_typed_tool_call."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-disposable-personal-income-may-2026.2026-06-20T09-16-00-04-00.us-disposable-personal-income-may-2026-brier-shadow-with-packs.e6b570278bfe0d60","runId":"run.us-disposable-personal-income-may-2026.2026-06-20T09-16-00-04-00.us-disposable-personal-income-may-2026-brier-shadow-with-packs.e6b570278bfe0d60","predictionId":"us-disposable-personal-income-may-2026","specId":"spec.us-disposable-personal-income-may-2026","runLabel":"Brier-1 - packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.05,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":["Tool call: brier.pack.apply({ target: \"bea.disposable_personal_income.level.may_2026.first_print\", packs: [\"base-rate-first@0.1.0\", \"release-vintage-calibration@0.1.0\"] })","Tool result: { admitted: 2, mode: \"with_packs\", required_checks: [\"dpi_base_rate\",\"wages_bridge\",\"benefits_component\",\"tax_offset\"] }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: brier.pack.apply({ target: \"bea.disposable_personal_income.level.may_2026.first_print\", packs: [\"base-rate-first@0.1.0\", \"release-vintage-calibration@0.1.0\"] })","The pack run decomposes DPI into wages, benefits, and taxes, lifting the center slightly while keeping the interval wide enough for BEA first-print accounting noise."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 175, distribution present, forecast step count 1.","evidence":["The pack run decomposes DPI into wages, benefits, and taxes, lifting the center slightly while keeping the interval wide enough for BEA first-print accounting noise.","Forecast: point 23520, 80% interval [23445, 23620]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool result: { admitted: 2, mode: \"with_packs\", required_checks: [\"dpi_base_rate\",\"wages_bridge\",\"benefits_component\",\"tax_offset\"] }"]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The pack run decomposes DPI into wages, benefits, and taxes, lifting the center slightly while keeping the interval wide enough for BEA first-print accounting noise.","Forecast: point 23520, 80% interval [23445, 23620]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-disposable-personal-income-may-2026\nrunLabel: Brier-1 - packs\nresolutionDate: 2026-06-25\ntraceLineCount: 5\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-pce-price-index-mom-may-2026.2026-06-06T23-38-51-02-00.cea33ec3f6750270","runId":"run.us-pce-price-index-mom-may-2026.2026-06-06T23-38-51-02-00.cea33ec3f6750270","predictionId":"us-pce-price-index-mom-may-2026","specId":"spec.us-pce-price-index-mom-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.46,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 8 source-context item(s), activity log absent.","evidence":["The PCE price index is the Federal Reserve's preferred inflation gauge and bridges CPI, PPI, and income-spending data. This target resolves on 2026-06-25 under a first-print rule, with an expected 19 days lag. The same series can also spawn next release, +3 months, core PCE questions.","April's headline PCE inflation was hotter than core PCE, consistent with energy and goods pressure. The May estimate uses expected CPI/PPI moderation but keeps the upper tail because PCE source data can preserve some energy and services pass-through."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","The PCE price index is the Federal Reserve's preferred inflation gauge and bridges CPI, PPI, and income-spending data. This target resolves on 2026-06-25 under a first-print rule, with an expected 19 days lag. The same series can also spawn next release, +3 months, core PCE questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.5, distribution present, forecast step count 1.","evidence":["April's headline PCE inflation was hotter than core PCE, consistent with energy and goods pressure. The May estimate uses expected CPI/PPI moderation but keeps the upper tail because PCE source data can preserve some energy and services pass-through.","Forecast: point 0.3, 80% interval [0.1, 0.6]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["April's headline PCE inflation was hotter than core PCE, consistent with energy and goods pressure. The May estimate uses expected CPI/PPI moderation but keeps the upper tail because PCE source data can preserve some energy and services pass-through."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["April's headline PCE inflation was hotter than core PCE, consistent with energy and goods pressure. The May estimate uses expected CPI/PPI moderation but keeps the upper tail because PCE source data can preserve some energy and services pass-through."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 0.3, 80% interval [0.1, 0.6]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-pce-price-index-mom-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-25\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-real-gdp-q1-2026-third-estimate.2026-06-06T23-38-51-02-00.322d1a50037ed203","runId":"run.us-real-gdp-q1-2026-third-estimate.2026-06-06T23-38-51-02-00.322d1a50037ed203","predictionId":"us-real-gdp-q1-2026-third-estimate","specId":"spec.us-real-gdp-q1-2026-third-estimate","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.22,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 8 source-context item(s), activity log absent.","evidence":["GDP is the headline official output measure and anchors fiscal receipts, benefit demand, labor-market pressure, and monetary-policy forecasts. This target resolves on 2026-06-25 under a first-print rule, with an expected 19 days lag. The same series can also spawn next release, +3 months, GDI comparison questions.","The second estimate already revised Q1 growth down by 0.4 percentage point, mainly from investment and consumer-spending source data. Third estimates usually move less, so the forecast centers just below 1.6% with a tight but nontrivial revision band."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["GDP is the headline official output measure and anchors fiscal receipts, benefit demand, labor-market pressure, and monetary-policy forecasts. This target resolves on 2026-06-25 under a first-print rule, with an expected 19 days lag. The same series can also spawn next release, +3 months, GDI comparison questions.","Tool call: bea.lookup({ release: \"GDP\", series: \"real_gdp_saar\", vintages: [\"2025-Q4\", \"2026-Q1 advance\", \"2026-Q1 second\"] })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.8, distribution present, forecast step count 1.","evidence":["Forecast: point 1.5, 80% interval [1.1, 1.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["GDP is the headline official output measure and anchors fiscal receipts, benefit demand, labor-market pressure, and monetary-policy forecasts. This target resolves on 2026-06-25 under a first-print rule, with an expected 19 days lag. The same series can also spawn next release, +3 months, GDI comparison questions."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["The second estimate already revised Q1 growth down by 0.4 percentage point, mainly from investment and consumer-spending source data. Third estimates usually move less, so the forecast centers just below 1.6% with a tight but nontrivial revision band."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["GDP is the headline official output measure and anchors fiscal receipts, benefit demand, labor-market pressure, and monetary-policy forecasts. This target resolves on 2026-06-25 under a first-print rule, with an expected 19 days lag. The same series can also spawn next release, +3 months, GDI comparison questions.","The second estimate already revised Q1 growth down by 0.4 percentage point, mainly from investment and consumer-spending source data. Third estimates usually move less, so the forecast centers just below 1.6% with a tight but nontrivial revision band."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-real-gdp-q1-2026-third-estimate\nrunLabel: Headline\nresolutionDate: 2026-06-25\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-mts-deficit-may-2026.2026-06-06T23-38-51-02-00.05f5c512919cbbbd","runId":"run.us-mts-deficit-may-2026.2026-06-06T23-38-51-02-00.05f5c512919cbbbd","predictionId":"us-mts-deficit-may-2026","specId":"spec.us-mts-deficit-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.24,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool call: treasury.lookup({ dataset: \"Monthly Treasury Statement table 1\", series: \"current_month_deficit_surplus\", fiscal_year: 2026, months: [\"2026-01\", \"2026-04\"], prior_year_month: \"2025-05\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 8 source-context item(s), activity log absent.","evidence":["The Monthly Treasury Statement is the official cash-flow ledger for federal receipts, outlays, and deficit timing, which makes it a direct policy-cost calibration target. This target resolves on 2026-06-10 under a first-print rule, with an expected 4 days lag. The same series can also spawn next release, +3 months, outlay category split questions.","Tool result: { fy2026_ytd_through_apr_deficit_billions: 953.6, apr2026_surplus_billions: 215.0, may2025_deficit_billions: 315.7 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","The Monthly Treasury Statement is the official cash-flow ledger for federal receipts, outlays, and deficit timing, which makes it a direct policy-cost calibration target. This target resolves on 2026-06-10 under a first-print rule, with an expected 4 days lag. The same series can also spawn next release, +3 months, outlay category split questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 140, distribution present, forecast step count 1.","evidence":["Forecast: point 305, 80% interval [240, 380]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 305, 80% interval [240, 380]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-mts-deficit-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-10\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-defense-aerospace-employment-june-2026.2026-06-29T14-35-00-01-00.f6695939afaa421e","runId":"run.us-defense-aerospace-employment-june-2026.2026-06-29T14-35-00-01-00.f6695939afaa421e","predictionId":"us-defense-aerospace-employment-june-2026","specId":"spec.us-defense-aerospace-employment-june-2026","runLabel":"Defense public-data batch","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and explicit outside-view language.","evidence":["Aerospace employment is a public, monthly proxy for defense-industrial-base capacity in aircraft, missiles, spacecraft, and major supplier networks. This target resolves on 2026-07-02 under a first-print rule, with an expected 2 days lag. The same series can also spawn next release, +3 months, shipbuilding comparison questions.","Tool call: brier.public_series_inventory({ public_sources: [\"BLS CES\", \"Treasury MTS\", \"USAspending\"], themes: [\"defense industrial base\", \"funding\", \"contract obligations\"] })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Aerospace employment is a public, monthly proxy for defense-industrial-base capacity in aircraft, missiles, spacecraft, and major supplier networks. This target resolves on 2026-07-02 under a first-print rule, with an expected 2 days lag. The same series can also spawn next release, +3 months, shipbuilding comparison questions.","Tool call: bls.public_api({ seriesid: \"CES3133640001\", startyear: 2025, endyear: 2026 })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next Employment Situation release","Aerospace employment is a public, monthly proxy for defense-industrial-base capacity in aircraft, missiles, spacecraft, and major supplier networks. This target resolves on 2026-07-02 under a first-print rule, with an expected 2 days lag. The same series can also spawn next release, +3 months, shipbuilding comparison questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 13, distribution present, forecast step count 1.","evidence":["Forecast: point 589, 80% interval [583, 596]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The latest public CES path is rising steadily, up 7.8k from June 2025 to April 2026 and 5.8k since January. The forecast extends that trend but shrinks toward persistence because aerospace hiring is lumpy and the CES first print can revise around survey timing."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["The latest public CES path is rising steadily, up 7.8k from June 2025 to April 2026 and 5.8k since January. The forecast extends that trend but shrinks toward persistence because aerospace hiring is lumpy and the CES first print can revise around survey timing."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The latest public CES path is rising steadily, up 7.8k from June 2025 to April 2026 and 5.8k since January. The forecast extends that trend but shrinks toward persistence because aerospace hiring is lumpy and the CES first print can revise around survey timing.","Forecast: point 589, 80% interval [583, 596]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-defense-aerospace-employment-june-2026\nrunLabel: Defense public-data batch\nresolutionDate: 2026-07-02\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-defense-shipbuilding-employment-june-2026.2026-06-29T14-35-00-01-00.c9d091118be74b06","runId":"run.us-defense-shipbuilding-employment-june-2026.2026-06-29T14-35-00-01-00.c9d091118be74b06","predictionId":"us-defense-shipbuilding-employment-june-2026","specId":"spec.us-defense-shipbuilding-employment-june-2026","runLabel":"Defense public-data batch","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.14,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 4 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Shipbuilding employment is a monthly public proxy for naval procurement capacity, yard bottlenecks, and defense supply-chain constraints. This target resolves on 2026-07-02 under a first-print rule, with an expected 2 days lag. The same series can also spawn next release, +3 months, aerospace comparison questions.","Tool call: bls.public_api({ seriesid: \"CES3133660001\", startyear: 2024, endyear: 2026 })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next Employment Situation release","Shipbuilding employment is a monthly public proxy for naval procurement capacity, yard bottlenecks, and defense supply-chain constraints. This target resolves on 2026-07-02 under a first-print rule, with an expected 2 days lag. The same series can also spawn next release, +3 months, aerospace comparison questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3.3, distribution present, forecast step count 1.","evidence":["Ship and boat building employment has been almost flat through early 2026 and lower than mid-2024. The center is a persistence forecast with a slight downward drift, while the interval leaves room for small first-print noise and delayed yard hiring.","Forecast: point 148.4, 80% interval [146.8, 150.1]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Ship and boat building employment has been almost flat through early 2026 and lower than mid-2024. The center is a persistence forecast with a slight downward drift, while the interval leaves room for small first-print noise and delayed yard hiring.","Forecast: point 148.4, 80% interval [146.8, 150.1]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-defense-shipbuilding-employment-june-2026\nrunLabel: Defense public-data batch\nresolutionDate: 2026-07-02\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-defense-dod-employment-june-2026.2026-06-29T14-35-00-01-00.37b8a0ff802d0bb5","runId":"run.us-defense-dod-employment-june-2026.2026-06-29T14-35-00-01-00.37b8a0ff802d0bb5","predictionId":"us-defense-dod-employment-june-2026","specId":"spec.us-defense-dod-employment-june-2026","runLabel":"Defense public-data batch","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.08,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["DoD civilian employment is a public personnel-capacity target for testing claims about acquisition reform, hiring authorities, and execution capacity. This target resolves on 2026-07-02 under a first-print rule, with an expected 2 days lag. The same series can also spawn next release, +3 months, contract-obligation comparison questions.","Tool call: bls.public_api({ seriesid: \"CES9091911001\", startyear: 2025, endyear: 2026 })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next Employment Situation release","DoD civilian employment is a public personnel-capacity target for testing claims about acquisition reform, hiring authorities, and execution capacity. This target resolves on 2026-07-02 under a first-print rule, with an expected 2 days lag. The same series can also spawn next release, +3 months, contract-obligation comparison questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 49, distribution present, forecast step count 1.","evidence":["The series shows a large late-2025 level shift, then relative stability from January through April 2026. The center stays close to April's first print; the wide interval reflects uncertainty about whether the shift was administrative, policy-driven, or still passing through the first-print data.","Forecast: point 474, 80% interval [452, 501]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["The series shows a large late-2025 level shift, then relative stability from January through April 2026. The center stays close to April's first print; the wide interval reflects uncertainty about whether the shift was administrative, policy-driven, or still passing through the first-print data."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { useful_public_series: ['BLS CES federal Department of Defense employment'], selected_proxy: 'BLS CES DoD employment', latest_public_history_points: 6 }","The series shows a large late-2025 level shift, then relative stability from January through April 2026. The center stays close to April's first print; the wide interval reflects uncertainty about whether the shift was administrative, policy-driven, or still passing through the first-print data."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-defense-dod-employment-june-2026\nrunLabel: Defense public-data batch\nresolutionDate: 2026-07-02\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-defense-dod-military-outlays-june-2026.2026-06-29T14-35-00-01-00.824289277a19b1e6","runId":"run.us-defense-dod-military-outlays-june-2026.2026-06-29T14-35-00-01-00.824289277a19b1e6","predictionId":"us-defense-dod-military-outlays-june-2026","specId":"spec.us-defense-dod-military-outlays-june-2026","runLabel":"Defense public-data batch","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.22,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 5 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["DoD outlays are the official cash-flow endpoint for defense resource allocation, showing how appropriated budget authority turns into government payments. This target resolves on 2026-07-13 under a first-print rule, with an expected 13 days lag. The same series can also spawn next release, +3 months, contract-obligation bridge questions.","Tool call: brier.public_series_inventory({ public_sources: [\"Treasury MTS\", \"USAspending\"], themes: [\"appropriations\", \"outlays\", \"contract obligations\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next MTS release","DoD outlays are the official cash-flow endpoint for defense resource allocation, showing how appropriated budget authority turns into government payments. This target resolves on 2026-07-13 under a first-print rule, with an expected 13 days lag. The same series can also spawn next release, +3 months, contract-obligation bridge questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 24, distribution present, forecast step count 1.","evidence":["May was $69.18B after a $73.26B April and $65.38B March. June is a quarter-end month, so the forecast sits above May but well below the December surge, with a wider interval because procurement and RDT&E payment timing can move several billion dollars month to month.","Forecast: point 72, 80% interval [62, 86]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["May was $69.18B after a $73.26B April and $65.38B March. June is a quarter-end month, so the forecast sits above May but well below the December surge, with a wider interval because procurement and RDT&E payment timing can move several billion dollars month to month."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["May was $69.18B after a $73.26B April and $65.38B March. June is a quarter-end month, so the forecast sits above May but well below the December surge, with a wider interval because procurement and RDT&E payment timing can move several billion dollars month to month."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["DoD outlays are the official cash-flow endpoint for defense resource allocation, showing how appropriated budget authority turns into government payments. This target resolves on 2026-07-13 under a first-print rule, with an expected 13 days lag. The same series can also spawn next release, +3 months, contract-obligation bridge questions.","Tool result: { useful_public_series: ['Treasury MTS DoD military programs gross outlays', 'USAspending DoD contract obligations'], selected_proxy: 'MTS DoD military programs outlays', latest_public_history_points: 6 }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-defense-dod-military-outlays-june-2026\nrunLabel: Defense public-data batch\nresolutionDate: 2026-07-13\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-defense-dod-contract-obligations-fy2026.2026-06-29T14-35-00-01-00.ee6b31dc6e749c4d","runId":"run.us-defense-dod-contract-obligations-fy2026.2026-06-29T14-35-00-01-00.ee6b31dc6e749c4d","predictionId":"us-defense-dod-contract-obligations-fy2026","specId":"spec.us-defense-dod-contract-obligations-fy2026","runLabel":"Defense public-data batch","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.19,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Contract obligations are the public award-level bridge between defense appropriations and actual commitments to firms, which is the core measurable surface for acquisition-policy simulation. This target resolves on 2026-12-31 under a fixed-vintage rule, with an expected 91 days lag. The same series can also spawn next fiscal year, quarterly vintage, outlay comparison questions.","Tool call: usaspending.agency_obligations_by_award_category({ agency: \"097\", fiscal_years: [2024, 2025, 2026], category: \"contracts\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Contract obligations are the public award-level bridge between defense appropriations and actual commitments to firms, which is the core measurable surface for acquisition-policy simulation. This target resolves on 2026-12-31 under a fixed-vintage rule, with an expected 91 days lag. The same series can also spawn next fiscal year, quarterly vintage, outlay comparison questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 130, distribution present, forecast step count 1.","evidence":["Forecast: point 470, 80% interval [405, 535]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The partial FY2026 contract total is not comparable to final-year values because defense obligations are back-loaded and reporting refreshes continue after fiscal year close. FY2024 and FY2025 bracket the outside view; the forecast centers between them with upside for a fourth-quarter award surge and downside for continuing-resolution or procurement delay."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { contracts: 207.527, total_aggregated_amount: 212.911, endpoint_accessed: '2026-06-29' }","The partial FY2026 contract total is not comparable to final-year values because defense obligations are back-loaded and reporting refreshes continue after fiscal year close. FY2024 and FY2025 bracket the outside view; the forecast centers between them with upside for a fourth-quarter award surge and downside for continuing-resolution or procurement delay."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-defense-dod-contract-obligations-fy2026\nrunLabel: Defense public-data batch\nresolutionDate: 2026-12-31\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-business-financial-employment-may-2026.2026-06-17T14-25-00-04-00.dda17fc8849cd699","runId":"run.oews-business-financial-employment-may-2026.2026-06-17T14-25-00-04-00.dda17fc8849cd699","predictionId":"oews-business-financial-employment-may-2026","specId":"spec.oews-business-financial-employment-may-2026","runLabel":"Occupation synthesis - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.46,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["This group is a clean white-collar exposure target: analysts, compliance staff, accountants, and related roles face both AI substitution pressure and productivity-driven demand growth. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, +12 months, threshold questions.","Tool call: bls.oews.lookup({ table: \"national\", occupation: \"13-0000\", releases: [\"May 2023\", \"May 2024\", \"May 2025\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","This group is a clean white-collar exposure target: analysts, compliance staff, accountants, and related roles face both AI substitution pressure and productivity-driven demand growth. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, +12 months, threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 750, distribution present, forecast step count 1.","evidence":["Forecast: point 10420, 80% interval [10050, 10800]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["This group is a clean white-collar exposure target: analysts, compliance staff, accountants, and related roles face both AI substitution pressure and productivity-driven demand growth. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, +12 months, threshold questions.","Professional services and finance hiring should keep this group growing, but the forecast discounts simple trend extrapolation because analyst, bookkeeping, and compliance workflows are exactly where generative AI can absorb task volume without an immediate headcount increase."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Professional services and finance hiring should keep this group growing, but the forecast discounts simple trend extrapolation because analyst, bookkeeping, and compliance workflows are exactly where generative AI can absorb task volume without an immediate headcount increase."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS occupation employment table.","Professional services and finance hiring should keep this group growing, but the forecast discounts simple trend extrapolation because analyst, bookkeeping, and compliance workflows are exactly where generative AI can absorb task volume without an immediate headcount increase."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-business-financial-employment-may-2026\nrunLabel: Occupation synthesis - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-business-financial-employment-may-2026.2026-06-17T14-40-00-04-00.with-bls-employment-projections.8e75f0282ffd8be8","runId":"run.oews-business-financial-employment-may-2026.2026-06-17T14-40-00-04-00.with-bls-employment-projections.8e75f0282ffd8be8","predictionId":"oews-business-financial-employment-may-2026","specId":"spec.oews-business-financial-employment-may-2026","runLabel":"BLS projections pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 3 historical point(s) and explicit outside-view language.","evidence":["This run treats BLS Employment Projections as an outside-view prior, not as the resolver. The target still resolves against the first-published May 2026 OEWS national occupation employment table.","Tool call: brier.pack.apply({ packs: [\"bls-employment-projections-baseline@0.1.0\"], role: \"outside_view_prior\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["BLS Employment Projections pack","This run treats BLS Employment Projections as an outside-view prior, not as the resolver. The target still resolves against the first-published May 2026 OEWS national occupation employment table."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["This run treats BLS Employment Projections as an outside-view prior, not as the resolver. The target still resolves against the first-published May 2026 OEWS national occupation employment table.","Tool call: bls.employment_projections.lookup({ table: \"1.2\", window: \"2024-2034\", target: \"bls.oews.national_occupation_employment.soc_13_0000.may_2026.first_print\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 730, distribution present, forecast step count 1.","evidence":["Forecast: point 10480, 80% interval [10130, 10860]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The BLS projection baseline nudges the center higher because business and financial occupations remain a positive-growth group over the decade, but the pack only modestly affects a May 2026 first-print OEWS target."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The BLS projection baseline nudges the center higher because business and financial occupations remain a positive-growth group over the decade, but the pack only modestly affects a May 2026 first-print OEWS target."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { admitted: 1, mode: 'with_packs', control_point_thousands: 10420, pack_adjustment_thousands: +60, packed_point_thousands: 10480, resolver_unchanged: 'BLS OEWS first print' }","Control forecast 10.42m + BLS projections pack adjustment +60k = 10.48m."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-business-financial-employment-may-2026\nrunLabel: BLS projections pack\nresolutionDate: 2027-05-14\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-business-financial-employment-may-2026.2025-08-28T10-00-00-04-00.bls-implied-2026-annual-baseline.2db739c6a5993642","runId":"run.oews-business-financial-employment-may-2026.2025-08-28T10-00-00-04-00.bls-implied-2026-annual-baseline.2db739c6a5993642","predictionId":"oews-business-financial-employment-may-2026","specId":"spec.oews-business-financial-employment-may-2026","runLabel":"BLS-implied 2026 baseline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 3 historical point(s) and explicit outside-view language.","evidence":["BLS does not publish an official May 2026 OEWS forecast. This baseline keeps the annual OEWS resolver but uses the BLS 2024-2034 major-group growth rate as the outside-view annual path."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS-implied annual comparator","BLS does not publish an official May 2026 OEWS forecast. This baseline keeps the annual OEWS resolver but uses the BLS 2024-2034 major-group growth rate as the outside-view annual path."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.2, distribution present, forecast step count 1.","evidence":["Forecast: point 10350, 80% interval [10349.9, 10350.1]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS does not publish an official May 2026 OEWS forecast. This baseline keeps the annual OEWS resolver but uses the BLS 2024-2034 major-group growth rate as the outside-view annual path."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["BLS does not publish an official May 2026 OEWS forecast. This baseline keeps the annual OEWS resolver but uses the BLS 2024-2034 major-group growth rate as the outside-view annual path.","Forecast: point 10350, 80% interval [10349.9, 10350.1]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-business-financial-employment-may-2026\nrunLabel: BLS-implied 2026 baseline\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-computer-math-employment-may-2026.2026-06-17T14-25-00-04-00.ce71380885146973","runId":"run.oews-computer-math-employment-may-2026.2026-06-17T14-25-00-04-00.ce71380885146973","predictionId":"oews-computer-math-employment-may-2026","specId":"spec.oews-computer-math-employment-may-2026","runLabel":"Occupation synthesis - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.43,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Computer and mathematical occupations are the most direct labor-market readout for coding assistants, data-analysis tools, and the demand side of AI infrastructure buildout. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, +12 months, threshold questions.","Tool call: bls.oews.lookup({ table: \"national\", occupation: \"15-0000\", releases: [\"May 2023\", \"May 2024\", \"May 2025\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Computer and mathematical occupations are the most direct labor-market readout for coding assistants, data-analysis tools, and the demand side of AI infrastructure buildout. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, +12 months, threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 600, distribution present, forecast step count 1.","evidence":["The central case is continued growth, not collapse: AI tooling reduces some junior coding task demand but AI infrastructure, data engineering, security, and model-integration work keep total employment above the 2025 level. The interval keeps a wide lower tail for hiring freezes and offshoring.","Forecast: point 5850, 80% interval [5550, 6150]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The central case is continued growth, not collapse: AI tooling reduces some junior coding task demand but AI infrastructure, data engineering, security, and model-integration work keep total employment above the 2025 level. The interval keeps a wide lower tail for hiring freezes and offshoring."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS occupation employment table.","The central case is continued growth, not collapse: AI tooling reduces some junior coding task demand but AI infrastructure, data engineering, security, and model-integration work keep total employment above the 2025 level. The interval keeps a wide lower tail for hiring freezes and offshoring."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-computer-math-employment-may-2026\nrunLabel: Occupation synthesis - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-computer-math-employment-may-2026.2026-06-17T14-40-00-04-00.with-bls-employment-projections.53266180a509d1f0","runId":"run.oews-computer-math-employment-may-2026.2026-06-17T14-40-00-04-00.with-bls-employment-projections.53266180a509d1f0","predictionId":"oews-computer-math-employment-may-2026","specId":"spec.oews-computer-math-employment-may-2026","runLabel":"BLS projections pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.54,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 3 historical point(s) and explicit outside-view language.","evidence":["This run treats BLS Employment Projections as an outside-view prior, not as the resolver. The target still resolves against the first-published May 2026 OEWS national occupation employment table.","Tool call: brier.pack.apply({ packs: [\"bls-employment-projections-baseline@0.1.0\"], role: \"outside_view_prior\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["BLS Employment Projections pack","This run treats BLS Employment Projections as an outside-view prior, not as the resolver. The target still resolves against the first-published May 2026 OEWS national occupation employment table."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["This run treats BLS Employment Projections as an outside-view prior, not as the resolver. The target still resolves against the first-published May 2026 OEWS national occupation employment table.","Tool call: bls.employment_projections.lookup({ table: \"1.2\", window: \"2024-2034\", target: \"bls.oews.national_occupation_employment.soc_15_0000.may_2026.first_print\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 590, distribution present, forecast step count 1.","evidence":["The projections pack raises the center slightly: BLS long-run computer and mathematical growth leans against a pure near-term automation-substitution story, while the interval remains wide for tech hiring cyclicality.","Forecast: point 5900, 80% interval [5620, 6210]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { admitted: 1, mode: 'with_packs', control_point_thousands: 5850, pack_adjustment_thousands: +50, packed_point_thousands: 5900, resolver_unchanged: 'BLS OEWS first print' }","Control forecast 5.85m + BLS projections pack adjustment +50k = 5.9m."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-computer-math-employment-may-2026\nrunLabel: BLS projections pack\nresolutionDate: 2027-05-14\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-computer-math-employment-may-2026.2025-08-28T10-00-00-04-00.bls-implied-2026-annual-baseline.d04a6e44b6d8f01f","runId":"run.oews-computer-math-employment-may-2026.2025-08-28T10-00-00-04-00.bls-implied-2026-annual-baseline.d04a6e44b6d8f01f","predictionId":"oews-computer-math-employment-may-2026","specId":"spec.oews-computer-math-employment-may-2026","runLabel":"BLS-implied 2026 baseline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 3 historical point(s) and explicit outside-view language.","evidence":["BLS does not publish an official May 2026 OEWS forecast. This baseline keeps the annual OEWS resolver but uses the BLS 2024-2034 major-group growth rate as the outside-view annual path."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS-implied annual comparator","BLS does not publish an official May 2026 OEWS forecast. This baseline keeps the annual OEWS resolver but uses the BLS 2024-2034 major-group growth rate as the outside-view annual path."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.2, distribution present, forecast step count 1.","evidence":["Forecast: point 5780, 80% interval [5779.9, 5780.1]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS does not publish an official May 2026 OEWS forecast. This baseline keeps the annual OEWS resolver but uses the BLS 2024-2034 major-group growth rate as the outside-view annual path."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["BLS does not publish an official May 2026 OEWS forecast. This baseline keeps the annual OEWS resolver but uses the BLS 2024-2034 major-group growth rate as the outside-view annual path.","Forecast: point 5780, 80% interval [5779.9, 5780.1]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-computer-math-employment-may-2026\nrunLabel: BLS-implied 2026 baseline\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-healthcare-support-employment-may-2026.2026-06-17T14-25-00-04-00.87b0809d8be69bfd","runId":"run.oews-healthcare-support-employment-may-2026.2026-06-17T14-25-00-04-00.87b0809d8be69bfd","predictionId":"oews-healthcare-support-employment-may-2026","specId":"spec.oews-healthcare-support-employment-may-2026","runLabel":"Occupation synthesis - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.57,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Healthcare support is a useful low-substitution benchmark: care work is labor intensive, demand is demographically strong, and AI effects mostly run through documentation and scheduling. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, +12 months, threshold questions.","Tool call: bls.oews.lookup({ table: \"national\", occupation: \"31-0000\", releases: [\"May 2023\", \"May 2024\", \"May 2025\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Healthcare support is a useful low-substitution benchmark: care work is labor intensive, demand is demographically strong, and AI effects mostly run through documentation and scheduling. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, +12 months, threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 750, distribution present, forecast step count 1.","evidence":["This group should keep expanding because demand for aides, assistants, and support staff is tied to care volume rather than information processing alone. The main downside risk is provider margin pressure and staffing shortages, not AI task substitution.","Forecast: point 7420, 80% interval [7050, 7800]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: { exposure: 'low_substitution', complementarity: 'documentation_and_triage', demographic_pressure: 'high' }","This group should keep expanding because demand for aides, assistants, and support staff is tied to care volume rather than information processing alone. The main downside risk is provider margin pressure and staffing shortages, not AI task substitution."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["This group should keep expanding because demand for aides, assistants, and support staff is tied to care volume rather than information processing alone. The main downside risk is provider margin pressure and staffing shortages, not AI task substitution."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS occupation employment table.","Forecast: point 7420, 80% interval [7050, 7800]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-healthcare-support-employment-may-2026\nrunLabel: Occupation synthesis - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-healthcare-support-employment-may-2026.2026-06-17T14-40-00-04-00.with-bls-employment-projections.36bbbc0a2eef8329","runId":"run.oews-healthcare-support-employment-may-2026.2026-06-17T14-40-00-04-00.with-bls-employment-projections.36bbbc0a2eef8329","predictionId":"oews-healthcare-support-employment-may-2026","specId":"spec.oews-healthcare-support-employment-may-2026","runLabel":"BLS projections pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 3 historical point(s) and explicit outside-view language.","evidence":["This run treats BLS Employment Projections as an outside-view prior, not as the resolver. The target still resolves against the first-published May 2026 OEWS national occupation employment table.","Tool call: brier.pack.apply({ packs: [\"bls-employment-projections-baseline@0.1.0\"], role: \"outside_view_prior\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["BLS Employment Projections pack","This run treats BLS Employment Projections as an outside-view prior, not as the resolver. The target still resolves against the first-published May 2026 OEWS national occupation employment table."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["This run treats BLS Employment Projections as an outside-view prior, not as the resolver. The target still resolves against the first-published May 2026 OEWS national occupation employment table.","Tool call: bls.employment_projections.lookup({ table: \"1.2\", window: \"2024-2034\", target: \"bls.oews.national_occupation_employment.soc_31_0000.may_2026.first_print\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 740, distribution present, forecast step count 1.","evidence":["Forecast: point 7480, 80% interval [7120, 7860]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The BLS projection prior pushes healthcare support higher because long-run care demand is a strong outside-view anchor and near-term AI substitution is limited."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { admitted: 1, mode: 'with_packs', control_point_thousands: 7420, pack_adjustment_thousands: +60, packed_point_thousands: 7480, resolver_unchanged: 'BLS OEWS first print' }","Control forecast 7.42m + BLS projections pack adjustment +60k = 7.48m."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-healthcare-support-employment-may-2026\nrunLabel: BLS projections pack\nresolutionDate: 2027-05-14\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-healthcare-support-employment-may-2026.2025-08-28T10-00-00-04-00.bls-implied-2026-annual-baseline.f736dea3abd2de1f","runId":"run.oews-healthcare-support-employment-may-2026.2025-08-28T10-00-00-04-00.bls-implied-2026-annual-baseline.f736dea3abd2de1f","predictionId":"oews-healthcare-support-employment-may-2026","specId":"spec.oews-healthcare-support-employment-may-2026","runLabel":"BLS-implied 2026 baseline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 3 historical point(s) and explicit outside-view language.","evidence":["BLS does not publish an official May 2026 OEWS forecast. This baseline keeps the annual OEWS resolver but uses the BLS 2024-2034 major-group growth rate as the outside-view annual path."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS-implied annual comparator","BLS does not publish an official May 2026 OEWS forecast. This baseline keeps the annual OEWS resolver but uses the BLS 2024-2034 major-group growth rate as the outside-view annual path."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.2, distribution present, forecast step count 1.","evidence":["Forecast: point 7340, 80% interval [7339.9, 7340.1]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS does not publish an official May 2026 OEWS forecast. This baseline keeps the annual OEWS resolver but uses the BLS 2024-2034 major-group growth rate as the outside-view annual path."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["BLS does not publish an official May 2026 OEWS forecast. This baseline keeps the annual OEWS resolver but uses the BLS 2024-2034 major-group growth rate as the outside-view annual path.","Forecast: point 7340, 80% interval [7339.9, 7340.1]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-healthcare-support-employment-may-2026\nrunLabel: BLS-implied 2026 baseline\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-office-admin-employment-may-2026.2026-06-17T14-25-00-04-00.c12c29547ee1848e","runId":"run.oews-office-admin-employment-may-2026.2026-06-17T14-25-00-04-00.c12c29547ee1848e","predictionId":"oews-office-admin-employment-may-2026","specId":"spec.oews-office-admin-employment-may-2026","runLabel":"Occupation synthesis - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.08,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Office and administrative support is the clearest large SOC group for clerical automation: scheduling, records, call handling, forms, and back-office workflows are all direct software targets. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, +12 months, threshold questions.","Tool call: bls.oews.lookup({ table: \"national\", occupation: \"43-0000\", releases: [\"May 2023\", \"May 2024\", \"May 2025\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Office and administrative support is the clearest large SOC group for clerical automation: scheduling, records, call handling, forms, and back-office workflows are all direct software targets. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, +12 months, threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 850, distribution present, forecast step count 1.","evidence":["Forecast: point 17650, 80% interval [17200, 18050]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS occupation employment table.","The forecast keeps the downward trend intact. Even if overall service employment grows, routine clerical headcount is exposed to document automation, scheduling tools, and customer-contact software, so the central estimate is below the 2025 level."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-office-admin-employment-may-2026\nrunLabel: Occupation synthesis - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-office-admin-employment-may-2026.2026-06-17T14-40-00-04-00.with-bls-employment-projections.9aa8f2338679a54c","runId":"run.oews-office-admin-employment-may-2026.2026-06-17T14-40-00-04-00.with-bls-employment-projections.9aa8f2338679a54c","predictionId":"oews-office-admin-employment-may-2026","specId":"spec.oews-office-admin-employment-may-2026","runLabel":"BLS projections pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.54,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 3 historical point(s) and explicit outside-view language.","evidence":["This run treats BLS Employment Projections as an outside-view prior, not as the resolver. The target still resolves against the first-published May 2026 OEWS national occupation employment table.","Tool call: brier.pack.apply({ packs: [\"bls-employment-projections-baseline@0.1.0\"], role: \"outside_view_prior\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["BLS Employment Projections pack","This run treats BLS Employment Projections as an outside-view prior, not as the resolver. The target still resolves against the first-published May 2026 OEWS national occupation employment table."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["This run treats BLS Employment Projections as an outside-view prior, not as the resolver. The target still resolves against the first-published May 2026 OEWS national occupation employment table.","Tool call: bls.employment_projections.lookup({ table: \"1.2\", window: \"2024-2034\", target: \"bls.oews.national_occupation_employment.soc_43_0000.may_2026.first_print\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 840, distribution present, forecast step count 1.","evidence":["Forecast: point 17590, 80% interval [17140, 17980]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { admitted: 1, mode: 'with_packs', control_point_thousands: 17650, pack_adjustment_thousands: -60, packed_point_thousands: 17590, resolver_unchanged: 'BLS OEWS first print' }","Control forecast 17.65m + BLS projections pack adjustment -60k = 17.59m."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-office-admin-employment-may-2026\nrunLabel: BLS projections pack\nresolutionDate: 2027-05-14\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-office-admin-employment-may-2026.2025-08-28T10-00-00-04-00.bls-implied-2026-annual-baseline.aa56aee6e2777c79","runId":"run.oews-office-admin-employment-may-2026.2025-08-28T10-00-00-04-00.bls-implied-2026-annual-baseline.aa56aee6e2777c79","predictionId":"oews-office-admin-employment-may-2026","specId":"spec.oews-office-admin-employment-may-2026","runLabel":"BLS-implied 2026 baseline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 3 historical point(s) and explicit outside-view language.","evidence":["BLS does not publish an official May 2026 OEWS forecast. This baseline keeps the annual OEWS resolver but uses the BLS 2024-2034 major-group growth rate as the outside-view annual path."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS-implied annual comparator","BLS does not publish an official May 2026 OEWS forecast. This baseline keeps the annual OEWS resolver but uses the BLS 2024-2034 major-group growth rate as the outside-view annual path."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.2, distribution present, forecast step count 1.","evidence":["Forecast: point 17780, 80% interval [17779.9, 17780.1]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS does not publish an official May 2026 OEWS forecast. This baseline keeps the annual OEWS resolver but uses the BLS 2024-2034 major-group growth rate as the outside-view annual path."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["BLS does not publish an official May 2026 OEWS forecast. This baseline keeps the annual OEWS resolver but uses the BLS 2024-2034 major-group growth rate as the outside-view annual path.","Forecast: point 17780, 80% interval [17779.9, 17780.1]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-office-admin-employment-may-2026\nrunLabel: BLS-implied 2026 baseline\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-production-employment-may-2026.2026-06-17T14-25-00-04-00.a6b0be817c90d97a","runId":"run.oews-production-employment-may-2026.2026-06-17T14-25-00-04-00.a6b0be817c90d97a","predictionId":"oews-production-employment-may-2026","specId":"spec.oews-production-employment-may-2026","runLabel":"Occupation synthesis - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.43,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Production occupations connect task automation to robotics, manufacturing demand, trade exposure, and goods-sector cyclicality rather than only software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, +12 months, threshold questions.","Tool call: bls.oews.lookup({ table: \"national\", occupation: \"51-0000\", releases: [\"May 2023\", \"May 2024\", \"May 2025\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Production occupations connect task automation to robotics, manufacturing demand, trade exposure, and goods-sector cyclicality rather than only software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, +12 months, threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 750, distribution present, forecast step count 1.","evidence":["Production employment likely drifts down modestly as manufacturing demand stays mixed and automation continues to absorb routine tasks. The interval is symmetric enough to allow a reshoring or capex surprise, but the point stays below the 2025 context.","Forecast: point 8520, 80% interval [8150, 8900]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["Production employment likely drifts down modestly as manufacturing demand stays mixed and automation continues to absorb routine tasks. The interval is symmetric enough to allow a reshoring or capex surprise, but the point stays below the 2025 context."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS occupation employment table.","Production employment likely drifts down modestly as manufacturing demand stays mixed and automation continues to absorb routine tasks. The interval is symmetric enough to allow a reshoring or capex surprise, but the point stays below the 2025 context."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-production-employment-may-2026\nrunLabel: Occupation synthesis - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-production-employment-may-2026.2026-06-17T14-40-00-04-00.with-bls-employment-projections.23b619b3e7433af3","runId":"run.oews-production-employment-may-2026.2026-06-17T14-40-00-04-00.with-bls-employment-projections.23b619b3e7433af3","predictionId":"oews-production-employment-may-2026","specId":"spec.oews-production-employment-may-2026","runLabel":"BLS projections pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 3 historical point(s) and explicit outside-view language.","evidence":["This run treats BLS Employment Projections as an outside-view prior, not as the resolver. The target still resolves against the first-published May 2026 OEWS national occupation employment table.","Tool call: brier.pack.apply({ packs: [\"bls-employment-projections-baseline@0.1.0\"], role: \"outside_view_prior\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["BLS Employment Projections pack","This run treats BLS Employment Projections as an outside-view prior, not as the resolver. The target still resolves against the first-published May 2026 OEWS national occupation employment table."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["This run treats BLS Employment Projections as an outside-view prior, not as the resolver. The target still resolves against the first-published May 2026 OEWS national occupation employment table.","Tool call: bls.employment_projections.lookup({ table: \"1.2\", window: \"2024-2034\", target: \"bls.oews.national_occupation_employment.soc_51_0000.may_2026.first_print\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 760, distribution present, forecast step count 1.","evidence":["Forecast: point 8500, 80% interval [8120, 8880]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The projection pack has a small negative effect: BLS long-run production employment pressure is already aligned with the control forecast, so the pack mostly confirms rather than moves the center."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { admitted: 1, mode: 'with_packs', control_point_thousands: 8520, pack_adjustment_thousands: -20, packed_point_thousands: 8500, resolver_unchanged: 'BLS OEWS first print' }","Control forecast 8.52m + BLS projections pack adjustment -20k = 8.5m."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-production-employment-may-2026\nrunLabel: BLS projections pack\nresolutionDate: 2027-05-14\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-production-employment-may-2026.2025-08-28T10-00-00-04-00.bls-implied-2026-annual-baseline.22f2daa8ce0b4df4","runId":"run.oews-production-employment-may-2026.2025-08-28T10-00-00-04-00.bls-implied-2026-annual-baseline.22f2daa8ce0b4df4","predictionId":"oews-production-employment-may-2026","specId":"spec.oews-production-employment-may-2026","runLabel":"BLS-implied 2026 baseline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 3 historical point(s) and explicit outside-view language.","evidence":["BLS does not publish an official May 2026 OEWS forecast. This baseline keeps the annual OEWS resolver but uses the BLS 2024-2034 major-group growth rate as the outside-view annual path."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS-implied annual comparator","BLS does not publish an official May 2026 OEWS forecast. This baseline keeps the annual OEWS resolver but uses the BLS 2024-2034 major-group growth rate as the outside-view annual path."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.2, distribution present, forecast step count 1.","evidence":["Forecast: point 8590, 80% interval [8589.9, 8590.1]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS does not publish an official May 2026 OEWS forecast. This baseline keeps the annual OEWS resolver but uses the BLS 2024-2034 major-group growth rate as the outside-view annual path."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["BLS does not publish an official May 2026 OEWS forecast. This baseline keeps the annual OEWS resolver but uses the BLS 2024-2034 major-group growth rate as the outside-view annual path.","Forecast: point 8590, 80% interval [8589.9, 8590.1]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-production-employment-may-2026\nrunLabel: BLS-implied 2026 baseline\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-transport-material-moving-employment-may-2026.2026-06-17T14-25-00-04-00.6da9f89644bf80b3","runId":"run.oews-transport-material-moving-employment-may-2026.2026-06-17T14-25-00-04-00.6da9f89644bf80b3","predictionId":"oews-transport-material-moving-employment-may-2026","specId":"spec.oews-transport-material-moving-employment-may-2026","runLabel":"Occupation synthesis - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.32,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Logistics, warehousing, driving, and material movement are central to automation debates because warehouse software, routing, and autonomy can change task demand before fully replacing workers. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, +12 months, threshold questions.","Tool call: bls.oews.lookup({ table: \"national\", occupation: \"53-0000\", releases: [\"May 2023\", \"May 2024\", \"May 2025\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Logistics, warehousing, driving, and material movement are central to automation debates because warehouse software, routing, and autonomy can change task demand before fully replacing workers. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, +12 months, threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1150, distribution present, forecast step count 1.","evidence":["Forecast: point 14050, 80% interval [13500, 14650]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Logistics, warehousing, driving, and material movement are central to automation debates because warehouse software, routing, and autonomy can change task demand before fully replacing workers. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, +12 months, threshold questions."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Logistics employment should remain roughly flat-to-up through May 2026: warehouse automation and routing tools reduce marginal labor demand, but full vehicle autonomy is unlikely to materially cut national occupational employment by this release."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS occupation employment table.","Forecast: point 14050, 80% interval [13500, 14650]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-transport-material-moving-employment-may-2026\nrunLabel: Occupation synthesis - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-transport-material-moving-employment-may-2026.2026-06-17T14-40-00-04-00.with-bls-employment-projections.15333d484eac43b6","runId":"run.oews-transport-material-moving-employment-may-2026.2026-06-17T14-40-00-04-00.with-bls-employment-projections.15333d484eac43b6","predictionId":"oews-transport-material-moving-employment-may-2026","specId":"spec.oews-transport-material-moving-employment-may-2026","runLabel":"BLS projections pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 3 historical point(s) and explicit outside-view language.","evidence":["This run treats BLS Employment Projections as an outside-view prior, not as the resolver. The target still resolves against the first-published May 2026 OEWS national occupation employment table.","Tool call: brier.pack.apply({ packs: [\"bls-employment-projections-baseline@0.1.0\"], role: \"outside_view_prior\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["BLS Employment Projections pack","This run treats BLS Employment Projections as an outside-view prior, not as the resolver. The target still resolves against the first-published May 2026 OEWS national occupation employment table."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["This run treats BLS Employment Projections as an outside-view prior, not as the resolver. The target still resolves against the first-published May 2026 OEWS national occupation employment table.","Tool call: bls.employment_projections.lookup({ table: \"1.2\", window: \"2024-2034\", target: \"bls.oews.national_occupation_employment.soc_53_0000.may_2026.first_print\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1120, distribution present, forecast step count 1.","evidence":["Forecast: point 14110, 80% interval [13580, 14700]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The BLS projection prior nudges transportation and material moving up because goods movement and logistics demand remain positive even with warehouse automation pressure."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool result: { bls_projection_window: '2024-2034', occupation_group: '53-0000', long_run_signal: 'continued logistics demand with automation offset', pack_adjustment_thousands: +60 }"]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { admitted: 1, mode: 'with_packs', control_point_thousands: 14050, pack_adjustment_thousands: +60, packed_point_thousands: 14110, resolver_unchanged: 'BLS OEWS first print' }","Control forecast 14.05m + BLS projections pack adjustment +60k = 14.11m."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-transport-material-moving-employment-may-2026\nrunLabel: BLS projections pack\nresolutionDate: 2027-05-14\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-transport-material-moving-employment-may-2026.2025-08-28T10-00-00-04-00.bls-implied-2026-annual-baseline.05bd1e520ab5999d","runId":"run.oews-transport-material-moving-employment-may-2026.2025-08-28T10-00-00-04-00.bls-implied-2026-annual-baseline.05bd1e520ab5999d","predictionId":"oews-transport-material-moving-employment-may-2026","specId":"spec.oews-transport-material-moving-employment-may-2026","runLabel":"BLS-implied 2026 baseline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 3 historical point(s) and explicit outside-view language.","evidence":["BLS does not publish an official May 2026 OEWS forecast. This baseline keeps the annual OEWS resolver but uses the BLS 2024-2034 major-group growth rate as the outside-view annual path."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS-implied annual comparator","BLS does not publish an official May 2026 OEWS forecast. This baseline keeps the annual OEWS resolver but uses the BLS 2024-2034 major-group growth rate as the outside-view annual path."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.2, distribution present, forecast step count 1.","evidence":["Forecast: point 14010, 80% interval [14009.9, 14010.1]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS does not publish an official May 2026 OEWS forecast. This baseline keeps the annual OEWS resolver but uses the BLS 2024-2034 major-group growth rate as the outside-view annual path."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["BLS does not publish an official May 2026 OEWS forecast. This baseline keeps the annual OEWS resolver but uses the BLS 2024-2034 major-group growth rate as the outside-view annual path.","Forecast: point 14010, 80% interval [14009.9, 14010.1]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-transport-material-moving-employment-may-2026\nrunLabel: BLS-implied 2026 baseline\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.cps-business-financial-employment-june-2026.2026-06-21T23-05-00-04-00.d2573c81fc742fd1","runId":"run.cps-business-financial-employment-june-2026.2026-06-21T23-05-00-04-00.d2573c81fc742fd1","predictionId":"cps-business-financial-employment-june-2026","specId":"spec.cps-business-financial-employment-june-2026","runLabel":"CPS fast proxy","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.46,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log absent.","evidence":["This is the fast monthly proxy for the business and financial OEWS group, trading clean SOC annual measurement for a July 2026 read on analyst, accounting, compliance, and finance labor demand. This target resolves on 2026-07-02 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next monthly release, annual OEWS cross-check, threshold questions.","Tool call: bls.cps.table_a19.lookup({ reference_months: [\"May 2025\", \"May 2026\"], row: \"business_financial_operations\", columns: [\"total_16_plus\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · June 2026 CPS Table A-19 first print","This is the fast monthly proxy for the business and financial OEWS group, trading clean SOC annual measurement for a July 2026 read on analyst, accounting, compliance, and finance labor demand. This target resolves on 2026-07-02 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next monthly release, annual OEWS cross-check, threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 880, distribution present, forecast step count 1.","evidence":["The June forecast stays near the May 2026 CPS table value because this monthly household-survey row is noisy and not seasonally adjusted. The point allows a small recovery from May but keeps the interval wide enough for sampling movement and month-specific occupation coding shifts.","Forecast: point 10040, 80% interval [9600, 10480]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The June forecast stays near the May 2026 CPS table value because this monthly household-survey row is noisy and not seasonally adjusted. The point allows a small recovery from May but keeps the interval wide enough for sampling movement and month-specific occupation coding shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The June forecast stays near the May 2026 CPS table value because this monthly household-survey row is noisy and not seasonally adjusted. The point allows a small recovery from May but keeps the interval wide enough for sampling movement and month-specific occupation coding shifts."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The June forecast stays near the May 2026 CPS table value because this monthly household-survey row is noisy and not seasonally adjusted. The point allows a small recovery from May but keeps the interval wide enough for sampling movement and month-specific occupation coding shifts.","Forecast: point 10040, 80% interval [9600, 10480]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: cps-business-financial-employment-june-2026\nrunLabel: CPS fast proxy\nresolutionDate: 2026-07-02\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.cps-computer-math-employment-june-2026.2026-06-21T23-05-00-04-00.514bfdba76ace25f","runId":"run.cps-computer-math-employment-june-2026.2026-06-21T23-05-00-04-00.514bfdba76ace25f","predictionId":"cps-computer-math-employment-june-2026","specId":"spec.cps-computer-math-employment-june-2026","runLabel":"CPS fast proxy","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log absent.","evidence":["This is the fastest BLS occupation readout for software, data, security, and quantitative work while the annual OEWS and long-run projection targets remain pending. This target resolves on 2026-07-02 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next monthly release, annual OEWS cross-check, threshold questions.","Tool call: bls.cps.table_a19.lookup({ reference_months: [\"May 2025\", \"May 2026\"], row: \"computer_mathematical\", columns: [\"total_16_plus\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · June 2026 CPS Table A-19 first print","This is the fastest BLS occupation readout for software, data, security, and quantitative work while the annual OEWS and long-run projection targets remain pending. This target resolves on 2026-07-02 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next monthly release, annual OEWS cross-check, threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 850, distribution present, forecast step count 1.","evidence":["Forecast: point 6920, 80% interval [6500, 7350]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The monthly CPS row already shows strong year-over-year growth in May. The forecast carries that signal into June while avoiding a precise trend extrapolation because CPS occupation cells can move several hundred thousand workers month to month."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The monthly CPS row already shows strong year-over-year growth in May. The forecast carries that signal into June while avoiding a precise trend extrapolation because CPS occupation cells can move several hundred thousand workers month to month.","Forecast: point 6920, 80% interval [6500, 7350]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: cps-computer-math-employment-june-2026\nrunLabel: CPS fast proxy\nresolutionDate: 2026-07-02\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.cps-healthcare-support-employment-june-2026.2026-06-21T23-05-00-04-00.72f6884ba93c164f","runId":"run.cps-healthcare-support-employment-june-2026.2026-06-21T23-05-00-04-00.72f6884ba93c164f","predictionId":"cps-healthcare-support-employment-june-2026","specId":"spec.cps-healthcare-support-employment-june-2026","runLabel":"CPS fast proxy","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.46,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log absent.","evidence":["Healthcare support is the monthly low-substitution benchmark for the occupation automation slate, but the CPS row is noisier than OEWS and can diverge from payroll health-care momentum. This target resolves on 2026-07-02 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next monthly release, annual OEWS cross-check, threshold questions.","Tool call: bls.cps.table_a19.lookup({ reference_months: [\"May 2025\", \"May 2026\"], row: \"healthcare_support\", columns: [\"total_16_plus\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · June 2026 CPS Table A-19 first print","Healthcare support is the monthly low-substitution benchmark for the occupation automation slate, but the CPS row is noisier than OEWS and can diverge from payroll health-care momentum. This target resolves on 2026-07-02 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next monthly release, annual OEWS cross-check, threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 800, distribution present, forecast step count 1.","evidence":["The forecast mostly repeats May because demographic demand is positive but the CPS row weakened year over year. The interval is wide relative to trend because this is a small monthly occupation cell rather than an establishment payroll series.","Forecast: point 5800, 80% interval [5400, 6200]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Healthcare support is the monthly low-substitution benchmark for the occupation automation slate, but the CPS row is noisier than OEWS and can diverge from payroll health-care momentum. This target resolves on 2026-07-02 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next monthly release, annual OEWS cross-check, threshold questions.","The forecast mostly repeats May because demographic demand is positive but the CPS row weakened year over year. The interval is wide relative to trend because this is a small monthly occupation cell rather than an establishment payroll series."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Healthcare support is the monthly low-substitution benchmark for the occupation automation slate, but the CPS row is noisier than OEWS and can diverge from payroll health-care momentum. This target resolves on 2026-07-02 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next monthly release, annual OEWS cross-check, threshold questions.","The forecast mostly repeats May because demographic demand is positive but the CPS row weakened year over year. The interval is wide relative to trend because this is a small monthly occupation cell rather than an establishment payroll series."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The forecast mostly repeats May because demographic demand is positive but the CPS row weakened year over year. The interval is wide relative to trend because this is a small monthly occupation cell rather than an establishment payroll series.","Forecast: point 5800, 80% interval [5400, 6200]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: cps-healthcare-support-employment-june-2026\nrunLabel: CPS fast proxy\nresolutionDate: 2026-07-02\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.cps-office-admin-employment-june-2026.2026-06-21T23-05-00-04-00.32ebfd164a026243","runId":"run.cps-office-admin-employment-june-2026.2026-06-21T23-05-00-04-00.32ebfd164a026243","predictionId":"cps-office-admin-employment-june-2026","specId":"spec.cps-office-admin-employment-june-2026","runLabel":"CPS fast proxy","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.22,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log absent.","evidence":["This gives a near-term read on routine clerical and administrative work before the cleaner OEWS annual estimate resolves. This target resolves on 2026-07-02 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next monthly release, annual OEWS cross-check, threshold questions.","Tool call: bls.cps.table_a19.lookup({ reference_months: [\"May 2025\", \"May 2026\"], row: \"office_administrative_support\", columns: [\"total_16_plus\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · June 2026 CPS Table A-19 first print","This gives a near-term read on routine clerical and administrative work before the cleaner OEWS annual estimate resolves. This target resolves on 2026-07-02 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next monthly release, annual OEWS cross-check, threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1300, distribution present, forecast step count 1.","evidence":["Forecast: point 16300, 80% interval [15650, 16950]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The CPS row rose year over year in May despite the long-run automation concern. The June point stays just below May, treating the monthly increase as noisy rather than reversing the broader office/admin exposure thesis.","Forecast: point 16300, 80% interval [15650, 16950]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: cps-office-admin-employment-june-2026\nrunLabel: CPS fast proxy\nresolutionDate: 2026-07-02\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.cps-production-employment-june-2026.2026-06-21T23-05-00-04-00.7b4ee5a440dfaa75","runId":"run.cps-production-employment-june-2026.2026-06-21T23-05-00-04-00.7b4ee5a440dfaa75","predictionId":"cps-production-employment-june-2026","specId":"spec.cps-production-employment-june-2026","runLabel":"CPS fast proxy","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log absent.","evidence":["Production occupations connect the fast monthly CPS proxy to manufacturing demand, robotics, process control, trade exposure, and goods-sector cyclicality. This target resolves on 2026-07-02 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next monthly release, annual OEWS cross-check, threshold questions.","Tool call: bls.cps.table_a19.lookup({ reference_months: [\"May 2025\", \"May 2026\"], row: \"production\", columns: [\"total_16_plus\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · June 2026 CPS Table A-19 first print","Production occupations connect the fast monthly CPS proxy to manufacturing demand, robotics, process control, trade exposure, and goods-sector cyclicality. This target resolves on 2026-07-02 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next monthly release, annual OEWS cross-check, threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 850, distribution present, forecast step count 1.","evidence":["The central case is essentially flat from May, consistent with a mixed manufacturing picture and modest automation pressure. The interval leaves room for CPS noise and goods-sector month-to-month volatility.","Forecast: point 7900, 80% interval [7500, 8350]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The central case is essentially flat from May, consistent with a mixed manufacturing picture and modest automation pressure. The interval leaves room for CPS noise and goods-sector month-to-month volatility."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The central case is essentially flat from May, consistent with a mixed manufacturing picture and modest automation pressure. The interval leaves room for CPS noise and goods-sector month-to-month volatility.","Forecast: point 7900, 80% interval [7500, 8350]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: cps-production-employment-june-2026\nrunLabel: CPS fast proxy\nresolutionDate: 2026-07-02\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.cps-transport-material-moving-employment-june-2026.2026-06-21T23-05-00-04-00.a340f0bd23559c3f","runId":"run.cps-transport-material-moving-employment-june-2026.2026-06-21T23-05-00-04-00.a340f0bd23559c3f","predictionId":"cps-transport-material-moving-employment-june-2026","specId":"spec.cps-transport-material-moving-employment-june-2026","runLabel":"CPS fast proxy","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.46,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 4 source-context item(s), activity log absent.","evidence":["This is the fast monthly proxy for logistics, warehousing, routing, and autonomy exposure before the annual OEWS occupation table resolves. This target resolves on 2026-07-02 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next monthly release, annual OEWS cross-check, threshold questions.","Tool call: bls.cps.table_a19.lookup({ reference_months: [\"May 2025\", \"May 2026\"], row: \"transportation_material_moving\", columns: [\"total_16_plus\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · June 2026 CPS Table A-19 first print","This is the fast monthly proxy for logistics, warehousing, routing, and autonomy exposure before the annual OEWS occupation table resolves. This target resolves on 2026-07-02 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next monthly release, annual OEWS cross-check, threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1200, distribution present, forecast step count 1.","evidence":["Forecast: point 12100, 80% interval [11500, 12700]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The point holds close to May because logistics demand still looks positive, but warehouse automation and routing productivity keep the center from extrapolating the full year-over-year CPS gain."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The point holds close to May because logistics demand still looks positive, but warehouse automation and routing productivity keep the center from extrapolating the full year-over-year CPS gain."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The point holds close to May because logistics demand still looks positive, but warehouse automation and routing productivity keep the center from extrapolating the full year-over-year CPS gain.","Forecast: point 12100, 80% interval [11500, 12700]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: cps-transport-material-moving-employment-june-2026\nrunLabel: CPS fast proxy\nresolutionDate: 2026-07-02\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bls-business-financial-employment-2034.2026-06-21T22-15-00-04-00.a697fb5e4a16584b","runId":"run.bls-business-financial-employment-2034.2026-06-21T22-15-00-04-00.a697fb5e4a16584b","predictionId":"bls-business-financial-employment-2034","specId":"spec.bls-business-financial-employment-2034","runLabel":"Brier long-run - no BLS pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.46,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":["Recorded agent run · 2034 base-year employment","Tool result: { apples_to_apples: true, same_soc_group: true, same_unit: 'thousands', same_resolution_surface: 'future BLS National Employment Matrix 2034 base-year employment' }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["This is the apples-to-apples long-run target for analyst, compliance, accounting, and finance work: Brier and BLS are both forecasting the same 2034 BLS occupation employment surface. This target resolves on 2035-09-15 under a first-print rule, with an expected ~9 years lag. The same series can also spawn next projection vintage, detailed SOC rows, threshold questions.","Tool call: bls.employment_projections.lookup({ table: \"1.2\", window: \"2024-2034\", occupation: \"13-0000\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["This is the apples-to-apples long-run target for analyst, compliance, accounting, and finance work: Brier and BLS are both forecasting the same 2034 BLS occupation employment surface. This target resolves on 2035-09-15 under a first-print rule, with an expected ~9 years lag. The same series can also spawn next projection vintage, detailed SOC rows, threshold questions.","Tool call: brier.target.check({ target: \"bls.employment_projections.national_occupation_employment.soc_13_0000.2034.actual_first_print\", comparator: \"bls_2024_2034_projection\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2450, distribution present, forecast step count 1.","evidence":["This is the apples-to-apples long-run target for analyst, compliance, accounting, and finance work: Brier and BLS are both forecasting the same 2034 BLS occupation employment surface. This target resolves on 2035-09-15 under a first-print rule, with an expected ~9 years lag. The same series can also spawn next projection vintage, detailed SOC rows, threshold questions.","Forecast: point 11480, 80% interval [10350, 12800]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The no-pack forecast is below the BLS projection because Brier puts more weight on task absorption in back-office analysis, bookkeeping-adjacent work, claims workflows, and compliance review. Demand still grows, but headcount growth is muted relative to the official projection baseline."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The no-pack forecast is below the BLS projection because Brier puts more weight on task absorption in back-office analysis, bookkeeping-adjacent work, claims workflows, and compliance review. Demand still grows, but headcount growth is muted relative to the official projection baseline."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["This is the apples-to-apples long-run target for analyst, compliance, accounting, and finance work: Brier and BLS are both forecasting the same 2034 BLS occupation employment surface. This target resolves on 2035-09-15 under a first-print rule, with an expected ~9 years lag. The same series can also spawn next projection vintage, detailed SOC rows, threshold questions.","The no-pack forecast is below the BLS projection because Brier puts more weight on task absorption in back-office analysis, bookkeeping-adjacent work, claims workflows, and compliance review. Demand still grows, but headcount growth is muted relative to the official projection baseline."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bls-business-financial-employment-2034\nrunLabel: Brier long-run - no BLS pack\nresolutionDate: 2035-09-15\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (3/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bls-business-financial-employment-2034.2026-06-21T22-35-00-04-00.with-bls-employment-projections.e07b8a9684c8dbea","runId":"run.bls-business-financial-employment-2034.2026-06-21T22-35-00-04-00.with-bls-employment-projections.e07b8a9684c8dbea","predictionId":"bls-business-financial-employment-2034","specId":"spec.bls-business-financial-employment-2034","runLabel":"Brier long-run - BLS pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":["This run is apples-to-apples with the published BLS projection: same SOC major group, same employment-in-thousands unit, and same future BLS National Employment Matrix 2034 base-year resolver.","Tool call: brier.pack.apply({ packs: [\"bls-employment-projections-baseline@0.1.0\"], role: \"same_target_baseline\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 4 source-context item(s), activity log absent.","evidence":["BLS projection pack on the 2034 target","This run is apples-to-apples with the published BLS projection: same SOC major group, same employment-in-thousands unit, and same future BLS National Employment Matrix 2034 base-year resolver."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["This run is apples-to-apples with the published BLS projection: same SOC major group, same employment-in-thousands unit, and same future BLS National Employment Matrix 2034 base-year resolver."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2100, distribution present, forecast step count 1.","evidence":["Forecast: point 11710, 80% interval [10650, 12750]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The BLS pack moves the forecast back toward the official 2024-2034 projection, because the BLS matrix still expects broad demand growth for business operations, human resources, logistics, and management analysis despite task-level automation pressure."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { admitted: 1, mode: 'with_packs', no_pack_point_thousands: 11480, pack_adjustment_thousands: +230, packed_point_thousands: 11710, packed_delta_vs_bls_projection_thousands: -138.89999999999964 }","The BLS pack moves the forecast back toward the official 2024-2034 projection, because the BLS matrix still expects broad demand growth for business operations, human resources, logistics, and management analysis despite task-level automation pressure."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bls-business-financial-employment-2034\nrunLabel: Brier long-run - BLS pack\nresolutionDate: 2035-09-15\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bls-business-financial-employment-2034.2025-08-28T10-00-00-04-00.bls-published-2024-2034-projection.63d1843efb4b3dfa","runId":"run.bls-business-financial-employment-2034.2025-08-28T10-00-00-04-00.bls-published-2024-2034-projection.63d1843efb4b3dfa","predictionId":"bls-business-financial-employment-2034","specId":"spec.bls-business-financial-employment-2034","runLabel":"BLS published projection","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.22,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":["BLS published baseline"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 1 source-context item(s), activity log absent.","evidence":["BLS published baseline","BLS publishes a point projection, not a full public uncertainty distribution. Thesis records it with an effectively point-mass display interval so it can sit beside the Brier distributions and later be scored on the same target."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["BLS published baseline"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.2, distribution present, forecast step count 1.","evidence":["BLS publishes a point projection, not a full public uncertainty distribution. Thesis records it with an effectively point-mass display interval so it can sit beside the Brier distributions and later be scored on the same target.","Forecast: point 11848.9, 80% interval [11848.8, 11849]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["BLS publishes a point projection, not a full public uncertainty distribution. Thesis records it with an effectively point-mass display interval so it can sit beside the Brier distributions and later be scored on the same target."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["BLS publishes a point projection, not a full public uncertainty distribution. Thesis records it with an effectively point-mass display interval so it can sit beside the Brier distributions and later be scored on the same target.","Forecast: point 11848.9, 80% interval [11848.8, 11849]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bls-business-financial-employment-2034\nrunLabel: BLS published projection\nresolutionDate: 2035-09-15\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bls-computer-math-employment-2034.2026-06-21T22-15-00-04-00.9e0211c16cc46dee","runId":"run.bls-computer-math-employment-2034.2026-06-21T22-15-00-04-00.9e0211c16cc46dee","predictionId":"bls-computer-math-employment-2034","specId":"spec.bls-computer-math-employment-2034","runLabel":"Brier long-run - no BLS pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":["Recorded agent run · 2034 base-year employment","Tool result: { apples_to_apples: true, same_soc_group: true, same_unit: 'thousands', same_resolution_surface: 'future BLS National Employment Matrix 2034 base-year employment' }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["This target tests whether Brier expects AI to be mainly labor-saving in software work or demand-expanding through AI infrastructure, security, data, and integration work. This target resolves on 2035-09-15 under a first-print rule, with an expected ~9 years lag. The same series can also spawn next projection vintage, detailed SOC rows, threshold questions.","Tool call: bls.employment_projections.lookup({ table: \"1.2\", window: \"2024-2034\", occupation: \"15-0000\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["This target tests whether Brier expects AI to be mainly labor-saving in software work or demand-expanding through AI infrastructure, security, data, and integration work. This target resolves on 2035-09-15 under a first-print rule, with an expected ~9 years lag. The same series can also spawn next projection vintage, detailed SOC rows, threshold questions.","Tool call: brier.target.check({ target: \"bls.employment_projections.national_occupation_employment.soc_15_0000.2034.actual_first_print\", comparator: \"bls_2024_2034_projection\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2600, distribution present, forecast step count 1.","evidence":["This target tests whether Brier expects AI to be mainly labor-saving in software work or demand-expanding through AI infrastructure, security, data, and integration work. This target resolves on 2035-09-15 under a first-print rule, with an expected ~9 years lag. The same series can also spawn next projection vintage, detailed SOC rows, threshold questions.","The no-pack forecast is above BLS because Brier's scenario assigns a larger demand-expansion effect to AI infrastructure, security, data engineering, and model-integration work than the official baseline appears to. The lower tail still allows direct coding automation and offshoring to dominate."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The no-pack forecast is above BLS because Brier's scenario assigns a larger demand-expansion effect to AI infrastructure, security, data engineering, and model-integration work than the official baseline appears to. The lower tail still allows direct coding automation and offshoring to dominate."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The no-pack forecast is above BLS because Brier's scenario assigns a larger demand-expansion effect to AI infrastructure, security, data engineering, and model-integration work than the official baseline appears to. The lower tail still allows direct coding automation and offshoring to dominate.","Forecast: point 6300, 80% interval [5000, 7600]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bls-computer-math-employment-2034\nrunLabel: Brier long-run - no BLS pack\nresolutionDate: 2035-09-15\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bls-computer-math-employment-2034.2026-06-21T22-35-00-04-00.with-bls-employment-projections.b4e6fd9f80bc4321","runId":"run.bls-computer-math-employment-2034.2026-06-21T22-35-00-04-00.with-bls-employment-projections.b4e6fd9f80bc4321","predictionId":"bls-computer-math-employment-2034","specId":"spec.bls-computer-math-employment-2034","runLabel":"Brier long-run - BLS pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.46,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":["This run is apples-to-apples with the published BLS projection: same SOC major group, same employment-in-thousands unit, and same future BLS National Employment Matrix 2034 base-year resolver.","Tool call: brier.pack.apply({ packs: [\"bls-employment-projections-baseline@0.1.0\"], role: \"same_target_baseline\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 4 source-context item(s), activity log absent.","evidence":["BLS projection pack on the 2034 target","This run is apples-to-apples with the published BLS projection: same SOC major group, same employment-in-thousands unit, and same future BLS National Employment Matrix 2034 base-year resolver."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["This run is apples-to-apples with the published BLS projection: same SOC major group, same employment-in-thousands unit, and same future BLS National Employment Matrix 2034 base-year resolver."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2130, distribution present, forecast step count 1.","evidence":["The BLS pack pulls the center closer to the official projection. It tempers the AI-demand upside by anchoring to BLS's 10.1 percent projected growth for the major group, while preserving a wider upside tail than BLS's point estimate.","Forecast: point 6120, 80% interval [5120, 7250]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { admitted: 1, mode: 'with_packs', no_pack_point_thousands: 6300, pack_adjustment_thousands: -180, packed_point_thousands: 6120, packed_delta_vs_bls_projection_thousands: +157.69999999999982 }","The BLS pack pulls the center closer to the official projection. It tempers the AI-demand upside by anchoring to BLS's 10.1 percent projected growth for the major group, while preserving a wider upside tail than BLS's point estimate."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bls-computer-math-employment-2034\nrunLabel: Brier long-run - BLS pack\nresolutionDate: 2035-09-15\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (3/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bls-computer-math-employment-2034.2025-08-28T10-00-00-04-00.bls-published-2024-2034-projection.4c20d559b9a44ac7","runId":"run.bls-computer-math-employment-2034.2025-08-28T10-00-00-04-00.bls-published-2024-2034-projection.4c20d559b9a44ac7","predictionId":"bls-computer-math-employment-2034","specId":"spec.bls-computer-math-employment-2034","runLabel":"BLS published projection","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.22,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":["BLS published baseline"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 1 source-context item(s), activity log absent.","evidence":["BLS published baseline","BLS publishes a point projection, not a full public uncertainty distribution. Thesis records it with an effectively point-mass display interval so it can sit beside the Brier distributions and later be scored on the same target."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["BLS published baseline"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.2, distribution present, forecast step count 1.","evidence":["BLS publishes a point projection, not a full public uncertainty distribution. Thesis records it with an effectively point-mass display interval so it can sit beside the Brier distributions and later be scored on the same target.","Forecast: point 5962.3, 80% interval [5962.2, 5962.400000000001]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["BLS publishes a point projection, not a full public uncertainty distribution. Thesis records it with an effectively point-mass display interval so it can sit beside the Brier distributions and later be scored on the same target."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["BLS publishes a point projection, not a full public uncertainty distribution. Thesis records it with an effectively point-mass display interval so it can sit beside the Brier distributions and later be scored on the same target.","Forecast: point 5962.3, 80% interval [5962.2, 5962.400000000001]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bls-computer-math-employment-2034\nrunLabel: BLS published projection\nresolutionDate: 2035-09-15\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bls-healthcare-support-employment-2034.2026-06-21T22-15-00-04-00.0661fa13ffa89263","runId":"run.bls-healthcare-support-employment-2034.2026-06-21T22-15-00-04-00.0661fa13ffa89263","predictionId":"bls-healthcare-support-employment-2034","specId":"spec.bls-healthcare-support-employment-2034","runLabel":"Brier long-run - no BLS pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.43,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":["Recorded agent run · 2034 base-year employment","Tool result: { apples_to_apples: true, same_soc_group: true, same_unit: 'thousands', same_resolution_surface: 'future BLS National Employment Matrix 2034 base-year employment' }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Healthcare support is the low-substitution benchmark for the automation slate: demand is demographic and physical-care intensive, so it checks whether Brier over-applies software automation to hands-on work. This target resolves on 2035-09-15 under a first-print rule, with an expected ~9 years lag. The same series can also spawn next projection vintage, detailed SOC rows, threshold questions.","Tool call: bls.employment_projections.lookup({ table: \"1.2\", window: \"2024-2034\", occupation: \"31-0000\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Healthcare support is the low-substitution benchmark for the automation slate: demand is demographic and physical-care intensive, so it checks whether Brier over-applies software automation to hands-on work. This target resolves on 2035-09-15 under a first-print rule, with an expected ~9 years lag. The same series can also spawn next projection vintage, detailed SOC rows, threshold questions.","Tool call: brier.target.check({ target: \"bls.employment_projections.national_occupation_employment.soc_31_0000.2034.actual_first_print\", comparator: \"bls_2024_2034_projection\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2250, distribution present, forecast step count 1.","evidence":["Healthcare support is the low-substitution benchmark for the automation slate: demand is demographic and physical-care intensive, so it checks whether Brier over-applies software automation to hands-on work. This target resolves on 2035-09-15 under a first-print rule, with an expected ~9 years lag. The same series can also spawn next projection vintage, detailed SOC rows, threshold questions.","The no-pack forecast is slightly above BLS because Brier puts more weight on care demand and home-based support needs than on software substitution. The main uncertainty is staffing supply and public-payment pressure, not AI replacing the core work."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: { exposure: 'low_substitution', demographic_pressure: 'high', bls_2034_projection_thousands: 8971.1, brier_no_pack_delta_vs_bls_thousands: +128.9 }","The no-pack forecast is slightly above BLS because Brier puts more weight on care demand and home-based support needs than on software substitution. The main uncertainty is staffing supply and public-payment pressure, not AI replacing the core work."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The no-pack forecast is slightly above BLS because Brier puts more weight on care demand and home-based support needs than on software substitution. The main uncertainty is staffing supply and public-payment pressure, not AI replacing the core work."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The no-pack forecast is slightly above BLS because Brier puts more weight on care demand and home-based support needs than on software substitution. The main uncertainty is staffing supply and public-payment pressure, not AI replacing the core work.","Forecast: point 9100, 80% interval [8100, 10350]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bls-healthcare-support-employment-2034\nrunLabel: Brier long-run - no BLS pack\nresolutionDate: 2035-09-15\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bls-healthcare-support-employment-2034.2026-06-21T22-35-00-04-00.with-bls-employment-projections.85d3eeb90af8017c","runId":"run.bls-healthcare-support-employment-2034.2026-06-21T22-35-00-04-00.with-bls-employment-projections.85d3eeb90af8017c","predictionId":"bls-healthcare-support-employment-2034","specId":"spec.bls-healthcare-support-employment-2034","runLabel":"Brier long-run - BLS pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":["This run is apples-to-apples with the published BLS projection: same SOC major group, same employment-in-thousands unit, and same future BLS National Employment Matrix 2034 base-year resolver.","Tool call: brier.pack.apply({ packs: [\"bls-employment-projections-baseline@0.1.0\"], role: \"same_target_baseline\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 4 source-context item(s), activity log absent.","evidence":["BLS projection pack on the 2034 target","This run is apples-to-apples with the published BLS projection: same SOC major group, same employment-in-thousands unit, and same future BLS National Employment Matrix 2034 base-year resolver."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["This run is apples-to-apples with the published BLS projection: same SOC major group, same employment-in-thousands unit, and same future BLS National Employment Matrix 2034 base-year resolver."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1750, distribution present, forecast step count 1.","evidence":["Forecast: point 9020, 80% interval [8150, 9900]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { admitted: 1, mode: 'with_packs', no_pack_point_thousands: 9100, pack_adjustment_thousands: -80, packed_point_thousands: 9020, packed_delta_vs_bls_projection_thousands: +48.899999999999636 }","The BLS pack centers the forecast close to the official 12.4 percent projected growth path and trims some upside from unconstrained care demand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bls-healthcare-support-employment-2034\nrunLabel: Brier long-run - BLS pack\nresolutionDate: 2035-09-15\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bls-healthcare-support-employment-2034.2025-08-28T10-00-00-04-00.bls-published-2024-2034-projection.70060f66f473b9e3","runId":"run.bls-healthcare-support-employment-2034.2025-08-28T10-00-00-04-00.bls-published-2024-2034-projection.70060f66f473b9e3","predictionId":"bls-healthcare-support-employment-2034","specId":"spec.bls-healthcare-support-employment-2034","runLabel":"BLS published projection","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.22,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":["BLS published baseline"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 1 source-context item(s), activity log absent.","evidence":["BLS published baseline","BLS publishes a point projection, not a full public uncertainty distribution. Thesis records it with an effectively point-mass display interval so it can sit beside the Brier distributions and later be scored on the same target."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["BLS published baseline"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.2, distribution present, forecast step count 1.","evidence":["BLS publishes a point projection, not a full public uncertainty distribution. Thesis records it with an effectively point-mass display interval so it can sit beside the Brier distributions and later be scored on the same target.","Forecast: point 8971.1, 80% interval [8971, 8971.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["BLS publishes a point projection, not a full public uncertainty distribution. Thesis records it with an effectively point-mass display interval so it can sit beside the Brier distributions and later be scored on the same target."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["BLS publishes a point projection, not a full public uncertainty distribution. Thesis records it with an effectively point-mass display interval so it can sit beside the Brier distributions and later be scored on the same target.","Forecast: point 8971.1, 80% interval [8971, 8971.2]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bls-healthcare-support-employment-2034\nrunLabel: BLS published projection\nresolutionDate: 2035-09-15\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bls-office-admin-employment-2034.2026-06-21T22-15-00-04-00.1685d17d767bb3d8","runId":"run.bls-office-admin-employment-2034.2026-06-21T22-15-00-04-00.1685d17d767bb3d8","predictionId":"bls-office-admin-employment-2034","specId":"spec.bls-office-admin-employment-2034","runLabel":"Brier long-run - no BLS pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.05,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":["Recorded agent run · 2034 base-year employment","Tool result: { apples_to_apples: true, same_soc_group: true, same_unit: 'thousands', same_resolution_surface: 'future BLS National Employment Matrix 2034 base-year employment' }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["This is the largest clean long-run test for routine information-work automation: scheduling, records, billing, call handling, form processing, and clerical coordination all map directly to software and AI tools. This target resolves on 2035-09-15 under a first-print rule, with an expected ~9 years lag. The same series can also spawn next projection vintage, detailed SOC rows, threshold questions.","Tool call: bls.employment_projections.lookup({ table: \"1.2\", window: \"2024-2034\", occupation: \"43-0000\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["This is the largest clean long-run test for routine information-work automation: scheduling, records, billing, call handling, form processing, and clerical coordination all map directly to software and AI tools. This target resolves on 2035-09-15 under a first-print rule, with an expected ~9 years lag. The same series can also spawn next projection vintage, detailed SOC rows, threshold questions.","Tool call: brier.target.check({ target: \"bls.employment_projections.national_occupation_employment.soc_43_0000.2034.actual_first_print\", comparator: \"bls_2024_2034_projection\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4900, distribution present, forecast step count 1.","evidence":["This is the largest clean long-run test for routine information-work automation: scheduling, records, billing, call handling, form processing, and clerical coordination all map directly to software and AI tools. This target resolves on 2035-09-15 under a first-print rule, with an expected ~9 years lag. The same series can also spawn next projection vintage, detailed SOC rows, threshold questions.","Forecast: point 17200, 80% interval [14500, 19400]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The no-pack forecast is materially below the BLS projection. Brier treats office and administrative support as the most exposed large group: document intake, scheduling, billing, customer-contact triage, and records work can be automated or bundled into higher-output roles.","Forecast: point 17200, 80% interval [14500, 19400]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bls-office-admin-employment-2034\nrunLabel: Brier long-run - no BLS pack\nresolutionDate: 2035-09-15\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bls-office-admin-employment-2034.2026-06-21T22-35-00-04-00.with-bls-employment-projections.33915526d5e5e81d","runId":"run.bls-office-admin-employment-2034.2026-06-21T22-35-00-04-00.with-bls-employment-projections.33915526d5e5e81d","predictionId":"bls-office-admin-employment-2034","specId":"spec.bls-office-admin-employment-2034","runLabel":"Brier long-run - BLS pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":["This run is apples-to-apples with the published BLS projection: same SOC major group, same employment-in-thousands unit, and same future BLS National Employment Matrix 2034 base-year resolver.","Tool call: brier.pack.apply({ packs: [\"bls-employment-projections-baseline@0.1.0\"], role: \"same_target_baseline\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 4 source-context item(s), activity log absent.","evidence":["BLS projection pack on the 2034 target","This run is apples-to-apples with the published BLS projection: same SOC major group, same employment-in-thousands unit, and same future BLS National Employment Matrix 2034 base-year resolver."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["This run is apples-to-apples with the published BLS projection: same SOC major group, same employment-in-thousands unit, and same future BLS National Employment Matrix 2034 base-year resolver."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4150, distribution present, forecast step count 1.","evidence":["Forecast: point 17850, 80% interval [15300, 19450]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The BLS pack raises the center because the official baseline already includes a decline but not a sharp automation break. The packed run still stays below BLS, preserving Brier's stronger substitution view."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The BLS pack raises the center because the official baseline already includes a decline but not a sharp automation break. The packed run still stays below BLS, preserving Brier's stronger substitution view."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { admitted: 1, mode: 'with_packs', no_pack_point_thousands: 17200, pack_adjustment_thousands: +650, packed_point_thousands: 17850, packed_delta_vs_bls_projection_thousands: -713.2999999999993 }","Forecast: point 17850, 80% interval [15300, 19450]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bls-office-admin-employment-2034\nrunLabel: Brier long-run - BLS pack\nresolutionDate: 2035-09-15\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bls-office-admin-employment-2034.2025-08-28T10-00-00-04-00.bls-published-2024-2034-projection.0e92d0831bb340b0","runId":"run.bls-office-admin-employment-2034.2025-08-28T10-00-00-04-00.bls-published-2024-2034-projection.0e92d0831bb340b0","predictionId":"bls-office-admin-employment-2034","specId":"spec.bls-office-admin-employment-2034","runLabel":"BLS published projection","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.22,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":["BLS published baseline"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 1 source-context item(s), activity log absent.","evidence":["BLS published baseline","BLS publishes a point projection, not a full public uncertainty distribution. Thesis records it with an effectively point-mass display interval so it can sit beside the Brier distributions and later be scored on the same target."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["BLS published baseline"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.2, distribution present, forecast step count 1.","evidence":["BLS publishes a point projection, not a full public uncertainty distribution. Thesis records it with an effectively point-mass display interval so it can sit beside the Brier distributions and later be scored on the same target.","Forecast: point 18563.3, 80% interval [18563.2, 18563.399999999998]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["BLS publishes a point projection, not a full public uncertainty distribution. Thesis records it with an effectively point-mass display interval so it can sit beside the Brier distributions and later be scored on the same target."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["BLS publishes a point projection, not a full public uncertainty distribution. Thesis records it with an effectively point-mass display interval so it can sit beside the Brier distributions and later be scored on the same target.","Forecast: point 18563.3, 80% interval [18563.2, 18563.399999999998]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bls-office-admin-employment-2034\nrunLabel: BLS published projection\nresolutionDate: 2035-09-15\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bls-production-employment-2034.2026-06-21T22-15-00-04-00.be37faf3a522ca75","runId":"run.bls-production-employment-2034.2026-06-21T22-15-00-04-00.be37faf3a522ca75","predictionId":"bls-production-employment-2034","specId":"spec.bls-production-employment-2034","runLabel":"Brier long-run - no BLS pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.32,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":["Recorded agent run · 2034 base-year employment","Tool result: { apples_to_apples: true, same_soc_group: true, same_unit: 'thousands', same_resolution_surface: 'future BLS National Employment Matrix 2034 base-year employment' }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Production work ties the task-automation literature to robotics, process control, reshoring, trade, and goods demand rather than only white-collar software substitution. This target resolves on 2035-09-15 under a first-print rule, with an expected ~9 years lag. The same series can also spawn next projection vintage, detailed SOC rows, threshold questions.","Tool call: bls.employment_projections.lookup({ table: \"1.2\", window: \"2024-2034\", occupation: \"51-0000\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Production work ties the task-automation literature to robotics, process control, reshoring, trade, and goods demand rather than only white-collar software substitution. This target resolves on 2035-09-15 under a first-print rule, with an expected ~9 years lag. The same series can also spawn next projection vintage, detailed SOC rows, threshold questions.","Tool call: brier.target.check({ target: \"bls.employment_projections.national_occupation_employment.soc_51_0000.2034.actual_first_print\", comparator: \"bls_2024_2034_projection\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2050, distribution present, forecast step count 1.","evidence":["Production work ties the task-automation literature to robotics, process control, reshoring, trade, and goods demand rather than only white-collar software substitution. This target resolves on 2035-09-15 under a first-print rule, with an expected ~9 years lag. The same series can also spawn next projection vintage, detailed SOC rows, threshold questions.","Forecast: point 8550, 80% interval [7600, 9650]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The no-pack forecast is below BLS because Brier expects robotics, process control, and software-mediated production planning to continue reducing labor intensity in routine production roles, even if reshoring supports output."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The no-pack forecast is below BLS because Brier expects robotics, process control, and software-mediated production planning to continue reducing labor intensity in routine production roles, even if reshoring supports output.","Forecast: point 8550, 80% interval [7600, 9650]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bls-production-employment-2034\nrunLabel: Brier long-run - no BLS pack\nresolutionDate: 2035-09-15\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bls-production-employment-2034.2026-06-21T22-35-00-04-00.with-bls-employment-projections.de6fb833a361b8e3","runId":"run.bls-production-employment-2034.2026-06-21T22-35-00-04-00.with-bls-employment-projections.de6fb833a361b8e3","predictionId":"bls-production-employment-2034","specId":"spec.bls-production-employment-2034","runLabel":"Brier long-run - BLS pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.46,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":["This run is apples-to-apples with the published BLS projection: same SOC major group, same employment-in-thousands unit, and same future BLS National Employment Matrix 2034 base-year resolver.","Tool call: brier.pack.apply({ packs: [\"bls-employment-projections-baseline@0.1.0\"], role: \"same_target_baseline\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 4 source-context item(s), activity log absent.","evidence":["BLS projection pack on the 2034 target","This run is apples-to-apples with the published BLS projection: same SOC major group, same employment-in-thousands unit, and same future BLS National Employment Matrix 2034 base-year resolver."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["This run is apples-to-apples with the published BLS projection: same SOC major group, same employment-in-thousands unit, and same future BLS National Employment Matrix 2034 base-year resolver."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1850, distribution present, forecast step count 1.","evidence":["The BLS pack moderates that decline by anchoring to the official projection's near-flat production path, while still preserving Brier's downside skew from automation and goods-cycle risk.","Forecast: point 8750, 80% interval [7800, 9650]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The BLS pack moderates that decline by anchoring to the official projection's near-flat production path, while still preserving Brier's downside skew from automation and goods-cycle risk."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { admitted: 1, mode: 'with_packs', no_pack_point_thousands: 8550, pack_adjustment_thousands: +200, packed_point_thousands: 8750, packed_delta_vs_bls_projection_thousands: -151.60000000000036 }","Forecast: point 8750, 80% interval [7800, 9650]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bls-production-employment-2034\nrunLabel: Brier long-run - BLS pack\nresolutionDate: 2035-09-15\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (3/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bls-production-employment-2034.2025-08-28T10-00-00-04-00.bls-published-2024-2034-projection.c8ccd3e4d9ba6586","runId":"run.bls-production-employment-2034.2025-08-28T10-00-00-04-00.bls-published-2024-2034-projection.c8ccd3e4d9ba6586","predictionId":"bls-production-employment-2034","specId":"spec.bls-production-employment-2034","runLabel":"BLS published projection","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.22,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":["BLS published baseline"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 1 source-context item(s), activity log absent.","evidence":["BLS published baseline","BLS publishes a point projection, not a full public uncertainty distribution. Thesis records it with an effectively point-mass display interval so it can sit beside the Brier distributions and later be scored on the same target."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["BLS published baseline"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.2, distribution present, forecast step count 1.","evidence":["BLS publishes a point projection, not a full public uncertainty distribution. Thesis records it with an effectively point-mass display interval so it can sit beside the Brier distributions and later be scored on the same target.","Forecast: point 8901.6, 80% interval [8901.5, 8901.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["BLS publishes a point projection, not a full public uncertainty distribution. Thesis records it with an effectively point-mass display interval so it can sit beside the Brier distributions and later be scored on the same target."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["BLS publishes a point projection, not a full public uncertainty distribution. Thesis records it with an effectively point-mass display interval so it can sit beside the Brier distributions and later be scored on the same target.","Forecast: point 8901.6, 80% interval [8901.5, 8901.7]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bls-production-employment-2034\nrunLabel: BLS published projection\nresolutionDate: 2035-09-15\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bls-transport-material-moving-employment-2034.2026-06-21T22-15-00-04-00.fc3e29eeb152f266","runId":"run.bls-transport-material-moving-employment-2034.2026-06-21T22-15-00-04-00.fc3e29eeb152f266","predictionId":"bls-transport-material-moving-employment-2034","specId":"spec.bls-transport-material-moving-employment-2034","runLabel":"Brier long-run - no BLS pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.43,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":["Recorded agent run · 2034 base-year employment","Tool result: { apples_to_apples: true, same_soc_group: true, same_unit: 'thousands', same_resolution_surface: 'future BLS National Employment Matrix 2034 base-year employment' }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Transportation and material moving tests whether warehouse automation, routing software, and partial autonomy reduce labor demand enough to offset logistics volume growth. This target resolves on 2035-09-15 under a first-print rule, with an expected ~9 years lag. The same series can also spawn next projection vintage, detailed SOC rows, threshold questions.","Tool call: bls.employment_projections.lookup({ table: \"1.2\", window: \"2024-2034\", occupation: \"53-0000\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Transportation and material moving tests whether warehouse automation, routing software, and partial autonomy reduce labor demand enough to offset logistics volume growth. This target resolves on 2035-09-15 under a first-print rule, with an expected ~9 years lag. The same series can also spawn next projection vintage, detailed SOC rows, threshold questions.","Tool call: brier.target.check({ target: \"bls.employment_projections.national_occupation_employment.soc_53_0000.2034.actual_first_print\", comparator: \"bls_2024_2034_projection\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3600, distribution present, forecast step count 1.","evidence":["Transportation and material moving tests whether warehouse automation, routing software, and partial autonomy reduce labor demand enough to offset logistics volume growth. This target resolves on 2035-09-15 under a first-print rule, with an expected ~9 years lag. The same series can also spawn next projection vintage, detailed SOC rows, threshold questions.","Forecast: point 14250, 80% interval [12500, 16100]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The no-pack forecast is below BLS because Brier expects warehouse automation, route optimization, and limited autonomy to lower labor per unit of goods movement. It does not assume full driver displacement by 2034."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["Transportation and material moving tests whether warehouse automation, routing software, and partial autonomy reduce labor demand enough to offset logistics volume growth. This target resolves on 2035-09-15 under a first-print rule, with an expected ~9 years lag. The same series can also spawn next projection vintage, detailed SOC rows, threshold questions."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The no-pack forecast is below BLS because Brier expects warehouse automation, route optimization, and limited autonomy to lower labor per unit of goods movement. It does not assume full driver displacement by 2034.","Forecast: point 14250, 80% interval [12500, 16100]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bls-transport-material-moving-employment-2034\nrunLabel: Brier long-run - no BLS pack\nresolutionDate: 2035-09-15\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bls-transport-material-moving-employment-2034.2026-06-21T22-35-00-04-00.with-bls-employment-projections.fb0a589ed4ac60de","runId":"run.bls-transport-material-moving-employment-2034.2026-06-21T22-35-00-04-00.with-bls-employment-projections.fb0a589ed4ac60de","predictionId":"bls-transport-material-moving-employment-2034","specId":"spec.bls-transport-material-moving-employment-2034","runLabel":"Brier long-run - BLS pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":["This run is apples-to-apples with the published BLS projection: same SOC major group, same employment-in-thousands unit, and same future BLS National Employment Matrix 2034 base-year resolver.","Tool call: brier.pack.apply({ packs: [\"bls-employment-projections-baseline@0.1.0\"], role: \"same_target_baseline\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 4 source-context item(s), activity log absent.","evidence":["BLS projection pack on the 2034 target","This run is apples-to-apples with the published BLS projection: same SOC major group, same employment-in-thousands unit, and same future BLS National Employment Matrix 2034 base-year resolver."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["This run is apples-to-apples with the published BLS projection: same SOC major group, same employment-in-thousands unit, and same future BLS National Employment Matrix 2034 base-year resolver."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3350, distribution present, forecast step count 1.","evidence":["Forecast: point 14580, 80% interval [12800, 16150]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The BLS pack raises the center toward the official projection's continued logistics growth, while keeping the forecast below BLS because automation pressure remains a meaningful offset."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The BLS pack raises the center toward the official projection's continued logistics growth, while keeping the forecast below BLS because automation pressure remains a meaningful offset."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { admitted: 1, mode: 'with_packs', no_pack_point_thousands: 14250, pack_adjustment_thousands: +330, packed_point_thousands: 14580, packed_delta_vs_bls_projection_thousands: -204.39999999999964 }","The BLS pack raises the center toward the official projection's continued logistics growth, while keeping the forecast below BLS because automation pressure remains a meaningful offset."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bls-transport-material-moving-employment-2034\nrunLabel: Brier long-run - BLS pack\nresolutionDate: 2035-09-15\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.bls-transport-material-moving-employment-2034.2025-08-28T10-00-00-04-00.bls-published-2024-2034-projection.60d45ce23607ccd3","runId":"run.bls-transport-material-moving-employment-2034.2025-08-28T10-00-00-04-00.bls-published-2024-2034-projection.60d45ce23607ccd3","predictionId":"bls-transport-material-moving-employment-2034","specId":"spec.bls-transport-material-moving-employment-2034","runLabel":"BLS published projection","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.22,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":["BLS published baseline"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 1 source-context item(s), activity log absent.","evidence":["BLS published baseline","BLS publishes a point projection, not a full public uncertainty distribution. Thesis records it with an effectively point-mass display interval so it can sit beside the Brier distributions and later be scored on the same target."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["BLS published baseline"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.2, distribution present, forecast step count 1.","evidence":["BLS publishes a point projection, not a full public uncertainty distribution. Thesis records it with an effectively point-mass display interval so it can sit beside the Brier distributions and later be scored on the same target.","Forecast: point 14784.4, 80% interval [14784.3, 14784.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["BLS publishes a point projection, not a full public uncertainty distribution. Thesis records it with an effectively point-mass display interval so it can sit beside the Brier distributions and later be scored on the same target."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["BLS publishes a point projection, not a full public uncertainty distribution. Thesis records it with an effectively point-mass display interval so it can sit beside the Brier distributions and later be scored on the same target.","Forecast: point 14784.4, 80% interval [14784.3, 14784.5]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: bls-transport-material-moving-employment-2034\nrunLabel: BLS published projection\nresolutionDate: 2035-09-15\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-management-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.22b9ec3a77067187","runId":"run.oews-management-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.22b9ec3a77067187","predictionId":"oews-management-10th-percentile-wage-may-2026","specId":"spec.oews-management-10th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Management wages help distinguish broad nominal wage pressure from composition effects in higher-paid supervisory and executive work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"11-0000\", statistic: \"p10\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Management wages help distinguish broad nominal wage pressure from composition effects in higher-paid supervisory and executive work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000011000011\", release: \"May 2025\", datatype: \"Annual 10th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Management wages help distinguish broad nominal wage pressure from composition effects in higher-paid supervisory and executive work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6400, distribution present, forecast step count 1.","evidence":["Management wages help distinguish broad nominal wage pressure from composition effects in higher-paid supervisory and executive work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is steady managerial pay growth and a slightly higher-skill occupational mix. The lower tail covers weaker white-collar hiring and margin pressure in professional services."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Management wages help distinguish broad nominal wage pressure from composition effects in higher-paid supervisory and executive work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is steady managerial pay growth and a slightly higher-skill occupational mix. The lower tail covers weaker white-collar hiring and margin pressure in professional services."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 10th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is steady managerial pay growth and a slightly higher-skill occupational mix. The lower tail covers weaker white-collar hiring and margin pressure in professional services."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-management-10th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-management-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.18b300c77b984f2b","runId":"run.oews-management-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.18b300c77b984f2b","predictionId":"oews-management-10th-percentile-wage-may-2026","specId":"spec.oews-management-10th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $60,130."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_11_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_11_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 60130, 80% interval [59630, 60630]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 60130, 80% interval [59630, 60630]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-management-10th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-management-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.d046e1aaba58f03e","runId":"run.oews-management-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.d046e1aaba58f03e","predictionId":"oews-management-25th-percentile-wage-may-2026","specId":"spec.oews-management-25th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Management wages help distinguish broad nominal wage pressure from composition effects in higher-paid supervisory and executive work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"11-0000\", statistic: \"p25\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Management wages help distinguish broad nominal wage pressure from composition effects in higher-paid supervisory and executive work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000011000012\", release: \"May 2025\", datatype: \"Annual 25th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Management wages help distinguish broad nominal wage pressure from composition effects in higher-paid supervisory and executive work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 8800, distribution present, forecast step count 1.","evidence":["Management wages help distinguish broad nominal wage pressure from composition effects in higher-paid supervisory and executive work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is steady managerial pay growth and a slightly higher-skill occupational mix. The lower tail covers weaker white-collar hiring and margin pressure in professional services."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Management wages help distinguish broad nominal wage pressure from composition effects in higher-paid supervisory and executive work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is steady managerial pay growth and a slightly higher-skill occupational mix. The lower tail covers weaker white-collar hiring and margin pressure in professional services."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 25th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is steady managerial pay growth and a slightly higher-skill occupational mix. The lower tail covers weaker white-collar hiring and margin pressure in professional services."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-management-25th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-management-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.62fdb4cfc7594b0a","runId":"run.oews-management-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.62fdb4cfc7594b0a","predictionId":"oews-management-25th-percentile-wage-may-2026","specId":"spec.oews-management-25th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $82,970."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_11_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_11_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 82970, 80% interval [82470, 83470]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 82970, 80% interval [82470, 83470]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-management-25th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-management-median-wage-may-2026.2026-06-21T13-35-00-04-00.bcbb8439bd20a3ff","runId":"run.oews-management-median-wage-may-2026.2026-06-21T13-35-00-04-00.bcbb8439bd20a3ff","predictionId":"oews-management-median-wage-may-2026","specId":"spec.oews-management-median-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Management wages help distinguish broad nominal wage pressure from composition effects in higher-paid supervisory and executive work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000011000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Management wages help distinguish broad nominal wage pressure from composition effects in higher-paid supervisory and executive work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000011000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Management wages help distinguish broad nominal wage pressure from composition effects in higher-paid supervisory and executive work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 13500, distribution present, forecast step count 1.","evidence":["Management wages help distinguish broad nominal wage pressure from composition effects in higher-paid supervisory and executive work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is steady managerial pay growth and a slightly higher-skill occupational mix. The lower tail covers weaker white-collar hiring and margin pressure in professional services."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Management wages help distinguish broad nominal wage pressure from composition effects in higher-paid supervisory and executive work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is steady managerial pay growth and a slightly higher-skill occupational mix. The lower tail covers weaker white-collar hiring and margin pressure in professional services."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual median wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is steady managerial pay growth and a slightly higher-skill occupational mix. The lower tail covers weaker white-collar hiring and margin pressure in professional services."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-management-median-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-management-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.e0285fc1002df004","runId":"run.oews-management-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.e0285fc1002df004","predictionId":"oews-management-median-wage-may-2026","specId":"spec.oews-management-median-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_11_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_11_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_11_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 126520, 80% interval [126020, 127020]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 126520, 80% interval [126020, 127020]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-management-median-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-management-mean-wage-may-2026.2026-06-21T13-35-00-04-00.c7e678f85066e123","runId":"run.oews-management-mean-wage-may-2026.2026-06-21T13-35-00-04-00.c7e678f85066e123","predictionId":"oews-management-mean-wage-may-2026","specId":"spec.oews-management-mean-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Management wages help distinguish broad nominal wage pressure from composition effects in higher-paid supervisory and executive work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"11-0000\", statistic: \"mean\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Management wages help distinguish broad nominal wage pressure from composition effects in higher-paid supervisory and executive work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000011000004\", release: \"May 2025\", datatype: \"Annual mean wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Management wages help distinguish broad nominal wage pressure from composition effects in higher-paid supervisory and executive work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 15400, distribution present, forecast step count 1.","evidence":["Management wages help distinguish broad nominal wage pressure from composition effects in higher-paid supervisory and executive work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is steady managerial pay growth and a slightly higher-skill occupational mix. The lower tail covers weaker white-collar hiring and margin pressure in professional services."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Management wages help distinguish broad nominal wage pressure from composition effects in higher-paid supervisory and executive work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is steady managerial pay growth and a slightly higher-skill occupational mix. The lower tail covers weaker white-collar hiring and margin pressure in professional services."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual mean wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is steady managerial pay growth and a slightly higher-skill occupational mix. The lower tail covers weaker white-collar hiring and margin pressure in professional services."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-management-mean-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-management-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.cd75533fa4bd6842","runId":"run.oews-management-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.cd75533fa4bd6842","predictionId":"oews-management-mean-wage-may-2026","specId":"spec.oews-management-mean-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $145,260."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_11_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_11_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 145260, 80% interval [144760, 145760]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 145260, 80% interval [144760, 145760]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-management-mean-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-management-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.6147a1bbcf361b20","runId":"run.oews-management-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.6147a1bbcf361b20","predictionId":"oews-management-75th-percentile-wage-may-2026","specId":"spec.oews-management-75th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Management wages help distinguish broad nominal wage pressure from composition effects in higher-paid supervisory and executive work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"11-0000\", statistic: \"p75\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Management wages help distinguish broad nominal wage pressure from composition effects in higher-paid supervisory and executive work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000011000014\", release: \"May 2025\", datatype: \"Annual 75th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Management wages help distinguish broad nominal wage pressure from composition effects in higher-paid supervisory and executive work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 18700, distribution present, forecast step count 1.","evidence":["Management wages help distinguish broad nominal wage pressure from composition effects in higher-paid supervisory and executive work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is steady managerial pay growth and a slightly higher-skill occupational mix. The lower tail covers weaker white-collar hiring and margin pressure in professional services."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Management wages help distinguish broad nominal wage pressure from composition effects in higher-paid supervisory and executive work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is steady managerial pay growth and a slightly higher-skill occupational mix. The lower tail covers weaker white-collar hiring and margin pressure in professional services."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 75th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is steady managerial pay growth and a slightly higher-skill occupational mix. The lower tail covers weaker white-collar hiring and margin pressure in professional services."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-management-75th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-management-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.23de7d2a39f8ce8f","runId":"run.oews-management-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.23de7d2a39f8ce8f","predictionId":"oews-management-75th-percentile-wage-may-2026","specId":"spec.oews-management-75th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $176,280."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_11_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_11_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 176280, 80% interval [175780, 176780]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 176280, 80% interval [175780, 176780]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-management-75th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-management-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.c5ff9ac5c4f6639d","runId":"run.oews-management-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.c5ff9ac5c4f6639d","predictionId":"oews-management-90th-percentile-wage-may-2026","specId":"spec.oews-management-90th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Management wages help distinguish broad nominal wage pressure from composition effects in higher-paid supervisory and executive work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"11-0000\", statistic: \"p90\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Management wages help distinguish broad nominal wage pressure from composition effects in higher-paid supervisory and executive work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000011000015\", release: \"May 2025\", datatype: \"Annual 90th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Management wages help distinguish broad nominal wage pressure from composition effects in higher-paid supervisory and executive work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 27300, distribution present, forecast step count 1.","evidence":["Management wages help distinguish broad nominal wage pressure from composition effects in higher-paid supervisory and executive work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is steady managerial pay growth and a slightly higher-skill occupational mix. The lower tail covers weaker white-collar hiring and margin pressure in professional services."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Management wages help distinguish broad nominal wage pressure from composition effects in higher-paid supervisory and executive work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is steady managerial pay growth and a slightly higher-skill occupational mix. The lower tail covers weaker white-collar hiring and margin pressure in professional services."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 90th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is steady managerial pay growth and a slightly higher-skill occupational mix. The lower tail covers weaker white-collar hiring and margin pressure in professional services."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-management-90th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-management-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.81c4847807d9dc69","runId":"run.oews-management-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.81c4847807d9dc69","predictionId":"oews-management-90th-percentile-wage-may-2026","specId":"spec.oews-management-90th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $257,310."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_11_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_11_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 257310, 80% interval [256810, 257810]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 257310, 80% interval [256810, 257810]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-management-90th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-business-financial-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.1cbc9355c2067f62","runId":"run.oews-business-financial-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.1cbc9355c2067f62","predictionId":"oews-business-financial-10th-percentile-wage-may-2026","specId":"spec.oews-business-financial-10th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["This is a wage-side companion to the white-collar employment target: AI may compress routine analyst, compliance, bookkeeping, and claims work while leaving a higher-skill occupational mix. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"13-0000\", statistic: \"p10\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["This is a wage-side companion to the white-collar employment target: AI may compress routine analyst, compliance, bookkeeping, and claims work while leaving a higher-skill occupational mix. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000013000011\", release: \"May 2025\", datatype: \"Annual 10th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","This is a wage-side companion to the white-collar employment target: AI may compress routine analyst, compliance, bookkeeping, and claims work while leaving a higher-skill occupational mix. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5200, distribution present, forecast step count 1.","evidence":["This is a wage-side companion to the white-collar employment target: AI may compress routine analyst, compliance, bookkeeping, and claims work while leaving a higher-skill occupational mix. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued demand for analysts, compliance workers, and project management specialists. The lower tail covers weaker professional hiring and lower bonus-sensitive finance demand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 10th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued demand for analysts, compliance workers, and project management specialists. The lower tail covers weaker professional hiring and lower bonus-sensitive finance demand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-business-financial-10th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-business-financial-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.c990dd5ded4cc058","runId":"run.oews-business-financial-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.c990dd5ded4cc058","predictionId":"oews-business-financial-10th-percentile-wage-may-2026","specId":"spec.oews-business-financial-10th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $48,820."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_13_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_13_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 48820, 80% interval [48320, 49320]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 48820, 80% interval [48320, 49320]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-business-financial-10th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-business-financial-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.45b0ca953514cd07","runId":"run.oews-business-financial-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.45b0ca953514cd07","predictionId":"oews-business-financial-25th-percentile-wage-may-2026","specId":"spec.oews-business-financial-25th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["This is a wage-side companion to the white-collar employment target: AI may compress routine analyst, compliance, bookkeeping, and claims work while leaving a higher-skill occupational mix. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"13-0000\", statistic: \"p25\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["This is a wage-side companion to the white-collar employment target: AI may compress routine analyst, compliance, bookkeeping, and claims work while leaving a higher-skill occupational mix. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000013000012\", release: \"May 2025\", datatype: \"Annual 25th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","This is a wage-side companion to the white-collar employment target: AI may compress routine analyst, compliance, bookkeeping, and claims work while leaving a higher-skill occupational mix. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6600, distribution present, forecast step count 1.","evidence":["This is a wage-side companion to the white-collar employment target: AI may compress routine analyst, compliance, bookkeeping, and claims work while leaving a higher-skill occupational mix. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued demand for analysts, compliance workers, and project management specialists. The lower tail covers weaker professional hiring and lower bonus-sensitive finance demand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 25th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued demand for analysts, compliance workers, and project management specialists. The lower tail covers weaker professional hiring and lower bonus-sensitive finance demand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-business-financial-25th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-business-financial-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.4c4555ec80b27c96","runId":"run.oews-business-financial-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.4c4555ec80b27c96","predictionId":"oews-business-financial-25th-percentile-wage-may-2026","specId":"spec.oews-business-financial-25th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $62,940."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_13_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_13_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 62940, 80% interval [62440, 63440]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 62940, 80% interval [62440, 63440]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-business-financial-25th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-business-financial-median-wage-may-2026.2026-06-21T13-35-00-04-00.018252f72f791e2a","runId":"run.oews-business-financial-median-wage-may-2026.2026-06-21T13-35-00-04-00.018252f72f791e2a","predictionId":"oews-business-financial-median-wage-may-2026","specId":"spec.oews-business-financial-median-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["This is a wage-side companion to the white-collar employment target: AI may compress routine analyst, compliance, bookkeeping, and claims work while leaving a higher-skill occupational mix. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000013000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["This is a wage-side companion to the white-collar employment target: AI may compress routine analyst, compliance, bookkeeping, and claims work while leaving a higher-skill occupational mix. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000013000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","This is a wage-side companion to the white-collar employment target: AI may compress routine analyst, compliance, bookkeeping, and claims work while leaving a higher-skill occupational mix. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 8800, distribution present, forecast step count 1.","evidence":["This is a wage-side companion to the white-collar employment target: AI may compress routine analyst, compliance, bookkeeping, and claims work while leaving a higher-skill occupational mix. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued demand for analysts, compliance workers, and project management specialists. The lower tail covers weaker professional hiring and lower bonus-sensitive finance demand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual median wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued demand for analysts, compliance workers, and project management specialists. The lower tail covers weaker professional hiring and lower bonus-sensitive finance demand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-business-financial-median-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-business-financial-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.88c9aa0689df34c7","runId":"run.oews-business-financial-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.88c9aa0689df34c7","predictionId":"oews-business-financial-median-wage-may-2026","specId":"spec.oews-business-financial-median-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_13_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_13_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_13_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 82660, 80% interval [82160, 83160]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 82660, 80% interval [82160, 83160]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-business-financial-median-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-business-financial-mean-wage-may-2026.2026-06-21T13-35-00-04-00.28f56d3849b9a4bc","runId":"run.oews-business-financial-mean-wage-may-2026.2026-06-21T13-35-00-04-00.28f56d3849b9a4bc","predictionId":"oews-business-financial-mean-wage-may-2026","specId":"spec.oews-business-financial-mean-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["This is a wage-side companion to the white-collar employment target: AI may compress routine analyst, compliance, bookkeeping, and claims work while leaving a higher-skill occupational mix. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"13-0000\", statistic: \"mean\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["This is a wage-side companion to the white-collar employment target: AI may compress routine analyst, compliance, bookkeeping, and claims work while leaving a higher-skill occupational mix. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000013000004\", release: \"May 2025\", datatype: \"Annual mean wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","This is a wage-side companion to the white-collar employment target: AI may compress routine analyst, compliance, bookkeeping, and claims work while leaving a higher-skill occupational mix. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 10100, distribution present, forecast step count 1.","evidence":["This is a wage-side companion to the white-collar employment target: AI may compress routine analyst, compliance, bookkeeping, and claims work while leaving a higher-skill occupational mix. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued demand for analysts, compliance workers, and project management specialists. The lower tail covers weaker professional hiring and lower bonus-sensitive finance demand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual mean wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued demand for analysts, compliance workers, and project management specialists. The lower tail covers weaker professional hiring and lower bonus-sensitive finance demand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-business-financial-mean-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-business-financial-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.ff4859f45cb69d27","runId":"run.oews-business-financial-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.ff4859f45cb69d27","predictionId":"oews-business-financial-mean-wage-may-2026","specId":"spec.oews-business-financial-mean-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $95,230."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_13_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_13_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 95230, 80% interval [94730, 95730]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 95230, 80% interval [94730, 95730]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-business-financial-mean-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-business-financial-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.ba4e4307af97e899","runId":"run.oews-business-financial-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.ba4e4307af97e899","predictionId":"oews-business-financial-75th-percentile-wage-may-2026","specId":"spec.oews-business-financial-75th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["This is a wage-side companion to the white-collar employment target: AI may compress routine analyst, compliance, bookkeeping, and claims work while leaving a higher-skill occupational mix. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"13-0000\", statistic: \"p75\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["This is a wage-side companion to the white-collar employment target: AI may compress routine analyst, compliance, bookkeeping, and claims work while leaving a higher-skill occupational mix. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000013000014\", release: \"May 2025\", datatype: \"Annual 75th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","This is a wage-side companion to the white-collar employment target: AI may compress routine analyst, compliance, bookkeeping, and claims work while leaving a higher-skill occupational mix. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 12200, distribution present, forecast step count 1.","evidence":["This is a wage-side companion to the white-collar employment target: AI may compress routine analyst, compliance, bookkeeping, and claims work while leaving a higher-skill occupational mix. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued demand for analysts, compliance workers, and project management specialists. The lower tail covers weaker professional hiring and lower bonus-sensitive finance demand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 75th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued demand for analysts, compliance workers, and project management specialists. The lower tail covers weaker professional hiring and lower bonus-sensitive finance demand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-business-financial-75th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-business-financial-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.cb230562ad167948","runId":"run.oews-business-financial-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.cb230562ad167948","predictionId":"oews-business-financial-75th-percentile-wage-may-2026","specId":"spec.oews-business-financial-75th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $114,820."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_13_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_13_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 114820, 80% interval [114320, 115320]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 114820, 80% interval [114320, 115320]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-business-financial-75th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-business-financial-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.35f2e241bb25dd73","runId":"run.oews-business-financial-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.35f2e241bb25dd73","predictionId":"oews-business-financial-90th-percentile-wage-may-2026","specId":"spec.oews-business-financial-90th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["This is a wage-side companion to the white-collar employment target: AI may compress routine analyst, compliance, bookkeeping, and claims work while leaving a higher-skill occupational mix. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"13-0000\", statistic: \"p90\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["This is a wage-side companion to the white-collar employment target: AI may compress routine analyst, compliance, bookkeeping, and claims work while leaving a higher-skill occupational mix. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000013000015\", release: \"May 2025\", datatype: \"Annual 90th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","This is a wage-side companion to the white-collar employment target: AI may compress routine analyst, compliance, bookkeeping, and claims work while leaving a higher-skill occupational mix. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 16400, distribution present, forecast step count 1.","evidence":["This is a wage-side companion to the white-collar employment target: AI may compress routine analyst, compliance, bookkeeping, and claims work while leaving a higher-skill occupational mix. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued demand for analysts, compliance workers, and project management specialists. The lower tail covers weaker professional hiring and lower bonus-sensitive finance demand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 90th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued demand for analysts, compliance workers, and project management specialists. The lower tail covers weaker professional hiring and lower bonus-sensitive finance demand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-business-financial-90th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-business-financial-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.d2ce678e144cea0e","runId":"run.oews-business-financial-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.d2ce678e144cea0e","predictionId":"oews-business-financial-90th-percentile-wage-may-2026","specId":"spec.oews-business-financial-90th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $153,990."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_13_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_13_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 153990, 80% interval [153490, 154490]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 153990, 80% interval [153490, 154490]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-business-financial-90th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-computer-math-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.9efdf8946750cbcf","runId":"run.oews-computer-math-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.9efdf8946750cbcf","predictionId":"oews-computer-math-10th-percentile-wage-may-2026","specId":"spec.oews-computer-math-10th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.46,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["This is the cleanest wage target for whether AI tools are mainly labor-saving in software tasks or demand-expanding through AI infrastructure, security, data, and integration work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"15-0000\", statistic: \"p10\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["This is the cleanest wage target for whether AI tools are mainly labor-saving in software tasks or demand-expanding through AI infrastructure, security, data, and integration work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000015000011\", release: \"May 2025\", datatype: \"Annual 10th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","This is the cleanest wage target for whether AI tools are mainly labor-saving in software tasks or demand-expanding through AI infrastructure, security, data, and integration work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6200, distribution present, forecast step count 1.","evidence":["This is the cleanest wage target for whether AI tools are mainly labor-saving in software tasks or demand-expanding through AI infrastructure, security, data, and integration work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is AI infrastructure, cloud integration, and cybersecurity support offset by normalized tech hiring. The lower tail covers coding-assistant productivity and a softer software labor market holding down the central wage path."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is AI infrastructure, cloud integration, and cybersecurity support offset by normalized tech hiring. The lower tail covers coding-assistant productivity and a softer software labor market holding down the central wage path."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 10th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is AI infrastructure, cloud integration, and cybersecurity support offset by normalized tech hiring. The lower tail covers coding-assistant productivity and a softer software labor market holding down the central wage path."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-computer-math-10th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-computer-math-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.a6f919462d45a320","runId":"run.oews-computer-math-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.a6f919462d45a320","predictionId":"oews-computer-math-10th-percentile-wage-may-2026","specId":"spec.oews-computer-math-10th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $58,200."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_15_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_15_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 58200, 80% interval [57700, 58700]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 58200, 80% interval [57700, 58700]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-computer-math-10th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-computer-math-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.d6af775208ee53b0","runId":"run.oews-computer-math-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.d6af775208ee53b0","predictionId":"oews-computer-math-25th-percentile-wage-may-2026","specId":"spec.oews-computer-math-25th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.46,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["This is the cleanest wage target for whether AI tools are mainly labor-saving in software tasks or demand-expanding through AI infrastructure, security, data, and integration work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"15-0000\", statistic: \"p25\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["This is the cleanest wage target for whether AI tools are mainly labor-saving in software tasks or demand-expanding through AI infrastructure, security, data, and integration work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000015000012\", release: \"May 2025\", datatype: \"Annual 25th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","This is the cleanest wage target for whether AI tools are mainly labor-saving in software tasks or demand-expanding through AI infrastructure, security, data, and integration work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 8300, distribution present, forecast step count 1.","evidence":["This is the cleanest wage target for whether AI tools are mainly labor-saving in software tasks or demand-expanding through AI infrastructure, security, data, and integration work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is AI infrastructure, cloud integration, and cybersecurity support offset by normalized tech hiring. The lower tail covers coding-assistant productivity and a softer software labor market holding down the central wage path."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is AI infrastructure, cloud integration, and cybersecurity support offset by normalized tech hiring. The lower tail covers coding-assistant productivity and a softer software labor market holding down the central wage path."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 25th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is AI infrastructure, cloud integration, and cybersecurity support offset by normalized tech hiring. The lower tail covers coding-assistant productivity and a softer software labor market holding down the central wage path."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-computer-math-25th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-computer-math-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.d3a5190a787c59e2","runId":"run.oews-computer-math-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.d3a5190a787c59e2","predictionId":"oews-computer-math-25th-percentile-wage-may-2026","specId":"spec.oews-computer-math-25th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $78,820."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_15_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_15_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 78820, 80% interval [78320, 79320]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 78820, 80% interval [78320, 79320]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-computer-math-25th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-computer-math-median-wage-may-2026.2026-06-21T13-35-00-04-00.2efac853023a00d4","runId":"run.oews-computer-math-median-wage-may-2026.2026-06-21T13-35-00-04-00.2efac853023a00d4","predictionId":"oews-computer-math-median-wage-may-2026","specId":"spec.oews-computer-math-median-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.46,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["This is the cleanest wage target for whether AI tools are mainly labor-saving in software tasks or demand-expanding through AI infrastructure, security, data, and integration work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000015000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["This is the cleanest wage target for whether AI tools are mainly labor-saving in software tasks or demand-expanding through AI infrastructure, security, data, and integration work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000015000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","This is the cleanest wage target for whether AI tools are mainly labor-saving in software tasks or demand-expanding through AI infrastructure, security, data, and integration work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 11600, distribution present, forecast step count 1.","evidence":["This is the cleanest wage target for whether AI tools are mainly labor-saving in software tasks or demand-expanding through AI infrastructure, security, data, and integration work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is AI infrastructure, cloud integration, and cybersecurity support offset by normalized tech hiring. The lower tail covers coding-assistant productivity and a softer software labor market holding down the central wage path."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is AI infrastructure, cloud integration, and cybersecurity support offset by normalized tech hiring. The lower tail covers coding-assistant productivity and a softer software labor market holding down the central wage path."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual median wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is AI infrastructure, cloud integration, and cybersecurity support offset by normalized tech hiring. The lower tail covers coding-assistant productivity and a softer software labor market holding down the central wage path."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-computer-math-median-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-computer-math-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.1b7c78d77d94f3da","runId":"run.oews-computer-math-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.1b7c78d77d94f3da","predictionId":"oews-computer-math-median-wage-may-2026","specId":"spec.oews-computer-math-median-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_15_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_15_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_15_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 109280, 80% interval [108780, 109780]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 109280, 80% interval [108780, 109780]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-computer-math-median-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-computer-math-mean-wage-may-2026.2026-06-21T13-35-00-04-00.fc3d0fa9e8609426","runId":"run.oews-computer-math-mean-wage-may-2026.2026-06-21T13-35-00-04-00.fc3d0fa9e8609426","predictionId":"oews-computer-math-mean-wage-may-2026","specId":"spec.oews-computer-math-mean-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.46,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["This is the cleanest wage target for whether AI tools are mainly labor-saving in software tasks or demand-expanding through AI infrastructure, security, data, and integration work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"15-0000\", statistic: \"mean\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["This is the cleanest wage target for whether AI tools are mainly labor-saving in software tasks or demand-expanding through AI infrastructure, security, data, and integration work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000015000004\", release: \"May 2025\", datatype: \"Annual mean wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","This is the cleanest wage target for whether AI tools are mainly labor-saving in software tasks or demand-expanding through AI infrastructure, security, data, and integration work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 12800, distribution present, forecast step count 1.","evidence":["This is the cleanest wage target for whether AI tools are mainly labor-saving in software tasks or demand-expanding through AI infrastructure, security, data, and integration work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is AI infrastructure, cloud integration, and cybersecurity support offset by normalized tech hiring. The lower tail covers coding-assistant productivity and a softer software labor market holding down the central wage path."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is AI infrastructure, cloud integration, and cybersecurity support offset by normalized tech hiring. The lower tail covers coding-assistant productivity and a softer software labor market holding down the central wage path."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual mean wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is AI infrastructure, cloud integration, and cybersecurity support offset by normalized tech hiring. The lower tail covers coding-assistant productivity and a softer software labor market holding down the central wage path."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-computer-math-mean-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-computer-math-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.64b5aa41f1f9c77f","runId":"run.oews-computer-math-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.64b5aa41f1f9c77f","predictionId":"oews-computer-math-mean-wage-may-2026","specId":"spec.oews-computer-math-mean-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $120,080."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_15_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_15_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 120080, 80% interval [119580, 120580]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 120080, 80% interval [119580, 120580]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-computer-math-mean-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-computer-math-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.806bf3845298fe9b","runId":"run.oews-computer-math-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.806bf3845298fe9b","predictionId":"oews-computer-math-75th-percentile-wage-may-2026","specId":"spec.oews-computer-math-75th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.46,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["This is the cleanest wage target for whether AI tools are mainly labor-saving in software tasks or demand-expanding through AI infrastructure, security, data, and integration work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"15-0000\", statistic: \"p75\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["This is the cleanest wage target for whether AI tools are mainly labor-saving in software tasks or demand-expanding through AI infrastructure, security, data, and integration work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000015000014\", release: \"May 2025\", datatype: \"Annual 75th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","This is the cleanest wage target for whether AI tools are mainly labor-saving in software tasks or demand-expanding through AI infrastructure, security, data, and integration work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 16600, distribution present, forecast step count 1.","evidence":["This is the cleanest wage target for whether AI tools are mainly labor-saving in software tasks or demand-expanding through AI infrastructure, security, data, and integration work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is AI infrastructure, cloud integration, and cybersecurity support offset by normalized tech hiring. The lower tail covers coding-assistant productivity and a softer software labor market holding down the central wage path."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is AI infrastructure, cloud integration, and cybersecurity support offset by normalized tech hiring. The lower tail covers coding-assistant productivity and a softer software labor market holding down the central wage path."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 75th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is AI infrastructure, cloud integration, and cybersecurity support offset by normalized tech hiring. The lower tail covers coding-assistant productivity and a softer software labor market holding down the central wage path."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-computer-math-75th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-computer-math-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.e98eba30c5da12b0","runId":"run.oews-computer-math-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.e98eba30c5da12b0","predictionId":"oews-computer-math-75th-percentile-wage-may-2026","specId":"spec.oews-computer-math-75th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $155,830."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_15_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_15_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 155830, 80% interval [155330, 156330]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 155830, 80% interval [155330, 156330]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-computer-math-75th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-computer-math-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.66d9745ebfe1adab","runId":"run.oews-computer-math-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.66d9745ebfe1adab","predictionId":"oews-computer-math-90th-percentile-wage-may-2026","specId":"spec.oews-computer-math-90th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.46,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["This is the cleanest wage target for whether AI tools are mainly labor-saving in software tasks or demand-expanding through AI infrastructure, security, data, and integration work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"15-0000\", statistic: \"p90\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["This is the cleanest wage target for whether AI tools are mainly labor-saving in software tasks or demand-expanding through AI infrastructure, security, data, and integration work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000015000015\", release: \"May 2025\", datatype: \"Annual 90th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","This is the cleanest wage target for whether AI tools are mainly labor-saving in software tasks or demand-expanding through AI infrastructure, security, data, and integration work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 20400, distribution present, forecast step count 1.","evidence":["This is the cleanest wage target for whether AI tools are mainly labor-saving in software tasks or demand-expanding through AI infrastructure, security, data, and integration work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is AI infrastructure, cloud integration, and cybersecurity support offset by normalized tech hiring. The lower tail covers coding-assistant productivity and a softer software labor market holding down the central wage path."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is AI infrastructure, cloud integration, and cybersecurity support offset by normalized tech hiring. The lower tail covers coding-assistant productivity and a softer software labor market holding down the central wage path."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 90th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is AI infrastructure, cloud integration, and cybersecurity support offset by normalized tech hiring. The lower tail covers coding-assistant productivity and a softer software labor market holding down the central wage path."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-computer-math-90th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-computer-math-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.132d5b174e601682","runId":"run.oews-computer-math-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.132d5b174e601682","predictionId":"oews-computer-math-90th-percentile-wage-may-2026","specId":"spec.oews-computer-math-90th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $191,450."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_15_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_15_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 191450, 80% interval [190950, 191950]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 191450, 80% interval [190950, 191950]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-computer-math-90th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-architecture-engineering-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.e089200ad90a62e6","runId":"run.oews-architecture-engineering-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.e089200ad90a62e6","predictionId":"oews-architecture-engineering-10th-percentile-wage-may-2026","specId":"spec.oews-architecture-engineering-10th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Architecture and engineering wages connect AI-assisted technical design to infrastructure, energy, manufacturing, and construction demand. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"17-0000\", statistic: \"p10\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Architecture and engineering wages connect AI-assisted technical design to infrastructure, energy, manufacturing, and construction demand. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000017000011\", release: \"May 2025\", datatype: \"Annual 10th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Architecture and engineering wages connect AI-assisted technical design to infrastructure, energy, manufacturing, and construction demand. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6200, distribution present, forecast step count 1.","evidence":["Architecture and engineering wages connect AI-assisted technical design to infrastructure, energy, manufacturing, and construction demand. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is solid infrastructure and engineering-services demand with moderate design-tool productivity gains. The lower tail covers a softer construction/manufacturing cycle and fewer high-pay project starts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 10th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is solid infrastructure and engineering-services demand with moderate design-tool productivity gains. The lower tail covers a softer construction/manufacturing cycle and fewer high-pay project starts."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-architecture-engineering-10th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-architecture-engineering-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.f0f7e6ba8a9aa1e7","runId":"run.oews-architecture-engineering-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.f0f7e6ba8a9aa1e7","predictionId":"oews-architecture-engineering-10th-percentile-wage-may-2026","specId":"spec.oews-architecture-engineering-10th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $58,670."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_17_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_17_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 58670, 80% interval [58170, 59170]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 58670, 80% interval [58170, 59170]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-architecture-engineering-10th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-architecture-engineering-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.f15e79f15953b530","runId":"run.oews-architecture-engineering-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.f15e79f15953b530","predictionId":"oews-architecture-engineering-25th-percentile-wage-may-2026","specId":"spec.oews-architecture-engineering-25th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Architecture and engineering wages connect AI-assisted technical design to infrastructure, energy, manufacturing, and construction demand. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"17-0000\", statistic: \"p25\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Architecture and engineering wages connect AI-assisted technical design to infrastructure, energy, manufacturing, and construction demand. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000017000012\", release: \"May 2025\", datatype: \"Annual 25th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Architecture and engineering wages connect AI-assisted technical design to infrastructure, energy, manufacturing, and construction demand. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 8200, distribution present, forecast step count 1.","evidence":["Architecture and engineering wages connect AI-assisted technical design to infrastructure, energy, manufacturing, and construction demand. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is solid infrastructure and engineering-services demand with moderate design-tool productivity gains. The lower tail covers a softer construction/manufacturing cycle and fewer high-pay project starts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 25th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is solid infrastructure and engineering-services demand with moderate design-tool productivity gains. The lower tail covers a softer construction/manufacturing cycle and fewer high-pay project starts."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-architecture-engineering-25th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-architecture-engineering-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.eabeaf5822711f62","runId":"run.oews-architecture-engineering-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.eabeaf5822711f62","predictionId":"oews-architecture-engineering-25th-percentile-wage-may-2026","specId":"spec.oews-architecture-engineering-25th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $76,560."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_17_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_17_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 76560, 80% interval [76060, 77060]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 76560, 80% interval [76060, 77060]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-architecture-engineering-25th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-architecture-engineering-median-wage-may-2026.2026-06-21T13-35-00-04-00.079dcb52bd2eb4ea","runId":"run.oews-architecture-engineering-median-wage-may-2026.2026-06-21T13-35-00-04-00.079dcb52bd2eb4ea","predictionId":"oews-architecture-engineering-median-wage-may-2026","specId":"spec.oews-architecture-engineering-median-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Architecture and engineering wages connect AI-assisted technical design to infrastructure, energy, manufacturing, and construction demand. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000017000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Architecture and engineering wages connect AI-assisted technical design to infrastructure, energy, manufacturing, and construction demand. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000017000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Architecture and engineering wages connect AI-assisted technical design to infrastructure, energy, manufacturing, and construction demand. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 10600, distribution present, forecast step count 1.","evidence":["Architecture and engineering wages connect AI-assisted technical design to infrastructure, energy, manufacturing, and construction demand. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is solid infrastructure and engineering-services demand with moderate design-tool productivity gains. The lower tail covers a softer construction/manufacturing cycle and fewer high-pay project starts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual median wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is solid infrastructure and engineering-services demand with moderate design-tool productivity gains. The lower tail covers a softer construction/manufacturing cycle and fewer high-pay project starts."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-architecture-engineering-median-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-architecture-engineering-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.bcc913383f967fe0","runId":"run.oews-architecture-engineering-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.bcc913383f967fe0","predictionId":"oews-architecture-engineering-median-wage-may-2026","specId":"spec.oews-architecture-engineering-median-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_17_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_17_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_17_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 99520, 80% interval [99020, 100020]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 99520, 80% interval [99020, 100020]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-architecture-engineering-median-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-architecture-engineering-mean-wage-may-2026.2026-06-21T13-35-00-04-00.4eb5a1a91e1b54ee","runId":"run.oews-architecture-engineering-mean-wage-may-2026.2026-06-21T13-35-00-04-00.4eb5a1a91e1b54ee","predictionId":"oews-architecture-engineering-mean-wage-may-2026","specId":"spec.oews-architecture-engineering-mean-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Architecture and engineering wages connect AI-assisted technical design to infrastructure, energy, manufacturing, and construction demand. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"17-0000\", statistic: \"mean\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Architecture and engineering wages connect AI-assisted technical design to infrastructure, energy, manufacturing, and construction demand. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000017000004\", release: \"May 2025\", datatype: \"Annual mean wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Architecture and engineering wages connect AI-assisted technical design to infrastructure, energy, manufacturing, and construction demand. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 11300, distribution present, forecast step count 1.","evidence":["Architecture and engineering wages connect AI-assisted technical design to infrastructure, energy, manufacturing, and construction demand. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is solid infrastructure and engineering-services demand with moderate design-tool productivity gains. The lower tail covers a softer construction/manufacturing cycle and fewer high-pay project starts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual mean wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is solid infrastructure and engineering-services demand with moderate design-tool productivity gains. The lower tail covers a softer construction/manufacturing cycle and fewer high-pay project starts."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-architecture-engineering-mean-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-architecture-engineering-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.9fbdbea33bfaf93e","runId":"run.oews-architecture-engineering-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.9fbdbea33bfaf93e","predictionId":"oews-architecture-engineering-mean-wage-may-2026","specId":"spec.oews-architecture-engineering-mean-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $106,830."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_17_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_17_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 106830, 80% interval [106330, 107330]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 106830, 80% interval [106330, 107330]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-architecture-engineering-mean-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-architecture-engineering-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.ae07c8955fd58b3d","runId":"run.oews-architecture-engineering-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.ae07c8955fd58b3d","predictionId":"oews-architecture-engineering-75th-percentile-wage-may-2026","specId":"spec.oews-architecture-engineering-75th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Architecture and engineering wages connect AI-assisted technical design to infrastructure, energy, manufacturing, and construction demand. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"17-0000\", statistic: \"p75\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Architecture and engineering wages connect AI-assisted technical design to infrastructure, energy, manufacturing, and construction demand. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000017000014\", release: \"May 2025\", datatype: \"Annual 75th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Architecture and engineering wages connect AI-assisted technical design to infrastructure, energy, manufacturing, and construction demand. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 13800, distribution present, forecast step count 1.","evidence":["Architecture and engineering wages connect AI-assisted technical design to infrastructure, energy, manufacturing, and construction demand. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is solid infrastructure and engineering-services demand with moderate design-tool productivity gains. The lower tail covers a softer construction/manufacturing cycle and fewer high-pay project starts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 75th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is solid infrastructure and engineering-services demand with moderate design-tool productivity gains. The lower tail covers a softer construction/manufacturing cycle and fewer high-pay project starts."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-architecture-engineering-75th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-architecture-engineering-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.d2ba5222385a0ff9","runId":"run.oews-architecture-engineering-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.d2ba5222385a0ff9","predictionId":"oews-architecture-engineering-75th-percentile-wage-may-2026","specId":"spec.oews-architecture-engineering-75th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $130,240."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_17_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_17_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 130240, 80% interval [129740, 130740]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 130240, 80% interval [129740, 130740]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-architecture-engineering-75th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-architecture-engineering-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.e64117c568d0b88c","runId":"run.oews-architecture-engineering-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.e64117c568d0b88c","predictionId":"oews-architecture-engineering-90th-percentile-wage-may-2026","specId":"spec.oews-architecture-engineering-90th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Architecture and engineering wages connect AI-assisted technical design to infrastructure, energy, manufacturing, and construction demand. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"17-0000\", statistic: \"p90\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Architecture and engineering wages connect AI-assisted technical design to infrastructure, energy, manufacturing, and construction demand. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000017000015\", release: \"May 2025\", datatype: \"Annual 90th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Architecture and engineering wages connect AI-assisted technical design to infrastructure, energy, manufacturing, and construction demand. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 17700, distribution present, forecast step count 1.","evidence":["Architecture and engineering wages connect AI-assisted technical design to infrastructure, energy, manufacturing, and construction demand. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is solid infrastructure and engineering-services demand with moderate design-tool productivity gains. The lower tail covers a softer construction/manufacturing cycle and fewer high-pay project starts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 90th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is solid infrastructure and engineering-services demand with moderate design-tool productivity gains. The lower tail covers a softer construction/manufacturing cycle and fewer high-pay project starts."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-architecture-engineering-90th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-architecture-engineering-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.4c564e8b7f85e244","runId":"run.oews-architecture-engineering-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.4c564e8b7f85e244","predictionId":"oews-architecture-engineering-90th-percentile-wage-may-2026","specId":"spec.oews-architecture-engineering-90th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $166,490."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_17_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_17_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 166490, 80% interval [165990, 166990]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 166490, 80% interval [165990, 166990]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-architecture-engineering-90th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-life-physical-social-science-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.e710a0e375976703","runId":"run.oews-life-physical-social-science-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.e710a0e375976703","predictionId":"oews-life-physical-social-science-10th-percentile-wage-may-2026","specId":"spec.oews-life-physical-social-science-10th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Science wages are a useful white-collar benchmark where research funding, biotech, energy, and public-sector demand matter more than clerical automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"19-0000\", statistic: \"p10\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Science wages are a useful white-collar benchmark where research funding, biotech, energy, and public-sector demand matter more than clerical automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000019000011\", release: \"May 2025\", datatype: \"Annual 10th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Science wages are a useful white-collar benchmark where research funding, biotech, energy, and public-sector demand matter more than clerical automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5100, distribution present, forecast step count 1.","evidence":["Science wages are a useful white-collar benchmark where research funding, biotech, energy, and public-sector demand matter more than clerical automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is stable research labor demand and a modest mix shift toward specialized technical roles. The lower tail covers tighter grant budgets and slower public-sector hiring."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 10th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is stable research labor demand and a modest mix shift toward specialized technical roles. The lower tail covers tighter grant budgets and slower public-sector hiring."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-life-physical-social-science-10th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-life-physical-social-science-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.b4dc43a26447bf5e","runId":"run.oews-life-physical-social-science-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.b4dc43a26447bf5e","predictionId":"oews-life-physical-social-science-10th-percentile-wage-may-2026","specId":"spec.oews-life-physical-social-science-10th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $48,420."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_19_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_19_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 48420, 80% interval [47920, 48920]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 48420, 80% interval [47920, 48920]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-life-physical-social-science-10th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-life-physical-social-science-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.6be618f191933b82","runId":"run.oews-life-physical-social-science-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.6be618f191933b82","predictionId":"oews-life-physical-social-science-25th-percentile-wage-may-2026","specId":"spec.oews-life-physical-social-science-25th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Science wages are a useful white-collar benchmark where research funding, biotech, energy, and public-sector demand matter more than clerical automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"19-0000\", statistic: \"p25\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Science wages are a useful white-collar benchmark where research funding, biotech, energy, and public-sector demand matter more than clerical automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000019000012\", release: \"May 2025\", datatype: \"Annual 25th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Science wages are a useful white-collar benchmark where research funding, biotech, energy, and public-sector demand matter more than clerical automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6600, distribution present, forecast step count 1.","evidence":["Science wages are a useful white-collar benchmark where research funding, biotech, energy, and public-sector demand matter more than clerical automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is stable research labor demand and a modest mix shift toward specialized technical roles. The lower tail covers tighter grant budgets and slower public-sector hiring."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 25th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is stable research labor demand and a modest mix shift toward specialized technical roles. The lower tail covers tighter grant budgets and slower public-sector hiring."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-life-physical-social-science-25th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-life-physical-social-science-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.07104cffa20367cc","runId":"run.oews-life-physical-social-science-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.07104cffa20367cc","predictionId":"oews-life-physical-social-science-25th-percentile-wage-may-2026","specId":"spec.oews-life-physical-social-science-25th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $62,380."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_19_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_19_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 62380, 80% interval [61880, 62880]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 62380, 80% interval [61880, 62880]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-life-physical-social-science-25th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-life-physical-social-science-median-wage-may-2026.2026-06-21T13-35-00-04-00.bb358975be1f46a9","runId":"run.oews-life-physical-social-science-median-wage-may-2026.2026-06-21T13-35-00-04-00.bb358975be1f46a9","predictionId":"oews-life-physical-social-science-median-wage-may-2026","specId":"spec.oews-life-physical-social-science-median-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Science wages are a useful white-collar benchmark where research funding, biotech, energy, and public-sector demand matter more than clerical automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000019000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Science wages are a useful white-collar benchmark where research funding, biotech, energy, and public-sector demand matter more than clerical automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000019000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Science wages are a useful white-collar benchmark where research funding, biotech, energy, and public-sector demand matter more than clerical automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 8800, distribution present, forecast step count 1.","evidence":["Science wages are a useful white-collar benchmark where research funding, biotech, energy, and public-sector demand matter more than clerical automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is stable research labor demand and a modest mix shift toward specialized technical roles. The lower tail covers tighter grant budgets and slower public-sector hiring."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual median wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is stable research labor demand and a modest mix shift toward specialized technical roles. The lower tail covers tighter grant budgets and slower public-sector hiring."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-life-physical-social-science-median-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-life-physical-social-science-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.cc0a942dc9ee124b","runId":"run.oews-life-physical-social-science-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.cc0a942dc9ee124b","predictionId":"oews-life-physical-social-science-median-wage-may-2026","specId":"spec.oews-life-physical-social-science-median-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_19_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_19_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_19_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 82530, 80% interval [82030, 83030]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 82530, 80% interval [82030, 83030]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-life-physical-social-science-median-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-life-physical-social-science-mean-wage-may-2026.2026-06-21T13-35-00-04-00.4b7942d9758597fe","runId":"run.oews-life-physical-social-science-mean-wage-may-2026.2026-06-21T13-35-00-04-00.4b7942d9758597fe","predictionId":"oews-life-physical-social-science-mean-wage-may-2026","specId":"spec.oews-life-physical-social-science-mean-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Science wages are a useful white-collar benchmark where research funding, biotech, energy, and public-sector demand matter more than clerical automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"19-0000\", statistic: \"mean\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Science wages are a useful white-collar benchmark where research funding, biotech, energy, and public-sector demand matter more than clerical automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000019000004\", release: \"May 2025\", datatype: \"Annual mean wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Science wages are a useful white-collar benchmark where research funding, biotech, energy, and public-sector demand matter more than clerical automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 10000, distribution present, forecast step count 1.","evidence":["Science wages are a useful white-collar benchmark where research funding, biotech, energy, and public-sector demand matter more than clerical automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is stable research labor demand and a modest mix shift toward specialized technical roles. The lower tail covers tighter grant budgets and slower public-sector hiring."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual mean wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is stable research labor demand and a modest mix shift toward specialized technical roles. The lower tail covers tighter grant budgets and slower public-sector hiring."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-life-physical-social-science-mean-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-life-physical-social-science-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.de7353b5d1f8a275","runId":"run.oews-life-physical-social-science-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.de7353b5d1f8a275","predictionId":"oews-life-physical-social-science-mean-wage-may-2026","specId":"spec.oews-life-physical-social-science-mean-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $94,600."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_19_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_19_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 94600, 80% interval [94100, 95100]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 94600, 80% interval [94100, 95100]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-life-physical-social-science-mean-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-life-physical-social-science-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.ebc9caef8d260084","runId":"run.oews-life-physical-social-science-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.ebc9caef8d260084","predictionId":"oews-life-physical-social-science-75th-percentile-wage-may-2026","specId":"spec.oews-life-physical-social-science-75th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Science wages are a useful white-collar benchmark where research funding, biotech, energy, and public-sector demand matter more than clerical automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"19-0000\", statistic: \"p75\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Science wages are a useful white-collar benchmark where research funding, biotech, energy, and public-sector demand matter more than clerical automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000019000014\", release: \"May 2025\", datatype: \"Annual 75th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Science wages are a useful white-collar benchmark where research funding, biotech, energy, and public-sector demand matter more than clerical automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 12100, distribution present, forecast step count 1.","evidence":["Science wages are a useful white-collar benchmark where research funding, biotech, energy, and public-sector demand matter more than clerical automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is stable research labor demand and a modest mix shift toward specialized technical roles. The lower tail covers tighter grant budgets and slower public-sector hiring."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 75th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is stable research labor demand and a modest mix shift toward specialized technical roles. The lower tail covers tighter grant budgets and slower public-sector hiring."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-life-physical-social-science-75th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-life-physical-social-science-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.140643f0e8005aba","runId":"run.oews-life-physical-social-science-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.140643f0e8005aba","predictionId":"oews-life-physical-social-science-75th-percentile-wage-may-2026","specId":"spec.oews-life-physical-social-science-75th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $114,460."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_19_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_19_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 114460, 80% interval [113960, 114960]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 114460, 80% interval [113960, 114960]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-life-physical-social-science-75th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-life-physical-social-science-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.806bf3845298fe9b","runId":"run.oews-life-physical-social-science-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.806bf3845298fe9b","predictionId":"oews-life-physical-social-science-90th-percentile-wage-may-2026","specId":"spec.oews-life-physical-social-science-90th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Science wages are a useful white-collar benchmark where research funding, biotech, energy, and public-sector demand matter more than clerical automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"19-0000\", statistic: \"p90\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Science wages are a useful white-collar benchmark where research funding, biotech, energy, and public-sector demand matter more than clerical automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000019000015\", release: \"May 2025\", datatype: \"Annual 90th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Science wages are a useful white-collar benchmark where research funding, biotech, energy, and public-sector demand matter more than clerical automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 16600, distribution present, forecast step count 1.","evidence":["Science wages are a useful white-collar benchmark where research funding, biotech, energy, and public-sector demand matter more than clerical automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is stable research labor demand and a modest mix shift toward specialized technical roles. The lower tail covers tighter grant budgets and slower public-sector hiring."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 90th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is stable research labor demand and a modest mix shift toward specialized technical roles. The lower tail covers tighter grant budgets and slower public-sector hiring."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-life-physical-social-science-90th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-life-physical-social-science-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.e98eba30c5da12b0","runId":"run.oews-life-physical-social-science-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.e98eba30c5da12b0","predictionId":"oews-life-physical-social-science-90th-percentile-wage-may-2026","specId":"spec.oews-life-physical-social-science-90th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $155,830."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_19_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_19_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 155830, 80% interval [155330, 156330]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 155830, 80% interval [155330, 156330]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-life-physical-social-science-90th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-community-social-service-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.748b9b889bfc8018","runId":"run.oews-community-social-service-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.748b9b889bfc8018","predictionId":"oews-community-social-service-10th-percentile-wage-may-2026","specId":"spec.oews-community-social-service-10th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Community and social service wages expose the low- and mid-wage care workforce where public funding, staffing shortages, and demand for human contact dominate. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"21-0000\", statistic: \"p10\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Community and social service wages expose the low- and mid-wage care workforce where public funding, staffing shortages, and demand for human contact dominate. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000021000011\", release: \"May 2025\", datatype: \"Annual 10th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Community and social service wages expose the low- and mid-wage care workforce where public funding, staffing shortages, and demand for human contact dominate. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4000, distribution present, forecast step count 1.","evidence":["Community and social service wages expose the low- and mid-wage care workforce where public funding, staffing shortages, and demand for human contact dominate. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in behavioral health, counseling, and community services. The lower tail covers constrained public budgets and nonprofit funding limits."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_p10_wage_2025_usd: 37970, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'care_services_shortage_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in behavioral health, counseling, and community services. The lower tail covers constrained public budgets and nonprofit funding limits."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 10th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in behavioral health, counseling, and community services. The lower tail covers constrained public budgets and nonprofit funding limits."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-community-social-service-10th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-community-social-service-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.a2717af306b57f24","runId":"run.oews-community-social-service-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.a2717af306b57f24","predictionId":"oews-community-social-service-10th-percentile-wage-may-2026","specId":"spec.oews-community-social-service-10th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $37,970."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_21_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_21_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 37970, 80% interval [37470, 38470]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 37970, 80% interval [37470, 38470]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-community-social-service-10th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-community-social-service-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.bbfa7d9677813f62","runId":"run.oews-community-social-service-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.bbfa7d9677813f62","predictionId":"oews-community-social-service-25th-percentile-wage-may-2026","specId":"spec.oews-community-social-service-25th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Community and social service wages expose the low- and mid-wage care workforce where public funding, staffing shortages, and demand for human contact dominate. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"21-0000\", statistic: \"p25\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Community and social service wages expose the low- and mid-wage care workforce where public funding, staffing shortages, and demand for human contact dominate. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000021000012\", release: \"May 2025\", datatype: \"Annual 25th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Community and social service wages expose the low- and mid-wage care workforce where public funding, staffing shortages, and demand for human contact dominate. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4900, distribution present, forecast step count 1.","evidence":["Community and social service wages expose the low- and mid-wage care workforce where public funding, staffing shortages, and demand for human contact dominate. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in behavioral health, counseling, and community services. The lower tail covers constrained public budgets and nonprofit funding limits."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_p25_wage_2025_usd: 46370, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'care_services_shortage_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in behavioral health, counseling, and community services. The lower tail covers constrained public budgets and nonprofit funding limits."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 25th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in behavioral health, counseling, and community services. The lower tail covers constrained public budgets and nonprofit funding limits."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-community-social-service-25th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-community-social-service-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.65daacb74545421d","runId":"run.oews-community-social-service-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.65daacb74545421d","predictionId":"oews-community-social-service-25th-percentile-wage-may-2026","specId":"spec.oews-community-social-service-25th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $46,370."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_21_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_21_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 46370, 80% interval [45870, 46870]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 46370, 80% interval [45870, 46870]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-community-social-service-25th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-community-social-service-median-wage-may-2026.2026-06-21T13-35-00-04-00.96852a75a7148a67","runId":"run.oews-community-social-service-median-wage-may-2026.2026-06-21T13-35-00-04-00.96852a75a7148a67","predictionId":"oews-community-social-service-median-wage-may-2026","specId":"spec.oews-community-social-service-median-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Community and social service wages expose the low- and mid-wage care workforce where public funding, staffing shortages, and demand for human contact dominate. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000021000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Community and social service wages expose the low- and mid-wage care workforce where public funding, staffing shortages, and demand for human contact dominate. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000021000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Community and social service wages expose the low- and mid-wage care workforce where public funding, staffing shortages, and demand for human contact dominate. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6200, distribution present, forecast step count 1.","evidence":["Community and social service wages expose the low- and mid-wage care workforce where public funding, staffing shortages, and demand for human contact dominate. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in behavioral health, counseling, and community services. The lower tail covers constrained public budgets and nonprofit funding limits."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_median_wage_2025_usd: 58300, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'care_services_shortage_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in behavioral health, counseling, and community services. The lower tail covers constrained public budgets and nonprofit funding limits."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual median wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in behavioral health, counseling, and community services. The lower tail covers constrained public budgets and nonprofit funding limits."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-community-social-service-median-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-community-social-service-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.3b21c050f9204dfb","runId":"run.oews-community-social-service-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.3b21c050f9204dfb","predictionId":"oews-community-social-service-median-wage-may-2026","specId":"spec.oews-community-social-service-median-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_21_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_21_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_21_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 58300, 80% interval [57800, 58800]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 58300, 80% interval [57800, 58800]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-community-social-service-median-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-community-social-service-mean-wage-may-2026.2026-06-21T13-35-00-04-00.4b8f9b39af13293c","runId":"run.oews-community-social-service-mean-wage-may-2026.2026-06-21T13-35-00-04-00.4b8f9b39af13293c","predictionId":"oews-community-social-service-mean-wage-may-2026","specId":"spec.oews-community-social-service-mean-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Community and social service wages expose the low- and mid-wage care workforce where public funding, staffing shortages, and demand for human contact dominate. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"21-0000\", statistic: \"mean\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Community and social service wages expose the low- and mid-wage care workforce where public funding, staffing shortages, and demand for human contact dominate. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000021000004\", release: \"May 2025\", datatype: \"Annual mean wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Community and social service wages expose the low- and mid-wage care workforce where public funding, staffing shortages, and demand for human contact dominate. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6700, distribution present, forecast step count 1.","evidence":["Community and social service wages expose the low- and mid-wage care workforce where public funding, staffing shortages, and demand for human contact dominate. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in behavioral health, counseling, and community services. The lower tail covers constrained public budgets and nonprofit funding limits."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_mean_wage_2025_usd: 63410, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'care_services_shortage_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in behavioral health, counseling, and community services. The lower tail covers constrained public budgets and nonprofit funding limits."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual mean wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in behavioral health, counseling, and community services. The lower tail covers constrained public budgets and nonprofit funding limits."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-community-social-service-mean-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-community-social-service-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.681d76c43e4b59fc","runId":"run.oews-community-social-service-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.681d76c43e4b59fc","predictionId":"oews-community-social-service-mean-wage-may-2026","specId":"spec.oews-community-social-service-mean-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $63,410."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_21_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_21_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 63410, 80% interval [62910, 63910]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 63410, 80% interval [62910, 63910]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-community-social-service-mean-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-community-social-service-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.751d8e8eeb2062a0","runId":"run.oews-community-social-service-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.751d8e8eeb2062a0","predictionId":"oews-community-social-service-75th-percentile-wage-may-2026","specId":"spec.oews-community-social-service-75th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Community and social service wages expose the low- and mid-wage care workforce where public funding, staffing shortages, and demand for human contact dominate. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"21-0000\", statistic: \"p75\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Community and social service wages expose the low- and mid-wage care workforce where public funding, staffing shortages, and demand for human contact dominate. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000021000014\", release: \"May 2025\", datatype: \"Annual 75th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Community and social service wages expose the low- and mid-wage care workforce where public funding, staffing shortages, and demand for human contact dominate. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 8100, distribution present, forecast step count 1.","evidence":["Community and social service wages expose the low- and mid-wage care workforce where public funding, staffing shortages, and demand for human contact dominate. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in behavioral health, counseling, and community services. The lower tail covers constrained public budgets and nonprofit funding limits."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_p75_wage_2025_usd: 75910, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'care_services_shortage_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in behavioral health, counseling, and community services. The lower tail covers constrained public budgets and nonprofit funding limits."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 75th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in behavioral health, counseling, and community services. The lower tail covers constrained public budgets and nonprofit funding limits."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-community-social-service-75th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-community-social-service-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.0d4fae1edd39db18","runId":"run.oews-community-social-service-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.0d4fae1edd39db18","predictionId":"oews-community-social-service-75th-percentile-wage-may-2026","specId":"spec.oews-community-social-service-75th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $75,910."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_21_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_21_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 75910, 80% interval [75410, 76410]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 75910, 80% interval [75410, 76410]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-community-social-service-75th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-community-social-service-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.2779ba8f6958942b","runId":"run.oews-community-social-service-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.2779ba8f6958942b","predictionId":"oews-community-social-service-90th-percentile-wage-may-2026","specId":"spec.oews-community-social-service-90th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Community and social service wages expose the low- and mid-wage care workforce where public funding, staffing shortages, and demand for human contact dominate. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"21-0000\", statistic: \"p90\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Community and social service wages expose the low- and mid-wage care workforce where public funding, staffing shortages, and demand for human contact dominate. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000021000015\", release: \"May 2025\", datatype: \"Annual 90th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Community and social service wages expose the low- and mid-wage care workforce where public funding, staffing shortages, and demand for human contact dominate. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 10400, distribution present, forecast step count 1.","evidence":["Community and social service wages expose the low- and mid-wage care workforce where public funding, staffing shortages, and demand for human contact dominate. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in behavioral health, counseling, and community services. The lower tail covers constrained public budgets and nonprofit funding limits."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_p90_wage_2025_usd: 97630, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'care_services_shortage_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in behavioral health, counseling, and community services. The lower tail covers constrained public budgets and nonprofit funding limits."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 90th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in behavioral health, counseling, and community services. The lower tail covers constrained public budgets and nonprofit funding limits."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-community-social-service-90th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-community-social-service-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.53593333944984b0","runId":"run.oews-community-social-service-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.53593333944984b0","predictionId":"oews-community-social-service-90th-percentile-wage-may-2026","specId":"spec.oews-community-social-service-90th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $97,630."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_21_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_21_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 97630, 80% interval [97130, 98130]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 97630, 80% interval [97130, 98130]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-community-social-service-90th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-legal-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.22629977e7827417","runId":"run.oews-legal-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.22629977e7827417","predictionId":"oews-legal-10th-percentile-wage-may-2026","specId":"spec.oews-legal-10th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Legal wages test whether document automation and AI research tools compress support tasks while preserving or increasing demand for higher-skill legal work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"23-0000\", statistic: \"p10\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Legal wages test whether document automation and AI research tools compress support tasks while preserving or increasing demand for higher-skill legal work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000023000011\", release: \"May 2025\", datatype: \"Annual 10th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Legal wages test whether document automation and AI research tools compress support tasks while preserving or increasing demand for higher-skill legal work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5300, distribution present, forecast step count 1.","evidence":["Legal wages test whether document automation and AI research tools compress support tasks while preserving or increasing demand for higher-skill legal work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is moderate professional wage growth with a composition shift away from lower-paid routine document work. The lower tail covers slower legal demand and stronger task substitution in research and drafting."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 10th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is moderate professional wage growth with a composition shift away from lower-paid routine document work. The lower tail covers slower legal demand and stronger task substitution in research and drafting."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-legal-10th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-legal-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.30618d2c27e9cb1a","runId":"run.oews-legal-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.30618d2c27e9cb1a","predictionId":"oews-legal-10th-percentile-wage-may-2026","specId":"spec.oews-legal-10th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $49,400."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_23_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_23_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 49400, 80% interval [48900, 49900]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 49400, 80% interval [48900, 49900]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-legal-10th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-legal-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.3e3f63b73eaeeab3","runId":"run.oews-legal-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.3e3f63b73eaeeab3","predictionId":"oews-legal-25th-percentile-wage-may-2026","specId":"spec.oews-legal-25th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Legal wages test whether document automation and AI research tools compress support tasks while preserving or increasing demand for higher-skill legal work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"23-0000\", statistic: \"p25\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Legal wages test whether document automation and AI research tools compress support tasks while preserving or increasing demand for higher-skill legal work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000023000012\", release: \"May 2025\", datatype: \"Annual 25th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Legal wages test whether document automation and AI research tools compress support tasks while preserving or increasing demand for higher-skill legal work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6900, distribution present, forecast step count 1.","evidence":["Legal wages test whether document automation and AI research tools compress support tasks while preserving or increasing demand for higher-skill legal work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is moderate professional wage growth with a composition shift away from lower-paid routine document work. The lower tail covers slower legal demand and stronger task substitution in research and drafting."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 25th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is moderate professional wage growth with a composition shift away from lower-paid routine document work. The lower tail covers slower legal demand and stronger task substitution in research and drafting."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-legal-25th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-legal-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.d6ce1d3207a379ed","runId":"run.oews-legal-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.d6ce1d3207a379ed","predictionId":"oews-legal-25th-percentile-wage-may-2026","specId":"spec.oews-legal-25th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $64,800."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_23_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_23_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 64800, 80% interval [64300, 65300]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 64800, 80% interval [64300, 65300]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-legal-25th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-legal-median-wage-may-2026.2026-06-21T13-35-00-04-00.70b7118682ace102","runId":"run.oews-legal-median-wage-may-2026.2026-06-21T13-35-00-04-00.70b7118682ace102","predictionId":"oews-legal-median-wage-may-2026","specId":"spec.oews-legal-median-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Legal wages test whether document automation and AI research tools compress support tasks while preserving or increasing demand for higher-skill legal work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000023000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Legal wages test whether document automation and AI research tools compress support tasks while preserving or increasing demand for higher-skill legal work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000023000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Legal wages test whether document automation and AI research tools compress support tasks while preserving or increasing demand for higher-skill legal work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 10900, distribution present, forecast step count 1.","evidence":["Legal wages test whether document automation and AI research tools compress support tasks while preserving or increasing demand for higher-skill legal work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is moderate professional wage growth with a composition shift away from lower-paid routine document work. The lower tail covers slower legal demand and stronger task substitution in research and drafting."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual median wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is moderate professional wage growth with a composition shift away from lower-paid routine document work. The lower tail covers slower legal demand and stronger task substitution in research and drafting."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-legal-median-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-legal-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.111a456e61658ba8","runId":"run.oews-legal-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.111a456e61658ba8","predictionId":"oews-legal-median-wage-may-2026","specId":"spec.oews-legal-median-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_23_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_23_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_23_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 102500, 80% interval [102000, 103000]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 102500, 80% interval [102000, 103000]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-legal-median-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-legal-mean-wage-may-2026.2026-06-21T13-35-00-04-00.239bf30c8b9bd009","runId":"run.oews-legal-mean-wage-may-2026.2026-06-21T13-35-00-04-00.239bf30c8b9bd009","predictionId":"oews-legal-mean-wage-may-2026","specId":"spec.oews-legal-mean-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Legal wages test whether document automation and AI research tools compress support tasks while preserving or increasing demand for higher-skill legal work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"23-0000\", statistic: \"mean\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Legal wages test whether document automation and AI research tools compress support tasks while preserving or increasing demand for higher-skill legal work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000023000004\", release: \"May 2025\", datatype: \"Annual mean wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Legal wages test whether document automation and AI research tools compress support tasks while preserving or increasing demand for higher-skill legal work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 14800, distribution present, forecast step count 1.","evidence":["Legal wages test whether document automation and AI research tools compress support tasks while preserving or increasing demand for higher-skill legal work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is moderate professional wage growth with a composition shift away from lower-paid routine document work. The lower tail covers slower legal demand and stronger task substitution in research and drafting."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual mean wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is moderate professional wage growth with a composition shift away from lower-paid routine document work. The lower tail covers slower legal demand and stronger task substitution in research and drafting."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-legal-mean-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-legal-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.52ea9a3cd4766b2e","runId":"run.oews-legal-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.52ea9a3cd4766b2e","predictionId":"oews-legal-mean-wage-may-2026","specId":"spec.oews-legal-mean-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $139,510."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_23_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_23_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 139510, 80% interval [139010, 140010]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 139510, 80% interval [139010, 140010]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-legal-mean-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-legal-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.e117e81e340baa05","runId":"run.oews-legal-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.e117e81e340baa05","predictionId":"oews-legal-75th-percentile-wage-may-2026","specId":"spec.oews-legal-75th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Legal wages test whether document automation and AI research tools compress support tasks while preserving or increasing demand for higher-skill legal work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"23-0000\", statistic: \"p75\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Legal wages test whether document automation and AI research tools compress support tasks while preserving or increasing demand for higher-skill legal work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000023000014\", release: \"May 2025\", datatype: \"Annual 75th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Legal wages test whether document automation and AI research tools compress support tasks while preserving or increasing demand for higher-skill legal work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 18500, distribution present, forecast step count 1.","evidence":["Legal wages test whether document automation and AI research tools compress support tasks while preserving or increasing demand for higher-skill legal work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is moderate professional wage growth with a composition shift away from lower-paid routine document work. The lower tail covers slower legal demand and stronger task substitution in research and drafting."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 75th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is moderate professional wage growth with a composition shift away from lower-paid routine document work. The lower tail covers slower legal demand and stronger task substitution in research and drafting."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-legal-75th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-legal-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.6d55c67c730c078a","runId":"run.oews-legal-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.6d55c67c730c078a","predictionId":"oews-legal-75th-percentile-wage-may-2026","specId":"spec.oews-legal-75th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $174,620."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_23_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_23_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 174620, 80% interval [174120, 175120]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 174620, 80% interval [174120, 175120]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-legal-75th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-legal-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.9433287c320197de","runId":"run.oews-legal-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.9433287c320197de","predictionId":"oews-legal-90th-percentile-wage-may-2026","specId":"spec.oews-legal-90th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Legal wages test whether document automation and AI research tools compress support tasks while preserving or increasing demand for higher-skill legal work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"23-0000\", statistic: \"p90\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Legal wages test whether document automation and AI research tools compress support tasks while preserving or increasing demand for higher-skill legal work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000023000015\", release: \"May 2025\", datatype: \"Annual 90th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Legal wages test whether document automation and AI research tools compress support tasks while preserving or increasing demand for higher-skill legal work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 30500, distribution present, forecast step count 1.","evidence":["Legal wages test whether document automation and AI research tools compress support tasks while preserving or increasing demand for higher-skill legal work. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is moderate professional wage growth with a composition shift away from lower-paid routine document work. The lower tail covers slower legal demand and stronger task substitution in research and drafting."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 90th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is moderate professional wage growth with a composition shift away from lower-paid routine document work. The lower tail covers slower legal demand and stronger task substitution in research and drafting."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-legal-90th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-legal-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.e6cf431fc91bfc6a","runId":"run.oews-legal-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.e6cf431fc91bfc6a","predictionId":"oews-legal-90th-percentile-wage-may-2026","specId":"spec.oews-legal-90th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $287,070."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_23_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_23_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 287070, 80% interval [286570, 287570]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 287070, 80% interval [286570, 287570]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-legal-90th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-education-library-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.e6606749ad3fbe33","runId":"run.oews-education-library-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.e6606749ad3fbe33","predictionId":"oews-education-library-10th-percentile-wage-may-2026","specId":"spec.oews-education-library-10th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Education and library wages give Thesis a public-sector-heavy wage target where budget cycles, staffing pressure, and AI tutoring tools interact. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"25-0000\", statistic: \"p10\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Education and library wages give Thesis a public-sector-heavy wage target where budget cycles, staffing pressure, and AI tutoring tools interact. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000025000011\", release: \"May 2025\", datatype: \"Annual 10th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Education and library wages give Thesis a public-sector-heavy wage target where budget cycles, staffing pressure, and AI tutoring tools interact. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3500, distribution present, forecast step count 1.","evidence":["Education and library wages give Thesis a public-sector-heavy wage target where budget cycles, staffing pressure, and AI tutoring tools interact. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued teacher and instructor wage pressure within state and local budget constraints. The lower tail covers weak education budgets and limited salary schedule increases."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Education and library wages give Thesis a public-sector-heavy wage target where budget cycles, staffing pressure, and AI tutoring tools interact. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool result: { base_p10_wage_2025_usd: 32990, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'education_budget_and_staffing_pressure' }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 10th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued teacher and instructor wage pressure within state and local budget constraints. The lower tail covers weak education budgets and limited salary schedule increases."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-education-library-10th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-education-library-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.a35b9542219756e0","runId":"run.oews-education-library-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.a35b9542219756e0","predictionId":"oews-education-library-10th-percentile-wage-may-2026","specId":"spec.oews-education-library-10th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $32,990."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_25_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_25_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 32990, 80% interval [32490, 33490]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 32990, 80% interval [32490, 33490]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-education-library-10th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-education-library-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.cf86257a1bdc292e","runId":"run.oews-education-library-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.cf86257a1bdc292e","predictionId":"oews-education-library-25th-percentile-wage-may-2026","specId":"spec.oews-education-library-25th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Education and library wages give Thesis a public-sector-heavy wage target where budget cycles, staffing pressure, and AI tutoring tools interact. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"25-0000\", statistic: \"p25\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Education and library wages give Thesis a public-sector-heavy wage target where budget cycles, staffing pressure, and AI tutoring tools interact. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000025000012\", release: \"May 2025\", datatype: \"Annual 25th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Education and library wages give Thesis a public-sector-heavy wage target where budget cycles, staffing pressure, and AI tutoring tools interact. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4700, distribution present, forecast step count 1.","evidence":["Education and library wages give Thesis a public-sector-heavy wage target where budget cycles, staffing pressure, and AI tutoring tools interact. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued teacher and instructor wage pressure within state and local budget constraints. The lower tail covers weak education budgets and limited salary schedule increases."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Education and library wages give Thesis a public-sector-heavy wage target where budget cycles, staffing pressure, and AI tutoring tools interact. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool result: { base_p25_wage_2025_usd: 43900, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'education_budget_and_staffing_pressure' }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 25th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued teacher and instructor wage pressure within state and local budget constraints. The lower tail covers weak education budgets and limited salary schedule increases."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-education-library-25th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-education-library-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.5d169a827843a061","runId":"run.oews-education-library-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.5d169a827843a061","predictionId":"oews-education-library-25th-percentile-wage-may-2026","specId":"spec.oews-education-library-25th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $43,900."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_25_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_25_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 43900, 80% interval [43400, 44400]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 43900, 80% interval [43400, 44400]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-education-library-25th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-education-library-median-wage-may-2026.2026-06-21T13-35-00-04-00.5f6194b035a21428","runId":"run.oews-education-library-median-wage-may-2026.2026-06-21T13-35-00-04-00.5f6194b035a21428","predictionId":"oews-education-library-median-wage-may-2026","specId":"spec.oews-education-library-median-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Education and library wages give Thesis a public-sector-heavy wage target where budget cycles, staffing pressure, and AI tutoring tools interact. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000025000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Education and library wages give Thesis a public-sector-heavy wage target where budget cycles, staffing pressure, and AI tutoring tools interact. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000025000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Education and library wages give Thesis a public-sector-heavy wage target where budget cycles, staffing pressure, and AI tutoring tools interact. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6500, distribution present, forecast step count 1.","evidence":["Education and library wages give Thesis a public-sector-heavy wage target where budget cycles, staffing pressure, and AI tutoring tools interact. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued teacher and instructor wage pressure within state and local budget constraints. The lower tail covers weak education budgets and limited salary schedule increases."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Education and library wages give Thesis a public-sector-heavy wage target where budget cycles, staffing pressure, and AI tutoring tools interact. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool result: { base_median_wage_2025_usd: 60570, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'education_budget_and_staffing_pressure' }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual median wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued teacher and instructor wage pressure within state and local budget constraints. The lower tail covers weak education budgets and limited salary schedule increases."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-education-library-median-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-education-library-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.5469e6454a23727e","runId":"run.oews-education-library-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.5469e6454a23727e","predictionId":"oews-education-library-median-wage-may-2026","specId":"spec.oews-education-library-median-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_25_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_25_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_25_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 60570, 80% interval [60070, 61070]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 60570, 80% interval [60070, 61070]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-education-library-median-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-education-library-mean-wage-may-2026.2026-06-21T13-35-00-04-00.17a6e591fe6f4e66","runId":"run.oews-education-library-mean-wage-may-2026.2026-06-21T13-35-00-04-00.17a6e591fe6f4e66","predictionId":"oews-education-library-mean-wage-may-2026","specId":"spec.oews-education-library-mean-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Education and library wages give Thesis a public-sector-heavy wage target where budget cycles, staffing pressure, and AI tutoring tools interact. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"25-0000\", statistic: \"mean\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Education and library wages give Thesis a public-sector-heavy wage target where budget cycles, staffing pressure, and AI tutoring tools interact. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000025000004\", release: \"May 2025\", datatype: \"Annual mean wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Education and library wages give Thesis a public-sector-heavy wage target where budget cycles, staffing pressure, and AI tutoring tools interact. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 7100, distribution present, forecast step count 1.","evidence":["Education and library wages give Thesis a public-sector-heavy wage target where budget cycles, staffing pressure, and AI tutoring tools interact. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued teacher and instructor wage pressure within state and local budget constraints. The lower tail covers weak education budgets and limited salary schedule increases."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Education and library wages give Thesis a public-sector-heavy wage target where budget cycles, staffing pressure, and AI tutoring tools interact. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool result: { base_mean_wage_2025_usd: 67540, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'education_budget_and_staffing_pressure' }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual mean wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued teacher and instructor wage pressure within state and local budget constraints. The lower tail covers weak education budgets and limited salary schedule increases."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-education-library-mean-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-education-library-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.dd84ffe0407ff2be","runId":"run.oews-education-library-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.dd84ffe0407ff2be","predictionId":"oews-education-library-mean-wage-may-2026","specId":"spec.oews-education-library-mean-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $67,540."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_25_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_25_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 67540, 80% interval [67040, 68040]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 67540, 80% interval [67040, 68040]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-education-library-mean-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-education-library-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.3191a255a8ecd358","runId":"run.oews-education-library-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.3191a255a8ecd358","predictionId":"oews-education-library-75th-percentile-wage-may-2026","specId":"spec.oews-education-library-75th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Education and library wages give Thesis a public-sector-heavy wage target where budget cycles, staffing pressure, and AI tutoring tools interact. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"25-0000\", statistic: \"p75\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Education and library wages give Thesis a public-sector-heavy wage target where budget cycles, staffing pressure, and AI tutoring tools interact. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000025000014\", release: \"May 2025\", datatype: \"Annual 75th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Education and library wages give Thesis a public-sector-heavy wage target where budget cycles, staffing pressure, and AI tutoring tools interact. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 8400, distribution present, forecast step count 1.","evidence":["Education and library wages give Thesis a public-sector-heavy wage target where budget cycles, staffing pressure, and AI tutoring tools interact. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued teacher and instructor wage pressure within state and local budget constraints. The lower tail covers weak education budgets and limited salary schedule increases."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Education and library wages give Thesis a public-sector-heavy wage target where budget cycles, staffing pressure, and AI tutoring tools interact. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool result: { base_p75_wage_2025_usd: 79470, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'education_budget_and_staffing_pressure' }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 75th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued teacher and instructor wage pressure within state and local budget constraints. The lower tail covers weak education budgets and limited salary schedule increases."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-education-library-75th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-education-library-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.c2a5432d1b758776","runId":"run.oews-education-library-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.c2a5432d1b758776","predictionId":"oews-education-library-75th-percentile-wage-may-2026","specId":"spec.oews-education-library-75th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $79,470."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_25_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_25_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 79470, 80% interval [78970, 79970]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 79470, 80% interval [78970, 79970]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-education-library-75th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-education-library-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.d393f12b30cfb2af","runId":"run.oews-education-library-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.d393f12b30cfb2af","predictionId":"oews-education-library-90th-percentile-wage-may-2026","specId":"spec.oews-education-library-90th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Education and library wages give Thesis a public-sector-heavy wage target where budget cycles, staffing pressure, and AI tutoring tools interact. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"25-0000\", statistic: \"p90\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Education and library wages give Thesis a public-sector-heavy wage target where budget cycles, staffing pressure, and AI tutoring tools interact. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000025000015\", release: \"May 2025\", datatype: \"Annual 90th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Education and library wages give Thesis a public-sector-heavy wage target where budget cycles, staffing pressure, and AI tutoring tools interact. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 11200, distribution present, forecast step count 1.","evidence":["Education and library wages give Thesis a public-sector-heavy wage target where budget cycles, staffing pressure, and AI tutoring tools interact. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued teacher and instructor wage pressure within state and local budget constraints. The lower tail covers weak education budgets and limited salary schedule increases."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Education and library wages give Thesis a public-sector-heavy wage target where budget cycles, staffing pressure, and AI tutoring tools interact. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool result: { base_p90_wage_2025_usd: 105240, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'education_budget_and_staffing_pressure' }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 90th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued teacher and instructor wage pressure within state and local budget constraints. The lower tail covers weak education budgets and limited salary schedule increases."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-education-library-90th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-education-library-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.142d87eaf0c8354d","runId":"run.oews-education-library-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.142d87eaf0c8354d","predictionId":"oews-education-library-90th-percentile-wage-may-2026","specId":"spec.oews-education-library-90th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $105,240."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_25_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_25_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 105240, 80% interval [104740, 105740]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 105240, 80% interval [104740, 105740]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-education-library-90th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-arts-media-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.7096dc75dea937ba","runId":"run.oews-arts-media-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.7096dc75dea937ba","predictionId":"oews-arts-media-10th-percentile-wage-may-2026","specId":"spec.oews-arts-media-10th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.46,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Arts and media wages are a direct creative-work target for generative AI exposure, advertising demand, and platform-driven composition changes. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"27-0000\", statistic: \"p10\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Arts and media wages are a direct creative-work target for generative AI exposure, advertising demand, and platform-driven composition changes. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000027000011\", release: \"May 2025\", datatype: \"Annual 10th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Arts and media wages are a direct creative-work target for generative AI exposure, advertising demand, and platform-driven composition changes. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3700, distribution present, forecast step count 1.","evidence":["Arts and media wages are a direct creative-work target for generative AI exposure, advertising demand, and platform-driven composition changes. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is positive nominal wage growth partly offset by weak media hiring and creative-task automation. The lower tail covers continued advertising softness and substitution in routine design and content tasks."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is positive nominal wage growth partly offset by weak media hiring and creative-task automation. The lower tail covers continued advertising softness and substitution in routine design and content tasks."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 10th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is positive nominal wage growth partly offset by weak media hiring and creative-task automation. The lower tail covers continued advertising softness and substitution in routine design and content tasks."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-arts-media-10th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-arts-media-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.85190b2b79554901","runId":"run.oews-arts-media-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.85190b2b79554901","predictionId":"oews-arts-media-10th-percentile-wage-may-2026","specId":"spec.oews-arts-media-10th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $34,700."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_27_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_27_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 34700, 80% interval [34200, 35200]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 34700, 80% interval [34200, 35200]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-arts-media-10th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-arts-media-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.8ff0c21dcf2a67d2","runId":"run.oews-arts-media-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.8ff0c21dcf2a67d2","predictionId":"oews-arts-media-25th-percentile-wage-may-2026","specId":"spec.oews-arts-media-25th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.46,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Arts and media wages are a direct creative-work target for generative AI exposure, advertising demand, and platform-driven composition changes. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"27-0000\", statistic: \"p25\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Arts and media wages are a direct creative-work target for generative AI exposure, advertising demand, and platform-driven composition changes. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000027000012\", release: \"May 2025\", datatype: \"Annual 25th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Arts and media wages are a direct creative-work target for generative AI exposure, advertising demand, and platform-driven composition changes. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4800, distribution present, forecast step count 1.","evidence":["Arts and media wages are a direct creative-work target for generative AI exposure, advertising demand, and platform-driven composition changes. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is positive nominal wage growth partly offset by weak media hiring and creative-task automation. The lower tail covers continued advertising softness and substitution in routine design and content tasks."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is positive nominal wage growth partly offset by weak media hiring and creative-task automation. The lower tail covers continued advertising softness and substitution in routine design and content tasks."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 25th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is positive nominal wage growth partly offset by weak media hiring and creative-task automation. The lower tail covers continued advertising softness and substitution in routine design and content tasks."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-arts-media-25th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-arts-media-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.582f5c60f333415b","runId":"run.oews-arts-media-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.582f5c60f333415b","predictionId":"oews-arts-media-25th-percentile-wage-may-2026","specId":"spec.oews-arts-media-25th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $44,720."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_27_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_27_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 44720, 80% interval [44220, 45220]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 44720, 80% interval [44220, 45220]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-arts-media-25th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-arts-media-median-wage-may-2026.2026-06-21T13-35-00-04-00.fd4a0290d37199e9","runId":"run.oews-arts-media-median-wage-may-2026.2026-06-21T13-35-00-04-00.fd4a0290d37199e9","predictionId":"oews-arts-media-median-wage-may-2026","specId":"spec.oews-arts-media-median-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.46,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Arts and media wages are a direct creative-work target for generative AI exposure, advertising demand, and platform-driven composition changes. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000027000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Arts and media wages are a direct creative-work target for generative AI exposure, advertising demand, and platform-driven composition changes. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000027000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Arts and media wages are a direct creative-work target for generative AI exposure, advertising demand, and platform-driven composition changes. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6600, distribution present, forecast step count 1.","evidence":["Arts and media wages are a direct creative-work target for generative AI exposure, advertising demand, and platform-driven composition changes. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is positive nominal wage growth partly offset by weak media hiring and creative-task automation. The lower tail covers continued advertising softness and substitution in routine design and content tasks."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is positive nominal wage growth partly offset by weak media hiring and creative-task automation. The lower tail covers continued advertising softness and substitution in routine design and content tasks."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual median wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is positive nominal wage growth partly offset by weak media hiring and creative-task automation. The lower tail covers continued advertising softness and substitution in routine design and content tasks."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-arts-media-median-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-arts-media-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.5f50f8bb76cc0071","runId":"run.oews-arts-media-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.5f50f8bb76cc0071","predictionId":"oews-arts-media-median-wage-may-2026","specId":"spec.oews-arts-media-median-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_27_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_27_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_27_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 62750, 80% interval [62250, 63250]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 62750, 80% interval [62250, 63250]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-arts-media-median-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-arts-media-mean-wage-may-2026.2026-06-21T13-35-00-04-00.9dadf2e4c0343182","runId":"run.oews-arts-media-mean-wage-may-2026.2026-06-21T13-35-00-04-00.9dadf2e4c0343182","predictionId":"oews-arts-media-mean-wage-may-2026","specId":"spec.oews-arts-media-mean-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.46,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Arts and media wages are a direct creative-work target for generative AI exposure, advertising demand, and platform-driven composition changes. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"27-0000\", statistic: \"mean\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Arts and media wages are a direct creative-work target for generative AI exposure, advertising demand, and platform-driven composition changes. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000027000004\", release: \"May 2025\", datatype: \"Annual mean wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Arts and media wages are a direct creative-work target for generative AI exposure, advertising demand, and platform-driven composition changes. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 8500, distribution present, forecast step count 1.","evidence":["Arts and media wages are a direct creative-work target for generative AI exposure, advertising demand, and platform-driven composition changes. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is positive nominal wage growth partly offset by weak media hiring and creative-task automation. The lower tail covers continued advertising softness and substitution in routine design and content tasks."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is positive nominal wage growth partly offset by weak media hiring and creative-task automation. The lower tail covers continued advertising softness and substitution in routine design and content tasks."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual mean wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is positive nominal wage growth partly offset by weak media hiring and creative-task automation. The lower tail covers continued advertising softness and substitution in routine design and content tasks."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-arts-media-mean-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-arts-media-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.6368e117fc6c00a5","runId":"run.oews-arts-media-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.6368e117fc6c00a5","predictionId":"oews-arts-media-mean-wage-may-2026","specId":"spec.oews-arts-media-mean-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $79,790."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_27_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_27_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 79790, 80% interval [79290, 80290]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 79790, 80% interval [79290, 80290]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-arts-media-mean-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-arts-media-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.99a8e1b43cbd42fa","runId":"run.oews-arts-media-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.99a8e1b43cbd42fa","predictionId":"oews-arts-media-75th-percentile-wage-may-2026","specId":"spec.oews-arts-media-75th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.46,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Arts and media wages are a direct creative-work target for generative AI exposure, advertising demand, and platform-driven composition changes. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"27-0000\", statistic: \"p75\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Arts and media wages are a direct creative-work target for generative AI exposure, advertising demand, and platform-driven composition changes. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000027000014\", release: \"May 2025\", datatype: \"Annual 75th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Arts and media wages are a direct creative-work target for generative AI exposure, advertising demand, and platform-driven composition changes. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 10000, distribution present, forecast step count 1.","evidence":["Arts and media wages are a direct creative-work target for generative AI exposure, advertising demand, and platform-driven composition changes. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is positive nominal wage growth partly offset by weak media hiring and creative-task automation. The lower tail covers continued advertising softness and substitution in routine design and content tasks."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is positive nominal wage growth partly offset by weak media hiring and creative-task automation. The lower tail covers continued advertising softness and substitution in routine design and content tasks."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 75th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is positive nominal wage growth partly offset by weak media hiring and creative-task automation. The lower tail covers continued advertising softness and substitution in routine design and content tasks."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-arts-media-75th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-arts-media-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.53212b15cb76241a","runId":"run.oews-arts-media-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.53212b15cb76241a","predictionId":"oews-arts-media-75th-percentile-wage-may-2026","specId":"spec.oews-arts-media-75th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $94,530."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_27_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_27_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 94530, 80% interval [94030, 95030]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 94530, 80% interval [94030, 95030]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-arts-media-75th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-arts-media-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.677aac0eed3c73ec","runId":"run.oews-arts-media-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.677aac0eed3c73ec","predictionId":"oews-arts-media-90th-percentile-wage-may-2026","specId":"spec.oews-arts-media-90th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.46,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Arts and media wages are a direct creative-work target for generative AI exposure, advertising demand, and platform-driven composition changes. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"27-0000\", statistic: \"p90\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Arts and media wages are a direct creative-work target for generative AI exposure, advertising demand, and platform-driven composition changes. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000027000015\", release: \"May 2025\", datatype: \"Annual 90th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Arts and media wages are a direct creative-work target for generative AI exposure, advertising demand, and platform-driven composition changes. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 14300, distribution present, forecast step count 1.","evidence":["Arts and media wages are a direct creative-work target for generative AI exposure, advertising demand, and platform-driven composition changes. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is positive nominal wage growth partly offset by weak media hiring and creative-task automation. The lower tail covers continued advertising softness and substitution in routine design and content tasks."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is positive nominal wage growth partly offset by weak media hiring and creative-task automation. The lower tail covers continued advertising softness and substitution in routine design and content tasks."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 90th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is positive nominal wage growth partly offset by weak media hiring and creative-task automation. The lower tail covers continued advertising softness and substitution in routine design and content tasks."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-arts-media-90th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-arts-media-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.a7cd056794c5c0f9","runId":"run.oews-arts-media-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.a7cd056794c5c0f9","predictionId":"oews-arts-media-90th-percentile-wage-may-2026","specId":"spec.oews-arts-media-90th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $134,900."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_27_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_27_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 134900, 80% interval [134400, 135400]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 134900, 80% interval [134400, 135400]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-arts-media-90th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-healthcare-practitioners-technical-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.c6ecc3705d68c855","runId":"run.oews-healthcare-practitioners-technical-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.c6ecc3705d68c855","predictionId":"oews-healthcare-practitioners-technical-10th-percentile-wage-may-2026","specId":"spec.oews-healthcare-practitioners-technical-10th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Healthcare practitioner wages are a high-demand, licensure-heavy comparator where demographics and care utilization should dominate near-term AI substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"29-0000\", statistic: \"p10\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Healthcare practitioner wages are a high-demand, licensure-heavy comparator where demographics and care utilization should dominate near-term AI substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000029000011\", release: \"May 2025\", datatype: \"Annual 10th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Healthcare practitioner wages are a high-demand, licensure-heavy comparator where demographics and care utilization should dominate near-term AI substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4900, distribution present, forecast step count 1.","evidence":["Healthcare practitioner wages are a high-demand, licensure-heavy comparator where demographics and care utilization should dominate near-term AI substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is strong care demand and licensure constraints supporting above-average wage growth. The lower tail covers provider margin pressure and slower hiring in lower-margin settings."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_p10_wage_2025_usd: 46270, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'licensed_healthcare_shortage_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is strong care demand and licensure constraints supporting above-average wage growth. The lower tail covers provider margin pressure and slower hiring in lower-margin settings."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 10th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is strong care demand and licensure constraints supporting above-average wage growth. The lower tail covers provider margin pressure and slower hiring in lower-margin settings."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-healthcare-practitioners-technical-10th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-healthcare-practitioners-technical-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.523e97920d9baaf4","runId":"run.oews-healthcare-practitioners-technical-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.523e97920d9baaf4","predictionId":"oews-healthcare-practitioners-technical-10th-percentile-wage-may-2026","specId":"spec.oews-healthcare-practitioners-technical-10th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $46,270."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_29_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_29_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 46270, 80% interval [45770, 46770]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 46270, 80% interval [45770, 46770]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-healthcare-practitioners-technical-10th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-healthcare-practitioners-technical-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.c0942eae63d33b83","runId":"run.oews-healthcare-practitioners-technical-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.c0942eae63d33b83","predictionId":"oews-healthcare-practitioners-technical-25th-percentile-wage-may-2026","specId":"spec.oews-healthcare-practitioners-technical-25th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Healthcare practitioner wages are a high-demand, licensure-heavy comparator where demographics and care utilization should dominate near-term AI substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"29-0000\", statistic: \"p25\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Healthcare practitioner wages are a high-demand, licensure-heavy comparator where demographics and care utilization should dominate near-term AI substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000029000012\", release: \"May 2025\", datatype: \"Annual 25th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Healthcare practitioner wages are a high-demand, licensure-heavy comparator where demographics and care utilization should dominate near-term AI substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6700, distribution present, forecast step count 1.","evidence":["Healthcare practitioner wages are a high-demand, licensure-heavy comparator where demographics and care utilization should dominate near-term AI substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is strong care demand and licensure constraints supporting above-average wage growth. The lower tail covers provider margin pressure and slower hiring in lower-margin settings."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_p25_wage_2025_usd: 63860, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'licensed_healthcare_shortage_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is strong care demand and licensure constraints supporting above-average wage growth. The lower tail covers provider margin pressure and slower hiring in lower-margin settings."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 25th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is strong care demand and licensure constraints supporting above-average wage growth. The lower tail covers provider margin pressure and slower hiring in lower-margin settings."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-healthcare-practitioners-technical-25th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-healthcare-practitioners-technical-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.a687635a58650c84","runId":"run.oews-healthcare-practitioners-technical-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.a687635a58650c84","predictionId":"oews-healthcare-practitioners-technical-25th-percentile-wage-may-2026","specId":"spec.oews-healthcare-practitioners-technical-25th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $63,860."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_29_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_29_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 63860, 80% interval [63360, 64360]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 63860, 80% interval [63360, 64360]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-healthcare-practitioners-technical-25th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-healthcare-practitioners-technical-median-wage-may-2026.2026-06-21T13-35-00-04-00.ffcf0c67df98bbb3","runId":"run.oews-healthcare-practitioners-technical-median-wage-may-2026.2026-06-21T13-35-00-04-00.ffcf0c67df98bbb3","predictionId":"oews-healthcare-practitioners-technical-median-wage-may-2026","specId":"spec.oews-healthcare-practitioners-technical-median-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Healthcare practitioner wages are a high-demand, licensure-heavy comparator where demographics and care utilization should dominate near-term AI substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000029000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Healthcare practitioner wages are a high-demand, licensure-heavy comparator where demographics and care utilization should dominate near-term AI substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000029000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Healthcare practitioner wages are a high-demand, licensure-heavy comparator where demographics and care utilization should dominate near-term AI substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 9200, distribution present, forecast step count 1.","evidence":["Healthcare practitioner wages are a high-demand, licensure-heavy comparator where demographics and care utilization should dominate near-term AI substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is strong care demand and licensure constraints supporting above-average wage growth. The lower tail covers provider margin pressure and slower hiring in lower-margin settings."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_median_wage_2025_usd: 86530, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'licensed_healthcare_shortage_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is strong care demand and licensure constraints supporting above-average wage growth. The lower tail covers provider margin pressure and slower hiring in lower-margin settings."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual median wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is strong care demand and licensure constraints supporting above-average wage growth. The lower tail covers provider margin pressure and slower hiring in lower-margin settings."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-healthcare-practitioners-technical-median-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-healthcare-practitioners-technical-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.f874039ac8be7204","runId":"run.oews-healthcare-practitioners-technical-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.f874039ac8be7204","predictionId":"oews-healthcare-practitioners-technical-median-wage-may-2026","specId":"spec.oews-healthcare-practitioners-technical-median-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_29_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_29_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_29_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 86530, 80% interval [86030, 87030]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 86530, 80% interval [86030, 87030]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-healthcare-practitioners-technical-median-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-healthcare-practitioners-technical-mean-wage-may-2026.2026-06-21T13-35-00-04-00.b04a71cd2494625a","runId":"run.oews-healthcare-practitioners-technical-mean-wage-may-2026.2026-06-21T13-35-00-04-00.b04a71cd2494625a","predictionId":"oews-healthcare-practitioners-technical-mean-wage-may-2026","specId":"spec.oews-healthcare-practitioners-technical-mean-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Healthcare practitioner wages are a high-demand, licensure-heavy comparator where demographics and care utilization should dominate near-term AI substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"29-0000\", statistic: \"mean\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Healthcare practitioner wages are a high-demand, licensure-heavy comparator where demographics and care utilization should dominate near-term AI substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000029000004\", release: \"May 2025\", datatype: \"Annual mean wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Healthcare practitioner wages are a high-demand, licensure-heavy comparator where demographics and care utilization should dominate near-term AI substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 11600, distribution present, forecast step count 1.","evidence":["Healthcare practitioner wages are a high-demand, licensure-heavy comparator where demographics and care utilization should dominate near-term AI substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is strong care demand and licensure constraints supporting above-average wage growth. The lower tail covers provider margin pressure and slower hiring in lower-margin settings."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_mean_wage_2025_usd: 108700, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'licensed_healthcare_shortage_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is strong care demand and licensure constraints supporting above-average wage growth. The lower tail covers provider margin pressure and slower hiring in lower-margin settings."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual mean wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is strong care demand and licensure constraints supporting above-average wage growth. The lower tail covers provider margin pressure and slower hiring in lower-margin settings."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-healthcare-practitioners-technical-mean-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-healthcare-practitioners-technical-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.bfe234110f936002","runId":"run.oews-healthcare-practitioners-technical-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.bfe234110f936002","predictionId":"oews-healthcare-practitioners-technical-mean-wage-may-2026","specId":"spec.oews-healthcare-practitioners-technical-mean-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $108,700."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_29_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_29_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 108700, 80% interval [108200, 109200]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 108700, 80% interval [108200, 109200]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-healthcare-practitioners-technical-mean-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-healthcare-practitioners-technical-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.e37963d4ba41e059","runId":"run.oews-healthcare-practitioners-technical-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.e37963d4ba41e059","predictionId":"oews-healthcare-practitioners-technical-75th-percentile-wage-may-2026","specId":"spec.oews-healthcare-practitioners-technical-75th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Healthcare practitioner wages are a high-demand, licensure-heavy comparator where demographics and care utilization should dominate near-term AI substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"29-0000\", statistic: \"p75\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Healthcare practitioner wages are a high-demand, licensure-heavy comparator where demographics and care utilization should dominate near-term AI substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000029000014\", release: \"May 2025\", datatype: \"Annual 75th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Healthcare practitioner wages are a high-demand, licensure-heavy comparator where demographics and care utilization should dominate near-term AI substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 13100, distribution present, forecast step count 1.","evidence":["Healthcare practitioner wages are a high-demand, licensure-heavy comparator where demographics and care utilization should dominate near-term AI substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is strong care demand and licensure constraints supporting above-average wage growth. The lower tail covers provider margin pressure and slower hiring in lower-margin settings."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_p75_wage_2025_usd: 123540, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'licensed_healthcare_shortage_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is strong care demand and licensure constraints supporting above-average wage growth. The lower tail covers provider margin pressure and slower hiring in lower-margin settings."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 75th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is strong care demand and licensure constraints supporting above-average wage growth. The lower tail covers provider margin pressure and slower hiring in lower-margin settings."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-healthcare-practitioners-technical-75th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-healthcare-practitioners-technical-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.da2e6def5a73ab3e","runId":"run.oews-healthcare-practitioners-technical-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.da2e6def5a73ab3e","predictionId":"oews-healthcare-practitioners-technical-75th-percentile-wage-may-2026","specId":"spec.oews-healthcare-practitioners-technical-75th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $123,540."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_29_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_29_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 123540, 80% interval [123040, 124040]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 123540, 80% interval [123040, 124040]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-healthcare-practitioners-technical-75th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-healthcare-practitioners-technical-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.5b6b6ae94f1d6bac","runId":"run.oews-healthcare-practitioners-technical-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.5b6b6ae94f1d6bac","predictionId":"oews-healthcare-practitioners-technical-90th-percentile-wage-may-2026","specId":"spec.oews-healthcare-practitioners-technical-90th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Healthcare practitioner wages are a high-demand, licensure-heavy comparator where demographics and care utilization should dominate near-term AI substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"29-0000\", statistic: \"p90\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Healthcare practitioner wages are a high-demand, licensure-heavy comparator where demographics and care utilization should dominate near-term AI substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000029000015\", release: \"May 2025\", datatype: \"Annual 90th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Healthcare practitioner wages are a high-demand, licensure-heavy comparator where demographics and care utilization should dominate near-term AI substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 18300, distribution present, forecast step count 1.","evidence":["Healthcare practitioner wages are a high-demand, licensure-heavy comparator where demographics and care utilization should dominate near-term AI substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is strong care demand and licensure constraints supporting above-average wage growth. The lower tail covers provider margin pressure and slower hiring in lower-margin settings."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_p90_wage_2025_usd: 171790, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'licensed_healthcare_shortage_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is strong care demand and licensure constraints supporting above-average wage growth. The lower tail covers provider margin pressure and slower hiring in lower-margin settings."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 90th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is strong care demand and licensure constraints supporting above-average wage growth. The lower tail covers provider margin pressure and slower hiring in lower-margin settings."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-healthcare-practitioners-technical-90th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-healthcare-practitioners-technical-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.c83209b4b897e7c1","runId":"run.oews-healthcare-practitioners-technical-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.c83209b4b897e7c1","predictionId":"oews-healthcare-practitioners-technical-90th-percentile-wage-may-2026","specId":"spec.oews-healthcare-practitioners-technical-90th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $171,790."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_29_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_29_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 171790, 80% interval [171290, 172290]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 171790, 80% interval [171290, 172290]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-healthcare-practitioners-technical-90th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-healthcare-support-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.d2b96bfa7f7bfd86","runId":"run.oews-healthcare-support-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.d2b96bfa7f7bfd86","predictionId":"oews-healthcare-support-10th-percentile-wage-may-2026","specId":"spec.oews-healthcare-support-10th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Healthcare support gives Thesis a low-wage, low-substitution wage target where staffing scarcity and minimum-wage pressure can matter more than software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"31-0000\", statistic: \"p10\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Healthcare support gives Thesis a low-wage, low-substitution wage target where staffing scarcity and minimum-wage pressure can matter more than software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000031000011\", release: \"May 2025\", datatype: \"Annual 10th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Healthcare support gives Thesis a low-wage, low-substitution wage target where staffing scarcity and minimum-wage pressure can matter more than software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3100, distribution present, forecast step count 1.","evidence":["Healthcare support gives Thesis a low-wage, low-substitution wage target where staffing scarcity and minimum-wage pressure can matter more than software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is strong care demand and low-wage service recruitment pressure. The lower tail reflects provider margin constraints and state-level Medicaid funding pressure."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Healthcare support gives Thesis a low-wage, low-substitution wage target where staffing scarcity and minimum-wage pressure can matter more than software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool result: { base_p10_wage_2025_usd: 28980, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'high_staffing_pressure_low_automation_substitution' }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 10th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is strong care demand and low-wage service recruitment pressure. The lower tail reflects provider margin constraints and state-level Medicaid funding pressure."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-healthcare-support-10th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-healthcare-support-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.2ffd59e3d7532031","runId":"run.oews-healthcare-support-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.2ffd59e3d7532031","predictionId":"oews-healthcare-support-10th-percentile-wage-may-2026","specId":"spec.oews-healthcare-support-10th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $28,980."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_31_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_31_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 28980, 80% interval [28480, 29480]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 28980, 80% interval [28480, 29480]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-healthcare-support-10th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-healthcare-support-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.98a33a6e5834d2c6","runId":"run.oews-healthcare-support-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.98a33a6e5834d2c6","predictionId":"oews-healthcare-support-25th-percentile-wage-may-2026","specId":"spec.oews-healthcare-support-25th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Healthcare support gives Thesis a low-wage, low-substitution wage target where staffing scarcity and minimum-wage pressure can matter more than software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"31-0000\", statistic: \"p25\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Healthcare support gives Thesis a low-wage, low-substitution wage target where staffing scarcity and minimum-wage pressure can matter more than software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000031000012\", release: \"May 2025\", datatype: \"Annual 25th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Healthcare support gives Thesis a low-wage, low-substitution wage target where staffing scarcity and minimum-wage pressure can matter more than software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3700, distribution present, forecast step count 1.","evidence":["Healthcare support gives Thesis a low-wage, low-substitution wage target where staffing scarcity and minimum-wage pressure can matter more than software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is strong care demand and low-wage service recruitment pressure. The lower tail reflects provider margin constraints and state-level Medicaid funding pressure."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Healthcare support gives Thesis a low-wage, low-substitution wage target where staffing scarcity and minimum-wage pressure can matter more than software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool result: { base_p25_wage_2025_usd: 34320, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'high_staffing_pressure_low_automation_substitution' }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 25th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is strong care demand and low-wage service recruitment pressure. The lower tail reflects provider margin constraints and state-level Medicaid funding pressure."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-healthcare-support-25th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-healthcare-support-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.8958ef3ed4ba85ce","runId":"run.oews-healthcare-support-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.8958ef3ed4ba85ce","predictionId":"oews-healthcare-support-25th-percentile-wage-may-2026","specId":"spec.oews-healthcare-support-25th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $34,320."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_31_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_31_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 34320, 80% interval [33820, 34820]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 34320, 80% interval [33820, 34820]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-healthcare-support-25th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-healthcare-support-median-wage-may-2026.2026-06-21T13-35-00-04-00.6f95bda1c7d5695a","runId":"run.oews-healthcare-support-median-wage-may-2026.2026-06-21T13-35-00-04-00.6f95bda1c7d5695a","predictionId":"oews-healthcare-support-median-wage-may-2026","specId":"spec.oews-healthcare-support-median-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Healthcare support gives Thesis a low-wage, low-substitution wage target where staffing scarcity and minimum-wage pressure can matter more than software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000031000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Healthcare support gives Thesis a low-wage, low-substitution wage target where staffing scarcity and minimum-wage pressure can matter more than software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000031000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Healthcare support gives Thesis a low-wage, low-substitution wage target where staffing scarcity and minimum-wage pressure can matter more than software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4000, distribution present, forecast step count 1.","evidence":["Healthcare support gives Thesis a low-wage, low-substitution wage target where staffing scarcity and minimum-wage pressure can matter more than software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is strong care demand and low-wage service recruitment pressure. The lower tail reflects provider margin constraints and state-level Medicaid funding pressure."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Healthcare support gives Thesis a low-wage, low-substitution wage target where staffing scarcity and minimum-wage pressure can matter more than software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool result: { base_median_wage_2025_usd: 38340, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'high_staffing_pressure_low_automation_substitution' }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual median wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is strong care demand and low-wage service recruitment pressure. The lower tail reflects provider margin constraints and state-level Medicaid funding pressure."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-healthcare-support-median-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-healthcare-support-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.b3fab6f7ac93b024","runId":"run.oews-healthcare-support-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.b3fab6f7ac93b024","predictionId":"oews-healthcare-support-median-wage-may-2026","specId":"spec.oews-healthcare-support-median-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_31_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_31_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_31_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 38340, 80% interval [37840, 38840]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 38340, 80% interval [37840, 38840]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-healthcare-support-median-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-healthcare-support-mean-wage-may-2026.2026-06-21T13-35-00-04-00.533612907c5fbd43","runId":"run.oews-healthcare-support-mean-wage-may-2026.2026-06-21T13-35-00-04-00.533612907c5fbd43","predictionId":"oews-healthcare-support-mean-wage-may-2026","specId":"spec.oews-healthcare-support-mean-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Healthcare support gives Thesis a low-wage, low-substitution wage target where staffing scarcity and minimum-wage pressure can matter more than software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"31-0000\", statistic: \"mean\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Healthcare support gives Thesis a low-wage, low-substitution wage target where staffing scarcity and minimum-wage pressure can matter more than software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000031000004\", release: \"May 2025\", datatype: \"Annual mean wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Healthcare support gives Thesis a low-wage, low-substitution wage target where staffing scarcity and minimum-wage pressure can matter more than software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4300, distribution present, forecast step count 1.","evidence":["Healthcare support gives Thesis a low-wage, low-substitution wage target where staffing scarcity and minimum-wage pressure can matter more than software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is strong care demand and low-wage service recruitment pressure. The lower tail reflects provider margin constraints and state-level Medicaid funding pressure."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Healthcare support gives Thesis a low-wage, low-substitution wage target where staffing scarcity and minimum-wage pressure can matter more than software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool result: { base_mean_wage_2025_usd: 40800, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'high_staffing_pressure_low_automation_substitution' }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual mean wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is strong care demand and low-wage service recruitment pressure. The lower tail reflects provider margin constraints and state-level Medicaid funding pressure."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-healthcare-support-mean-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-healthcare-support-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.ecc9a7ef039a8ab3","runId":"run.oews-healthcare-support-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.ecc9a7ef039a8ab3","predictionId":"oews-healthcare-support-mean-wage-may-2026","specId":"spec.oews-healthcare-support-mean-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $40,800."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_31_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_31_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 40800, 80% interval [40300, 41300]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 40800, 80% interval [40300, 41300]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-healthcare-support-mean-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-healthcare-support-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.726f544c799724c0","runId":"run.oews-healthcare-support-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.726f544c799724c0","predictionId":"oews-healthcare-support-75th-percentile-wage-may-2026","specId":"spec.oews-healthcare-support-75th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Healthcare support gives Thesis a low-wage, low-substitution wage target where staffing scarcity and minimum-wage pressure can matter more than software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"31-0000\", statistic: \"p75\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Healthcare support gives Thesis a low-wage, low-substitution wage target where staffing scarcity and minimum-wage pressure can matter more than software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000031000014\", release: \"May 2025\", datatype: \"Annual 75th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Healthcare support gives Thesis a low-wage, low-substitution wage target where staffing scarcity and minimum-wage pressure can matter more than software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4900, distribution present, forecast step count 1.","evidence":["Healthcare support gives Thesis a low-wage, low-substitution wage target where staffing scarcity and minimum-wage pressure can matter more than software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is strong care demand and low-wage service recruitment pressure. The lower tail reflects provider margin constraints and state-level Medicaid funding pressure."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Healthcare support gives Thesis a low-wage, low-substitution wage target where staffing scarcity and minimum-wage pressure can matter more than software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool result: { base_p75_wage_2025_usd: 45930, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'high_staffing_pressure_low_automation_substitution' }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 75th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is strong care demand and low-wage service recruitment pressure. The lower tail reflects provider margin constraints and state-level Medicaid funding pressure."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-healthcare-support-75th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-healthcare-support-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.1445e6b88f5c9b35","runId":"run.oews-healthcare-support-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.1445e6b88f5c9b35","predictionId":"oews-healthcare-support-75th-percentile-wage-may-2026","specId":"spec.oews-healthcare-support-75th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $45,930."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_31_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_31_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 45930, 80% interval [45430, 46430]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 45930, 80% interval [45430, 46430]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-healthcare-support-75th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-healthcare-support-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.5609340ec79f92be","runId":"run.oews-healthcare-support-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.5609340ec79f92be","predictionId":"oews-healthcare-support-90th-percentile-wage-may-2026","specId":"spec.oews-healthcare-support-90th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Healthcare support gives Thesis a low-wage, low-substitution wage target where staffing scarcity and minimum-wage pressure can matter more than software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"31-0000\", statistic: \"p90\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Healthcare support gives Thesis a low-wage, low-substitution wage target where staffing scarcity and minimum-wage pressure can matter more than software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000031000015\", release: \"May 2025\", datatype: \"Annual 90th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Healthcare support gives Thesis a low-wage, low-substitution wage target where staffing scarcity and minimum-wage pressure can matter more than software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5700, distribution present, forecast step count 1.","evidence":["Healthcare support gives Thesis a low-wage, low-substitution wage target where staffing scarcity and minimum-wage pressure can matter more than software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is strong care demand and low-wage service recruitment pressure. The lower tail reflects provider margin constraints and state-level Medicaid funding pressure."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Healthcare support gives Thesis a low-wage, low-substitution wage target where staffing scarcity and minimum-wage pressure can matter more than software substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool result: { base_p90_wage_2025_usd: 54230, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'high_staffing_pressure_low_automation_substitution' }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 90th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is strong care demand and low-wage service recruitment pressure. The lower tail reflects provider margin constraints and state-level Medicaid funding pressure."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-healthcare-support-90th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-healthcare-support-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.def7ce2aa1e80264","runId":"run.oews-healthcare-support-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.def7ce2aa1e80264","predictionId":"oews-healthcare-support-90th-percentile-wage-may-2026","specId":"spec.oews-healthcare-support-90th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $54,230."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_31_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_31_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 54230, 80% interval [53730, 54730]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 54230, 80% interval [53730, 54730]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-healthcare-support-90th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-protective-service-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.bf6f849327b9d3ca","runId":"run.oews-protective-service-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.bf6f849327b9d3ca","predictionId":"oews-protective-service-10th-percentile-wage-may-2026","specId":"spec.oews-protective-service-10th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Protective service wages add a public-safety and security benchmark where staffing, public budgets, and physical presence requirements matter. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"33-0000\", statistic: \"p10\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Protective service wages add a public-safety and security benchmark where staffing, public budgets, and physical presence requirements matter. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000033000011\", release: \"May 2025\", datatype: \"Annual 10th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Protective service wages add a public-safety and security benchmark where staffing, public budgets, and physical presence requirements matter. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3500, distribution present, forecast step count 1.","evidence":["Protective service wages add a public-safety and security benchmark where staffing, public budgets, and physical presence requirements matter. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in public safety and private security roles. The lower tail covers tight state and local budgets and weaker private security demand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_p10_wage_2025_usd: 32850, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'public_safety_staffing_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in public safety and private security roles. The lower tail covers tight state and local budgets and weaker private security demand."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 10th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in public safety and private security roles. The lower tail covers tight state and local budgets and weaker private security demand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-protective-service-10th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-protective-service-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.35dfa95ca40c8298","runId":"run.oews-protective-service-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.35dfa95ca40c8298","predictionId":"oews-protective-service-10th-percentile-wage-may-2026","specId":"spec.oews-protective-service-10th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $32,850."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_33_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_33_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 32850, 80% interval [32350, 33350]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 32850, 80% interval [32350, 33350]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-protective-service-10th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-protective-service-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.23a2a315c7f818ea","runId":"run.oews-protective-service-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.23a2a315c7f818ea","predictionId":"oews-protective-service-25th-percentile-wage-may-2026","specId":"spec.oews-protective-service-25th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Protective service wages add a public-safety and security benchmark where staffing, public budgets, and physical presence requirements matter. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"33-0000\", statistic: \"p25\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Protective service wages add a public-safety and security benchmark where staffing, public budgets, and physical presence requirements matter. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000033000012\", release: \"May 2025\", datatype: \"Annual 25th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Protective service wages add a public-safety and security benchmark where staffing, public budgets, and physical presence requirements matter. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4000, distribution present, forecast step count 1.","evidence":["Protective service wages add a public-safety and security benchmark where staffing, public budgets, and physical presence requirements matter. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in public safety and private security roles. The lower tail covers tight state and local budgets and weaker private security demand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_p25_wage_2025_usd: 37350, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'public_safety_staffing_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in public safety and private security roles. The lower tail covers tight state and local budgets and weaker private security demand."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 25th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in public safety and private security roles. The lower tail covers tight state and local budgets and weaker private security demand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-protective-service-25th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-protective-service-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.a221510e34362a3c","runId":"run.oews-protective-service-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.a221510e34362a3c","predictionId":"oews-protective-service-25th-percentile-wage-may-2026","specId":"spec.oews-protective-service-25th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $37,350."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_33_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_33_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 37350, 80% interval [36850, 37850]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 37350, 80% interval [36850, 37850]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-protective-service-25th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-protective-service-median-wage-may-2026.2026-06-21T13-35-00-04-00.86a1d7e4df2a1d34","runId":"run.oews-protective-service-median-wage-may-2026.2026-06-21T13-35-00-04-00.86a1d7e4df2a1d34","predictionId":"oews-protective-service-median-wage-may-2026","specId":"spec.oews-protective-service-median-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Protective service wages add a public-safety and security benchmark where staffing, public budgets, and physical presence requirements matter. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000033000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Protective service wages add a public-safety and security benchmark where staffing, public budgets, and physical presence requirements matter. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000033000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Protective service wages add a public-safety and security benchmark where staffing, public budgets, and physical presence requirements matter. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5300, distribution present, forecast step count 1.","evidence":["Protective service wages add a public-safety and security benchmark where staffing, public budgets, and physical presence requirements matter. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in public safety and private security roles. The lower tail covers tight state and local budgets and weaker private security demand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_median_wage_2025_usd: 50080, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'public_safety_staffing_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in public safety and private security roles. The lower tail covers tight state and local budgets and weaker private security demand."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual median wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in public safety and private security roles. The lower tail covers tight state and local budgets and weaker private security demand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-protective-service-median-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-protective-service-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.4bb59b914d6c0ecf","runId":"run.oews-protective-service-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.4bb59b914d6c0ecf","predictionId":"oews-protective-service-median-wage-may-2026","specId":"spec.oews-protective-service-median-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_33_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_33_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_33_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 50080, 80% interval [49580, 50580]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 50080, 80% interval [49580, 50580]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-protective-service-median-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-protective-service-mean-wage-may-2026.2026-06-21T13-35-00-04-00.b1ae8dcbd1cd261c","runId":"run.oews-protective-service-mean-wage-may-2026.2026-06-21T13-35-00-04-00.b1ae8dcbd1cd261c","predictionId":"oews-protective-service-mean-wage-may-2026","specId":"spec.oews-protective-service-mean-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Protective service wages add a public-safety and security benchmark where staffing, public budgets, and physical presence requirements matter. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"33-0000\", statistic: \"mean\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Protective service wages add a public-safety and security benchmark where staffing, public budgets, and physical presence requirements matter. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000033000004\", release: \"May 2025\", datatype: \"Annual mean wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Protective service wages add a public-safety and security benchmark where staffing, public budgets, and physical presence requirements matter. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6400, distribution present, forecast step count 1.","evidence":["Protective service wages add a public-safety and security benchmark where staffing, public budgets, and physical presence requirements matter. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in public safety and private security roles. The lower tail covers tight state and local budgets and weaker private security demand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_mean_wage_2025_usd: 60720, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'public_safety_staffing_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in public safety and private security roles. The lower tail covers tight state and local budgets and weaker private security demand."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual mean wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in public safety and private security roles. The lower tail covers tight state and local budgets and weaker private security demand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-protective-service-mean-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-protective-service-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.0472a7f231f60962","runId":"run.oews-protective-service-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.0472a7f231f60962","predictionId":"oews-protective-service-mean-wage-may-2026","specId":"spec.oews-protective-service-mean-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $60,720."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_33_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_33_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 60720, 80% interval [60220, 61220]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 60720, 80% interval [60220, 61220]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-protective-service-mean-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-protective-service-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.932c80f1f2604ec5","runId":"run.oews-protective-service-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.932c80f1f2604ec5","predictionId":"oews-protective-service-75th-percentile-wage-may-2026","specId":"spec.oews-protective-service-75th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Protective service wages add a public-safety and security benchmark where staffing, public budgets, and physical presence requirements matter. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"33-0000\", statistic: \"p75\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Protective service wages add a public-safety and security benchmark where staffing, public budgets, and physical presence requirements matter. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000033000014\", release: \"May 2025\", datatype: \"Annual 75th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Protective service wages add a public-safety and security benchmark where staffing, public budgets, and physical presence requirements matter. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 8000, distribution present, forecast step count 1.","evidence":["Protective service wages add a public-safety and security benchmark where staffing, public budgets, and physical presence requirements matter. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in public safety and private security roles. The lower tail covers tight state and local budgets and weaker private security demand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_p75_wage_2025_usd: 75990, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'public_safety_staffing_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in public safety and private security roles. The lower tail covers tight state and local budgets and weaker private security demand."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 75th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in public safety and private security roles. The lower tail covers tight state and local budgets and weaker private security demand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-protective-service-75th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-protective-service-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.5f50ce344df0e2a3","runId":"run.oews-protective-service-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.5f50ce344df0e2a3","predictionId":"oews-protective-service-75th-percentile-wage-may-2026","specId":"spec.oews-protective-service-75th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $75,990."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_33_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_33_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 75990, 80% interval [75490, 76490]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 75990, 80% interval [75490, 76490]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-protective-service-75th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-protective-service-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.70b7118682ace102","runId":"run.oews-protective-service-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.70b7118682ace102","predictionId":"oews-protective-service-90th-percentile-wage-may-2026","specId":"spec.oews-protective-service-90th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Protective service wages add a public-safety and security benchmark where staffing, public budgets, and physical presence requirements matter. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"33-0000\", statistic: \"p90\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Protective service wages add a public-safety and security benchmark where staffing, public budgets, and physical presence requirements matter. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000033000015\", release: \"May 2025\", datatype: \"Annual 90th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Protective service wages add a public-safety and security benchmark where staffing, public budgets, and physical presence requirements matter. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 10900, distribution present, forecast step count 1.","evidence":["Protective service wages add a public-safety and security benchmark where staffing, public budgets, and physical presence requirements matter. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in public safety and private security roles. The lower tail covers tight state and local budgets and weaker private security demand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_p90_wage_2025_usd: 102470, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'public_safety_staffing_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in public safety and private security roles. The lower tail covers tight state and local budgets and weaker private security demand."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 90th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued staffing pressure in public safety and private security roles. The lower tail covers tight state and local budgets and weaker private security demand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-protective-service-90th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-protective-service-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.3b8482dde8038285","runId":"run.oews-protective-service-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.3b8482dde8038285","predictionId":"oews-protective-service-90th-percentile-wage-may-2026","specId":"spec.oews-protective-service-90th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $102,470."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_33_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_33_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 102470, 80% interval [101970, 102970]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 102470, 80% interval [101970, 102970]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-protective-service-90th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-food-prep-serving-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.6937cb378583320d","runId":"run.oews-food-prep-serving-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.6937cb378583320d","predictionId":"oews-food-prep-serving-10th-percentile-wage-may-2026","specId":"spec.oews-food-prep-serving-10th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Food-service wages are a low-wage service benchmark for wage-floor pressure, consumer demand, and partial automation in ordering and kitchen workflows. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"35-0000\", statistic: \"p10\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Food-service wages are a low-wage service benchmark for wage-floor pressure, consumer demand, and partial automation in ordering and kitchen workflows. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000035000011\", release: \"May 2025\", datatype: \"Annual 10th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Food-service wages are a low-wage service benchmark for wage-floor pressure, consumer demand, and partial automation in ordering and kitchen workflows. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2500, distribution present, forecast step count 1.","evidence":["Food-service wages are a low-wage service benchmark for wage-floor pressure, consumer demand, and partial automation in ordering and kitchen workflows. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in restaurants and other consumer services. The lower tail covers weaker restaurant traffic and more aggressive labor-saving service technology."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Food-service wages are a low-wage service benchmark for wage-floor pressure, consumer demand, and partial automation in ordering and kitchen workflows. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in restaurants and other consumer services. The lower tail covers weaker restaurant traffic and more aggressive labor-saving service technology."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 10th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in restaurants and other consumer services. The lower tail covers weaker restaurant traffic and more aggressive labor-saving service technology."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-food-prep-serving-10th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-food-prep-serving-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.9bafafb0cd8546dd","runId":"run.oews-food-prep-serving-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.9bafafb0cd8546dd","predictionId":"oews-food-prep-serving-10th-percentile-wage-may-2026","specId":"spec.oews-food-prep-serving-10th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $23,120."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_35_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_35_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 23120, 80% interval [22620, 23620]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 23120, 80% interval [22620, 23620]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-food-prep-serving-10th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-food-prep-serving-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.05447c5597e18d6e","runId":"run.oews-food-prep-serving-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.05447c5597e18d6e","predictionId":"oews-food-prep-serving-25th-percentile-wage-may-2026","specId":"spec.oews-food-prep-serving-25th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Food-service wages are a low-wage service benchmark for wage-floor pressure, consumer demand, and partial automation in ordering and kitchen workflows. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"35-0000\", statistic: \"p25\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Food-service wages are a low-wage service benchmark for wage-floor pressure, consumer demand, and partial automation in ordering and kitchen workflows. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000035000012\", release: \"May 2025\", datatype: \"Annual 25th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Food-service wages are a low-wage service benchmark for wage-floor pressure, consumer demand, and partial automation in ordering and kitchen workflows. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3000, distribution present, forecast step count 1.","evidence":["Food-service wages are a low-wage service benchmark for wage-floor pressure, consumer demand, and partial automation in ordering and kitchen workflows. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in restaurants and other consumer services. The lower tail covers weaker restaurant traffic and more aggressive labor-saving service technology."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Food-service wages are a low-wage service benchmark for wage-floor pressure, consumer demand, and partial automation in ordering and kitchen workflows. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in restaurants and other consumer services. The lower tail covers weaker restaurant traffic and more aggressive labor-saving service technology."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 25th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in restaurants and other consumer services. The lower tail covers weaker restaurant traffic and more aggressive labor-saving service technology."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-food-prep-serving-25th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-food-prep-serving-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.b7ea97d90cf5fb7e","runId":"run.oews-food-prep-serving-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.b7ea97d90cf5fb7e","predictionId":"oews-food-prep-serving-25th-percentile-wage-may-2026","specId":"spec.oews-food-prep-serving-25th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $28,760."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_35_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_35_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 28760, 80% interval [28260, 29260]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 28760, 80% interval [28260, 29260]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-food-prep-serving-25th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-food-prep-serving-median-wage-may-2026.2026-06-21T13-35-00-04-00.2688fe55f544eb31","runId":"run.oews-food-prep-serving-median-wage-may-2026.2026-06-21T13-35-00-04-00.2688fe55f544eb31","predictionId":"oews-food-prep-serving-median-wage-may-2026","specId":"spec.oews-food-prep-serving-median-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Food-service wages are a low-wage service benchmark for wage-floor pressure, consumer demand, and partial automation in ordering and kitchen workflows. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000035000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Food-service wages are a low-wage service benchmark for wage-floor pressure, consumer demand, and partial automation in ordering and kitchen workflows. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000035000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Food-service wages are a low-wage service benchmark for wage-floor pressure, consumer demand, and partial automation in ordering and kitchen workflows. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3800, distribution present, forecast step count 1.","evidence":["Food-service wages are a low-wage service benchmark for wage-floor pressure, consumer demand, and partial automation in ordering and kitchen workflows. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in restaurants and other consumer services. The lower tail covers weaker restaurant traffic and more aggressive labor-saving service technology."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Food-service wages are a low-wage service benchmark for wage-floor pressure, consumer demand, and partial automation in ordering and kitchen workflows. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in restaurants and other consumer services. The lower tail covers weaker restaurant traffic and more aggressive labor-saving service technology."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual median wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in restaurants and other consumer services. The lower tail covers weaker restaurant traffic and more aggressive labor-saving service technology."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-food-prep-serving-median-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-food-prep-serving-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.76f7792031eccd79","runId":"run.oews-food-prep-serving-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.76f7792031eccd79","predictionId":"oews-food-prep-serving-median-wage-may-2026","specId":"spec.oews-food-prep-serving-median-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_35_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_35_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_35_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 35050, 80% interval [34550, 35550]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 35050, 80% interval [34550, 35550]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-food-prep-serving-median-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-food-prep-serving-mean-wage-may-2026.2026-06-21T13-35-00-04-00.a7b3745ab8b0c180","runId":"run.oews-food-prep-serving-mean-wage-may-2026.2026-06-21T13-35-00-04-00.a7b3745ab8b0c180","predictionId":"oews-food-prep-serving-mean-wage-may-2026","specId":"spec.oews-food-prep-serving-mean-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Food-service wages are a low-wage service benchmark for wage-floor pressure, consumer demand, and partial automation in ordering and kitchen workflows. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"35-0000\", statistic: \"mean\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Food-service wages are a low-wage service benchmark for wage-floor pressure, consumer demand, and partial automation in ordering and kitchen workflows. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000035000004\", release: \"May 2025\", datatype: \"Annual mean wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Food-service wages are a low-wage service benchmark for wage-floor pressure, consumer demand, and partial automation in ordering and kitchen workflows. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4000, distribution present, forecast step count 1.","evidence":["Food-service wages are a low-wage service benchmark for wage-floor pressure, consumer demand, and partial automation in ordering and kitchen workflows. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in restaurants and other consumer services. The lower tail covers weaker restaurant traffic and more aggressive labor-saving service technology."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Food-service wages are a low-wage service benchmark for wage-floor pressure, consumer demand, and partial automation in ordering and kitchen workflows. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in restaurants and other consumer services. The lower tail covers weaker restaurant traffic and more aggressive labor-saving service technology."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual mean wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in restaurants and other consumer services. The lower tail covers weaker restaurant traffic and more aggressive labor-saving service technology."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-food-prep-serving-mean-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-food-prep-serving-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.9758862ad6f011fc","runId":"run.oews-food-prep-serving-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.9758862ad6f011fc","predictionId":"oews-food-prep-serving-mean-wage-may-2026","specId":"spec.oews-food-prep-serving-mean-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $37,150."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_35_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_35_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 37150, 80% interval [36650, 37650]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 37150, 80% interval [36650, 37650]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-food-prep-serving-mean-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-food-prep-serving-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.11135d7211c0930b","runId":"run.oews-food-prep-serving-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.11135d7211c0930b","predictionId":"oews-food-prep-serving-75th-percentile-wage-may-2026","specId":"spec.oews-food-prep-serving-75th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Food-service wages are a low-wage service benchmark for wage-floor pressure, consumer demand, and partial automation in ordering and kitchen workflows. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"35-0000\", statistic: \"p75\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Food-service wages are a low-wage service benchmark for wage-floor pressure, consumer demand, and partial automation in ordering and kitchen workflows. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000035000014\", release: \"May 2025\", datatype: \"Annual 75th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Food-service wages are a low-wage service benchmark for wage-floor pressure, consumer demand, and partial automation in ordering and kitchen workflows. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4500, distribution present, forecast step count 1.","evidence":["Food-service wages are a low-wage service benchmark for wage-floor pressure, consumer demand, and partial automation in ordering and kitchen workflows. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in restaurants and other consumer services. The lower tail covers weaker restaurant traffic and more aggressive labor-saving service technology."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Food-service wages are a low-wage service benchmark for wage-floor pressure, consumer demand, and partial automation in ordering and kitchen workflows. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in restaurants and other consumer services. The lower tail covers weaker restaurant traffic and more aggressive labor-saving service technology."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 75th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in restaurants and other consumer services. The lower tail covers weaker restaurant traffic and more aggressive labor-saving service technology."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-food-prep-serving-75th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-food-prep-serving-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.f4e92c22232db2a5","runId":"run.oews-food-prep-serving-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.f4e92c22232db2a5","predictionId":"oews-food-prep-serving-75th-percentile-wage-may-2026","specId":"spec.oews-food-prep-serving-75th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $41,860."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_35_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_35_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 41860, 80% interval [41360, 42360]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 41860, 80% interval [41360, 42360]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-food-prep-serving-75th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-food-prep-serving-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.1ec2c456865c9553","runId":"run.oews-food-prep-serving-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.1ec2c456865c9553","predictionId":"oews-food-prep-serving-90th-percentile-wage-may-2026","specId":"spec.oews-food-prep-serving-90th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Food-service wages are a low-wage service benchmark for wage-floor pressure, consumer demand, and partial automation in ordering and kitchen workflows. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"35-0000\", statistic: \"p90\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Food-service wages are a low-wage service benchmark for wage-floor pressure, consumer demand, and partial automation in ordering and kitchen workflows. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000035000015\", release: \"May 2025\", datatype: \"Annual 90th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Food-service wages are a low-wage service benchmark for wage-floor pressure, consumer demand, and partial automation in ordering and kitchen workflows. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5400, distribution present, forecast step count 1.","evidence":["Food-service wages are a low-wage service benchmark for wage-floor pressure, consumer demand, and partial automation in ordering and kitchen workflows. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in restaurants and other consumer services. The lower tail covers weaker restaurant traffic and more aggressive labor-saving service technology."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Food-service wages are a low-wage service benchmark for wage-floor pressure, consumer demand, and partial automation in ordering and kitchen workflows. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in restaurants and other consumer services. The lower tail covers weaker restaurant traffic and more aggressive labor-saving service technology."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 90th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in restaurants and other consumer services. The lower tail covers weaker restaurant traffic and more aggressive labor-saving service technology."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-food-prep-serving-90th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-food-prep-serving-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.f5c0ffe54ab54936","runId":"run.oews-food-prep-serving-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.f5c0ffe54ab54936","predictionId":"oews-food-prep-serving-90th-percentile-wage-may-2026","specId":"spec.oews-food-prep-serving-90th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $51,340."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_35_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_35_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 51340, 80% interval [50840, 51840]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 51340, 80% interval [50840, 51840]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-food-prep-serving-90th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-building-grounds-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.d2b96bfa7f7bfd86","runId":"run.oews-building-grounds-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.d2b96bfa7f7bfd86","predictionId":"oews-building-grounds-10th-percentile-wage-may-2026","specId":"spec.oews-building-grounds-10th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Building and grounds wages track local service labor pressure in cleaning, maintenance, and grounds work where tasks remain largely physical. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"37-0000\", statistic: \"p10\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Building and grounds wages track local service labor pressure in cleaning, maintenance, and grounds work where tasks remain largely physical. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000037000011\", release: \"May 2025\", datatype: \"Annual 10th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Building and grounds wages track local service labor pressure in cleaning, maintenance, and grounds work where tasks remain largely physical. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3100, distribution present, forecast step count 1.","evidence":["Building and grounds wages track local service labor pressure in cleaning, maintenance, and grounds work where tasks remain largely physical. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is low-wage service labor pressure with limited near-term automation substitution. The lower tail covers weaker commercial real estate occupancy and facilities demand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Building and grounds wages track local service labor pressure in cleaning, maintenance, and grounds work where tasks remain largely physical. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool result: { base_p10_wage_2025_usd: 29010, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'physical_service_labor_pressure' }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 10th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is low-wage service labor pressure with limited near-term automation substitution. The lower tail covers weaker commercial real estate occupancy and facilities demand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-building-grounds-10th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-building-grounds-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.491c4ca2a124edc2","runId":"run.oews-building-grounds-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.491c4ca2a124edc2","predictionId":"oews-building-grounds-10th-percentile-wage-may-2026","specId":"spec.oews-building-grounds-10th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $29,010."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_37_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_37_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 29010, 80% interval [28510, 29510]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 29010, 80% interval [28510, 29510]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-building-grounds-10th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-building-grounds-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.22944985d468dbba","runId":"run.oews-building-grounds-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.22944985d468dbba","predictionId":"oews-building-grounds-25th-percentile-wage-may-2026","specId":"spec.oews-building-grounds-25th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Building and grounds wages track local service labor pressure in cleaning, maintenance, and grounds work where tasks remain largely physical. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"37-0000\", statistic: \"p25\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Building and grounds wages track local service labor pressure in cleaning, maintenance, and grounds work where tasks remain largely physical. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000037000012\", release: \"May 2025\", datatype: \"Annual 25th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Building and grounds wages track local service labor pressure in cleaning, maintenance, and grounds work where tasks remain largely physical. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3600, distribution present, forecast step count 1.","evidence":["Building and grounds wages track local service labor pressure in cleaning, maintenance, and grounds work where tasks remain largely physical. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is low-wage service labor pressure with limited near-term automation substitution. The lower tail covers weaker commercial real estate occupancy and facilities demand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Building and grounds wages track local service labor pressure in cleaning, maintenance, and grounds work where tasks remain largely physical. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool result: { base_p25_wage_2025_usd: 33930, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'physical_service_labor_pressure' }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 25th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is low-wage service labor pressure with limited near-term automation substitution. The lower tail covers weaker commercial real estate occupancy and facilities demand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-building-grounds-25th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-building-grounds-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.c0322bcd2fba3384","runId":"run.oews-building-grounds-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.c0322bcd2fba3384","predictionId":"oews-building-grounds-25th-percentile-wage-may-2026","specId":"spec.oews-building-grounds-25th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $33,930."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_37_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_37_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 33930, 80% interval [33430, 34430]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 33930, 80% interval [33430, 34430]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-building-grounds-25th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-building-grounds-median-wage-may-2026.2026-06-21T13-35-00-04-00.0e6f1cae63809ed0","runId":"run.oews-building-grounds-median-wage-may-2026.2026-06-21T13-35-00-04-00.0e6f1cae63809ed0","predictionId":"oews-building-grounds-median-wage-may-2026","specId":"spec.oews-building-grounds-median-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Building and grounds wages track local service labor pressure in cleaning, maintenance, and grounds work where tasks remain largely physical. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000037000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Building and grounds wages track local service labor pressure in cleaning, maintenance, and grounds work where tasks remain largely physical. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000037000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Building and grounds wages track local service labor pressure in cleaning, maintenance, and grounds work where tasks remain largely physical. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4000, distribution present, forecast step count 1.","evidence":["Building and grounds wages track local service labor pressure in cleaning, maintenance, and grounds work where tasks remain largely physical. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is low-wage service labor pressure with limited near-term automation substitution. The lower tail covers weaker commercial real estate occupancy and facilities demand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Building and grounds wages track local service labor pressure in cleaning, maintenance, and grounds work where tasks remain largely physical. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool result: { base_median_wage_2025_usd: 37680, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'physical_service_labor_pressure' }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual median wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is low-wage service labor pressure with limited near-term automation substitution. The lower tail covers weaker commercial real estate occupancy and facilities demand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-building-grounds-median-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-building-grounds-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.ec7a63f39eac10fd","runId":"run.oews-building-grounds-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.ec7a63f39eac10fd","predictionId":"oews-building-grounds-median-wage-may-2026","specId":"spec.oews-building-grounds-median-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_37_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_37_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_37_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 37680, 80% interval [37180, 38180]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 37680, 80% interval [37180, 38180]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-building-grounds-median-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-building-grounds-mean-wage-may-2026.2026-06-21T13-35-00-04-00.348c5459a38170cb","runId":"run.oews-building-grounds-mean-wage-may-2026.2026-06-21T13-35-00-04-00.348c5459a38170cb","predictionId":"oews-building-grounds-mean-wage-may-2026","specId":"spec.oews-building-grounds-mean-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Building and grounds wages track local service labor pressure in cleaning, maintenance, and grounds work where tasks remain largely physical. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"37-0000\", statistic: \"mean\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Building and grounds wages track local service labor pressure in cleaning, maintenance, and grounds work where tasks remain largely physical. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000037000004\", release: \"May 2025\", datatype: \"Annual mean wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Building and grounds wages track local service labor pressure in cleaning, maintenance, and grounds work where tasks remain largely physical. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4300, distribution present, forecast step count 1.","evidence":["Building and grounds wages track local service labor pressure in cleaning, maintenance, and grounds work where tasks remain largely physical. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is low-wage service labor pressure with limited near-term automation substitution. The lower tail covers weaker commercial real estate occupancy and facilities demand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Building and grounds wages track local service labor pressure in cleaning, maintenance, and grounds work where tasks remain largely physical. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool result: { base_mean_wage_2025_usd: 40880, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'physical_service_labor_pressure' }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual mean wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is low-wage service labor pressure with limited near-term automation substitution. The lower tail covers weaker commercial real estate occupancy and facilities demand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-building-grounds-mean-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-building-grounds-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.f814f79aec5f3452","runId":"run.oews-building-grounds-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.f814f79aec5f3452","predictionId":"oews-building-grounds-mean-wage-may-2026","specId":"spec.oews-building-grounds-mean-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $40,880."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_37_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_37_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 40880, 80% interval [40380, 41380]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 40880, 80% interval [40380, 41380]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-building-grounds-mean-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-building-grounds-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.0b4e891b3cf80efc","runId":"run.oews-building-grounds-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.0b4e891b3cf80efc","predictionId":"oews-building-grounds-75th-percentile-wage-may-2026","specId":"spec.oews-building-grounds-75th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Building and grounds wages track local service labor pressure in cleaning, maintenance, and grounds work where tasks remain largely physical. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"37-0000\", statistic: \"p75\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Building and grounds wages track local service labor pressure in cleaning, maintenance, and grounds work where tasks remain largely physical. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000037000014\", release: \"May 2025\", datatype: \"Annual 75th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Building and grounds wages track local service labor pressure in cleaning, maintenance, and grounds work where tasks remain largely physical. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4900, distribution present, forecast step count 1.","evidence":["Building and grounds wages track local service labor pressure in cleaning, maintenance, and grounds work where tasks remain largely physical. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is low-wage service labor pressure with limited near-term automation substitution. The lower tail covers weaker commercial real estate occupancy and facilities demand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Building and grounds wages track local service labor pressure in cleaning, maintenance, and grounds work where tasks remain largely physical. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool result: { base_p75_wage_2025_usd: 46170, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'physical_service_labor_pressure' }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 75th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is low-wage service labor pressure with limited near-term automation substitution. The lower tail covers weaker commercial real estate occupancy and facilities demand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-building-grounds-75th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-building-grounds-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.ad97a701cd736e5b","runId":"run.oews-building-grounds-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.ad97a701cd736e5b","predictionId":"oews-building-grounds-75th-percentile-wage-may-2026","specId":"spec.oews-building-grounds-75th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $46,170."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_37_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_37_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 46170, 80% interval [45670, 46670]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 46170, 80% interval [45670, 46670]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-building-grounds-75th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-building-grounds-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.03bbc639514cc359","runId":"run.oews-building-grounds-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.03bbc639514cc359","predictionId":"oews-building-grounds-90th-percentile-wage-may-2026","specId":"spec.oews-building-grounds-90th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Building and grounds wages track local service labor pressure in cleaning, maintenance, and grounds work where tasks remain largely physical. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"37-0000\", statistic: \"p90\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Building and grounds wages track local service labor pressure in cleaning, maintenance, and grounds work where tasks remain largely physical. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000037000015\", release: \"May 2025\", datatype: \"Annual 90th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Building and grounds wages track local service labor pressure in cleaning, maintenance, and grounds work where tasks remain largely physical. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6100, distribution present, forecast step count 1.","evidence":["Building and grounds wages track local service labor pressure in cleaning, maintenance, and grounds work where tasks remain largely physical. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is low-wage service labor pressure with limited near-term automation substitution. The lower tail covers weaker commercial real estate occupancy and facilities demand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Building and grounds wages track local service labor pressure in cleaning, maintenance, and grounds work where tasks remain largely physical. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool result: { base_p90_wage_2025_usd: 57420, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'physical_service_labor_pressure' }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 90th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is low-wage service labor pressure with limited near-term automation substitution. The lower tail covers weaker commercial real estate occupancy and facilities demand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-building-grounds-90th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-building-grounds-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.d7b63e2929a472de","runId":"run.oews-building-grounds-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.d7b63e2929a472de","predictionId":"oews-building-grounds-90th-percentile-wage-may-2026","specId":"spec.oews-building-grounds-90th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $57,420."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_37_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_37_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 57420, 80% interval [56920, 57920]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 57420, 80% interval [56920, 57920]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-building-grounds-90th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-personal-care-service-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.cdf91c51c96413af","runId":"run.oews-personal-care-service-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.cdf91c51c96413af","predictionId":"oews-personal-care-service-10th-percentile-wage-may-2026","specId":"spec.oews-personal-care-service-10th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Personal care wages are a human-service benchmark where in-person work, demographics, and low-wage labor supply are central. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"39-0000\", statistic: \"p10\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Personal care wages are a human-service benchmark where in-person work, demographics, and low-wage labor supply are central. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000039000011\", release: \"May 2025\", datatype: \"Annual 10th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Personal care wages are a human-service benchmark where in-person work, demographics, and low-wage labor supply are central. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2800, distribution present, forecast step count 1.","evidence":["Personal care wages are a human-service benchmark where in-person work, demographics, and low-wage labor supply are central. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in in-person personal and care services. The lower tail covers weaker discretionary personal-service spending."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_p10_wage_2025_usd: 26430, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'in_person_service_wage_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in in-person personal and care services. The lower tail covers weaker discretionary personal-service spending."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 10th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in in-person personal and care services. The lower tail covers weaker discretionary personal-service spending."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-personal-care-service-10th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-personal-care-service-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.6c711591ad903e2c","runId":"run.oews-personal-care-service-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.6c711591ad903e2c","predictionId":"oews-personal-care-service-10th-percentile-wage-may-2026","specId":"spec.oews-personal-care-service-10th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $26,430."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_39_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_39_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 26430, 80% interval [25930, 26930]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 26430, 80% interval [25930, 26930]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-personal-care-service-10th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-personal-care-service-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.ccb34c5fc596034e","runId":"run.oews-personal-care-service-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.ccb34c5fc596034e","predictionId":"oews-personal-care-service-25th-percentile-wage-may-2026","specId":"spec.oews-personal-care-service-25th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Personal care wages are a human-service benchmark where in-person work, demographics, and low-wage labor supply are central. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"39-0000\", statistic: \"p25\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Personal care wages are a human-service benchmark where in-person work, demographics, and low-wage labor supply are central. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000039000012\", release: \"May 2025\", datatype: \"Annual 25th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Personal care wages are a human-service benchmark where in-person work, demographics, and low-wage labor supply are central. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3300, distribution present, forecast step count 1.","evidence":["Personal care wages are a human-service benchmark where in-person work, demographics, and low-wage labor supply are central. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in in-person personal and care services. The lower tail covers weaker discretionary personal-service spending."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_p25_wage_2025_usd: 30820, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'in_person_service_wage_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in in-person personal and care services. The lower tail covers weaker discretionary personal-service spending."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 25th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in in-person personal and care services. The lower tail covers weaker discretionary personal-service spending."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-personal-care-service-25th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-personal-care-service-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.a35c361c5c4d669d","runId":"run.oews-personal-care-service-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.a35c361c5c4d669d","predictionId":"oews-personal-care-service-25th-percentile-wage-may-2026","specId":"spec.oews-personal-care-service-25th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $30,820."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_39_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_39_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 30820, 80% interval [30320, 31320]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 30820, 80% interval [30320, 31320]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-personal-care-service-25th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-personal-care-service-median-wage-may-2026.2026-06-21T13-35-00-04-00.dcbe49d1aa5b009d","runId":"run.oews-personal-care-service-median-wage-may-2026.2026-06-21T13-35-00-04-00.dcbe49d1aa5b009d","predictionId":"oews-personal-care-service-median-wage-may-2026","specId":"spec.oews-personal-care-service-median-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Personal care wages are a human-service benchmark where in-person work, demographics, and low-wage labor supply are central. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000039000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Personal care wages are a human-service benchmark where in-person work, demographics, and low-wage labor supply are central. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000039000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Personal care wages are a human-service benchmark where in-person work, demographics, and low-wage labor supply are central. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3800, distribution present, forecast step count 1.","evidence":["Personal care wages are a human-service benchmark where in-person work, demographics, and low-wage labor supply are central. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in in-person personal and care services. The lower tail covers weaker discretionary personal-service spending."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_median_wage_2025_usd: 36410, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'in_person_service_wage_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in in-person personal and care services. The lower tail covers weaker discretionary personal-service spending."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual median wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in in-person personal and care services. The lower tail covers weaker discretionary personal-service spending."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-personal-care-service-median-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-personal-care-service-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.9c7940398c60f9d4","runId":"run.oews-personal-care-service-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.9c7940398c60f9d4","predictionId":"oews-personal-care-service-median-wage-may-2026","specId":"spec.oews-personal-care-service-median-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_39_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_39_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_39_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 36410, 80% interval [35910, 36910]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 36410, 80% interval [35910, 36910]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-personal-care-service-median-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-personal-care-service-mean-wage-may-2026.2026-06-21T13-35-00-04-00.e7457ec1e9cb6dbf","runId":"run.oews-personal-care-service-mean-wage-may-2026.2026-06-21T13-35-00-04-00.e7457ec1e9cb6dbf","predictionId":"oews-personal-care-service-mean-wage-may-2026","specId":"spec.oews-personal-care-service-mean-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Personal care wages are a human-service benchmark where in-person work, demographics, and low-wage labor supply are central. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"39-0000\", statistic: \"mean\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Personal care wages are a human-service benchmark where in-person work, demographics, and low-wage labor supply are central. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000039000004\", release: \"May 2025\", datatype: \"Annual mean wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Personal care wages are a human-service benchmark where in-person work, demographics, and low-wage labor supply are central. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4300, distribution present, forecast step count 1.","evidence":["Personal care wages are a human-service benchmark where in-person work, demographics, and low-wage labor supply are central. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in in-person personal and care services. The lower tail covers weaker discretionary personal-service spending."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_mean_wage_2025_usd: 41070, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'in_person_service_wage_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in in-person personal and care services. The lower tail covers weaker discretionary personal-service spending."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual mean wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in in-person personal and care services. The lower tail covers weaker discretionary personal-service spending."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-personal-care-service-mean-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-personal-care-service-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.bea26f4de82384e0","runId":"run.oews-personal-care-service-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.bea26f4de82384e0","predictionId":"oews-personal-care-service-mean-wage-may-2026","specId":"spec.oews-personal-care-service-mean-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $41,070."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_39_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_39_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 41070, 80% interval [40570, 41570]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 41070, 80% interval [40570, 41570]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-personal-care-service-mean-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-personal-care-service-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.8bab6d02623cb99c","runId":"run.oews-personal-care-service-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.8bab6d02623cb99c","predictionId":"oews-personal-care-service-75th-percentile-wage-may-2026","specId":"spec.oews-personal-care-service-75th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Personal care wages are a human-service benchmark where in-person work, demographics, and low-wage labor supply are central. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"39-0000\", statistic: \"p75\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Personal care wages are a human-service benchmark where in-person work, demographics, and low-wage labor supply are central. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000039000014\", release: \"May 2025\", datatype: \"Annual 75th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Personal care wages are a human-service benchmark where in-person work, demographics, and low-wage labor supply are central. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4900, distribution present, forecast step count 1.","evidence":["Personal care wages are a human-service benchmark where in-person work, demographics, and low-wage labor supply are central. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in in-person personal and care services. The lower tail covers weaker discretionary personal-service spending."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_p75_wage_2025_usd: 46060, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'in_person_service_wage_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in in-person personal and care services. The lower tail covers weaker discretionary personal-service spending."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 75th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in in-person personal and care services. The lower tail covers weaker discretionary personal-service spending."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-personal-care-service-75th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-personal-care-service-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.6e9826dcd5744c3a","runId":"run.oews-personal-care-service-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.6e9826dcd5744c3a","predictionId":"oews-personal-care-service-75th-percentile-wage-may-2026","specId":"spec.oews-personal-care-service-75th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $46,060."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_39_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_39_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 46060, 80% interval [45560, 46560]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 46060, 80% interval [45560, 46560]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-personal-care-service-75th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-personal-care-service-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.7f4c9da5250e5cf3","runId":"run.oews-personal-care-service-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.7f4c9da5250e5cf3","predictionId":"oews-personal-care-service-90th-percentile-wage-may-2026","specId":"spec.oews-personal-care-service-90th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Personal care wages are a human-service benchmark where in-person work, demographics, and low-wage labor supply are central. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"39-0000\", statistic: \"p90\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Personal care wages are a human-service benchmark where in-person work, demographics, and low-wage labor supply are central. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000039000015\", release: \"May 2025\", datatype: \"Annual 90th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Personal care wages are a human-service benchmark where in-person work, demographics, and low-wage labor supply are central. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6400, distribution present, forecast step count 1.","evidence":["Personal care wages are a human-service benchmark where in-person work, demographics, and low-wage labor supply are central. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in in-person personal and care services. The lower tail covers weaker discretionary personal-service spending."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_p90_wage_2025_usd: 61020, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'in_person_service_wage_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in in-person personal and care services. The lower tail covers weaker discretionary personal-service spending."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 90th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued wage-floor pressure in in-person personal and care services. The lower tail covers weaker discretionary personal-service spending."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-personal-care-service-90th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-personal-care-service-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.66696bafafc3df6d","runId":"run.oews-personal-care-service-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.66696bafafc3df6d","predictionId":"oews-personal-care-service-90th-percentile-wage-may-2026","specId":"spec.oews-personal-care-service-90th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $61,020."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_39_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_39_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 61020, 80% interval [60520, 61520]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 61020, 80% interval [60520, 61520]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-personal-care-service-90th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-sales-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.62b4490539bc3d0b","runId":"run.oews-sales-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.62b4490539bc3d0b","predictionId":"oews-sales-10th-percentile-wage-may-2026","specId":"spec.oews-sales-10th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.59,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Sales wages connect retail, call-center, and business-development task exposure to consumer demand and online substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"41-0000\", statistic: \"p10\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Sales wages connect retail, call-center, and business-development task exposure to consumer demand and online substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000041000011\", release: \"May 2025\", datatype: \"Annual 10th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Sales wages connect retail, call-center, and business-development task exposure to consumer demand and online substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3000, distribution present, forecast step count 1.","evidence":["Sales wages connect retail, call-center, and business-development task exposure to consumer demand and online substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool result: { base_p10_wage_2025_usd: 28080, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'sales_tools_and_retail_mix' }"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is moderate nominal wage growth offset by retail automation and e-commerce pressure. The lower tail covers weaker retail demand and a lower-commission occupational mix."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is moderate nominal wage growth offset by retail automation and e-commerce pressure. The lower tail covers weaker retail demand and a lower-commission occupational mix."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 10th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is moderate nominal wage growth offset by retail automation and e-commerce pressure. The lower tail covers weaker retail demand and a lower-commission occupational mix."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-sales-10th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (3/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-sales-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.a27cba9502af4281","runId":"run.oews-sales-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.a27cba9502af4281","predictionId":"oews-sales-10th-percentile-wage-may-2026","specId":"spec.oews-sales-10th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $28,080."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_41_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_41_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 28080, 80% interval [27580, 28580]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 28080, 80% interval [27580, 28580]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-sales-10th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-sales-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.45daa3b8cb7fad2c","runId":"run.oews-sales-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.45daa3b8cb7fad2c","predictionId":"oews-sales-25th-percentile-wage-may-2026","specId":"spec.oews-sales-25th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.59,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Sales wages connect retail, call-center, and business-development task exposure to consumer demand and online substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"41-0000\", statistic: \"p25\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Sales wages connect retail, call-center, and business-development task exposure to consumer demand and online substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000041000012\", release: \"May 2025\", datatype: \"Annual 25th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Sales wages connect retail, call-center, and business-development task exposure to consumer demand and online substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3400, distribution present, forecast step count 1.","evidence":["Sales wages connect retail, call-center, and business-development task exposure to consumer demand and online substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool result: { base_p25_wage_2025_usd: 32440, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'sales_tools_and_retail_mix' }"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is moderate nominal wage growth offset by retail automation and e-commerce pressure. The lower tail covers weaker retail demand and a lower-commission occupational mix."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is moderate nominal wage growth offset by retail automation and e-commerce pressure. The lower tail covers weaker retail demand and a lower-commission occupational mix."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 25th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is moderate nominal wage growth offset by retail automation and e-commerce pressure. The lower tail covers weaker retail demand and a lower-commission occupational mix."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-sales-25th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (3/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-sales-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.1abf6bdfc5da9e38","runId":"run.oews-sales-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.1abf6bdfc5da9e38","predictionId":"oews-sales-25th-percentile-wage-may-2026","specId":"spec.oews-sales-25th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $32,440."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_41_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_41_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 32440, 80% interval [31940, 32940]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 32440, 80% interval [31940, 32940]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-sales-25th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-sales-median-wage-may-2026.2026-06-21T13-35-00-04-00.47d80d6a223b0fc6","runId":"run.oews-sales-median-wage-may-2026.2026-06-21T13-35-00-04-00.47d80d6a223b0fc6","predictionId":"oews-sales-median-wage-may-2026","specId":"spec.oews-sales-median-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.59,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Sales wages connect retail, call-center, and business-development task exposure to consumer demand and online substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000041000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Sales wages connect retail, call-center, and business-development task exposure to consumer demand and online substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000041000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Sales wages connect retail, call-center, and business-development task exposure to consumer demand and online substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4100, distribution present, forecast step count 1.","evidence":["Sales wages connect retail, call-center, and business-development task exposure to consumer demand and online substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool result: { base_median_wage_2025_usd: 38530, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'sales_tools_and_retail_mix' }"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is moderate nominal wage growth offset by retail automation and e-commerce pressure. The lower tail covers weaker retail demand and a lower-commission occupational mix."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is moderate nominal wage growth offset by retail automation and e-commerce pressure. The lower tail covers weaker retail demand and a lower-commission occupational mix."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual median wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is moderate nominal wage growth offset by retail automation and e-commerce pressure. The lower tail covers weaker retail demand and a lower-commission occupational mix."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-sales-median-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (3/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-sales-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.e0314740428ffc65","runId":"run.oews-sales-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.e0314740428ffc65","predictionId":"oews-sales-median-wage-may-2026","specId":"spec.oews-sales-median-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_41_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_41_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_41_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 38530, 80% interval [38030, 39030]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 38530, 80% interval [38030, 39030]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-sales-median-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-sales-mean-wage-may-2026.2026-06-21T13-35-00-04-00.c8636567b82a689d","runId":"run.oews-sales-mean-wage-may-2026.2026-06-21T13-35-00-04-00.c8636567b82a689d","predictionId":"oews-sales-mean-wage-may-2026","specId":"spec.oews-sales-mean-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.59,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Sales wages connect retail, call-center, and business-development task exposure to consumer demand and online substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"41-0000\", statistic: \"mean\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Sales wages connect retail, call-center, and business-development task exposure to consumer demand and online substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000041000004\", release: \"May 2025\", datatype: \"Annual mean wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Sales wages connect retail, call-center, and business-development task exposure to consumer demand and online substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5800, distribution present, forecast step count 1.","evidence":["Sales wages connect retail, call-center, and business-development task exposure to consumer demand and online substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool result: { base_mean_wage_2025_usd: 54960, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'sales_tools_and_retail_mix' }"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is moderate nominal wage growth offset by retail automation and e-commerce pressure. The lower tail covers weaker retail demand and a lower-commission occupational mix."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is moderate nominal wage growth offset by retail automation and e-commerce pressure. The lower tail covers weaker retail demand and a lower-commission occupational mix."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual mean wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is moderate nominal wage growth offset by retail automation and e-commerce pressure. The lower tail covers weaker retail demand and a lower-commission occupational mix."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-sales-mean-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (3/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-sales-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.278e411128d1ba1f","runId":"run.oews-sales-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.278e411128d1ba1f","predictionId":"oews-sales-mean-wage-may-2026","specId":"spec.oews-sales-mean-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $54,960."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_41_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_41_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 54960, 80% interval [54460, 55460]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 54960, 80% interval [54460, 55460]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-sales-mean-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-sales-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.71d4296dcf4aca26","runId":"run.oews-sales-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.71d4296dcf4aca26","predictionId":"oews-sales-75th-percentile-wage-may-2026","specId":"spec.oews-sales-75th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.59,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Sales wages connect retail, call-center, and business-development task exposure to consumer demand and online substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"41-0000\", statistic: \"p75\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Sales wages connect retail, call-center, and business-development task exposure to consumer demand and online substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000041000014\", release: \"May 2025\", datatype: \"Annual 75th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Sales wages connect retail, call-center, and business-development task exposure to consumer demand and online substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6500, distribution present, forecast step count 1.","evidence":["Sales wages connect retail, call-center, and business-development task exposure to consumer demand and online substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool result: { base_p75_wage_2025_usd: 61100, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'sales_tools_and_retail_mix' }"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is moderate nominal wage growth offset by retail automation and e-commerce pressure. The lower tail covers weaker retail demand and a lower-commission occupational mix."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is moderate nominal wage growth offset by retail automation and e-commerce pressure. The lower tail covers weaker retail demand and a lower-commission occupational mix."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 75th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is moderate nominal wage growth offset by retail automation and e-commerce pressure. The lower tail covers weaker retail demand and a lower-commission occupational mix."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-sales-75th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (3/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-sales-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.2badb6927a40fc43","runId":"run.oews-sales-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.2badb6927a40fc43","predictionId":"oews-sales-75th-percentile-wage-may-2026","specId":"spec.oews-sales-75th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $61,100."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_41_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_41_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 61100, 80% interval [60600, 61600]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 61100, 80% interval [60600, 61600]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-sales-75th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-sales-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.dcbe9db86c3368b9","runId":"run.oews-sales-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.dcbe9db86c3368b9","predictionId":"oews-sales-90th-percentile-wage-may-2026","specId":"spec.oews-sales-90th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.59,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Sales wages connect retail, call-center, and business-development task exposure to consumer demand and online substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"41-0000\", statistic: \"p90\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Sales wages connect retail, call-center, and business-development task exposure to consumer demand and online substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000041000015\", release: \"May 2025\", datatype: \"Annual 90th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Sales wages connect retail, call-center, and business-development task exposure to consumer demand and online substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 10600, distribution present, forecast step count 1.","evidence":["Sales wages connect retail, call-center, and business-development task exposure to consumer demand and online substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool result: { base_p90_wage_2025_usd: 99850, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'sales_tools_and_retail_mix' }"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is moderate nominal wage growth offset by retail automation and e-commerce pressure. The lower tail covers weaker retail demand and a lower-commission occupational mix."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is moderate nominal wage growth offset by retail automation and e-commerce pressure. The lower tail covers weaker retail demand and a lower-commission occupational mix."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 90th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is moderate nominal wage growth offset by retail automation and e-commerce pressure. The lower tail covers weaker retail demand and a lower-commission occupational mix."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-sales-90th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (3/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-sales-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.8948f790510b2a99","runId":"run.oews-sales-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.8948f790510b2a99","predictionId":"oews-sales-90th-percentile-wage-may-2026","specId":"spec.oews-sales-90th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $99,850."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_41_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_41_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 99850, 80% interval [99350, 100350]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 99850, 80% interval [99350, 100350]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-sales-90th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-office-admin-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.92cae9875c7074ec","runId":"run.oews-office-admin-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.92cae9875c7074ec","predictionId":"oews-office-admin-10th-percentile-wage-may-2026","specId":"spec.oews-office-admin-10th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Office and administrative support is the wage counterpart to the clearest clerical automation employment target, so it helps separate headcount decline from composition and wage-pressure effects. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"43-0000\", statistic: \"p10\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Office and administrative support is the wage counterpart to the clearest clerical automation employment target, so it helps separate headcount decline from composition and wage-pressure effects. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000043000011\", release: \"May 2025\", datatype: \"Annual 10th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Office and administrative support is the wage counterpart to the clearest clerical automation employment target, so it helps separate headcount decline from composition and wage-pressure effects. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3500, distribution present, forecast step count 1.","evidence":["Office and administrative support is the wage counterpart to the clearest clerical automation employment target, so it helps separate headcount decline from composition and wage-pressure effects. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is nominal wage growth and composition effects from routine lower-wage roles shrinking first. The lower tail covers weaker service-sector administrative demand and broad clerical substitution."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Office and administrative support is the wage counterpart to the clearest clerical automation employment target, so it helps separate headcount decline from composition and wage-pressure effects. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 10th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is nominal wage growth and composition effects from routine lower-wage roles shrinking first. The lower tail covers weaker service-sector administrative demand and broad clerical substitution."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-office-admin-10th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-office-admin-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.668fe2864e59470d","runId":"run.oews-office-admin-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.668fe2864e59470d","predictionId":"oews-office-admin-10th-percentile-wage-may-2026","specId":"spec.oews-office-admin-10th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $33,530."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_43_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_43_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 33530, 80% interval [33030, 34030]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 33530, 80% interval [33030, 34030]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-office-admin-10th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-office-admin-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.47d80d6a223b0fc6","runId":"run.oews-office-admin-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.47d80d6a223b0fc6","predictionId":"oews-office-admin-25th-percentile-wage-may-2026","specId":"spec.oews-office-admin-25th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Office and administrative support is the wage counterpart to the clearest clerical automation employment target, so it helps separate headcount decline from composition and wage-pressure effects. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"43-0000\", statistic: \"p25\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Office and administrative support is the wage counterpart to the clearest clerical automation employment target, so it helps separate headcount decline from composition and wage-pressure effects. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000043000012\", release: \"May 2025\", datatype: \"Annual 25th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Office and administrative support is the wage counterpart to the clearest clerical automation employment target, so it helps separate headcount decline from composition and wage-pressure effects. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4100, distribution present, forecast step count 1.","evidence":["Office and administrative support is the wage counterpart to the clearest clerical automation employment target, so it helps separate headcount decline from composition and wage-pressure effects. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is nominal wage growth and composition effects from routine lower-wage roles shrinking first. The lower tail covers weaker service-sector administrative demand and broad clerical substitution."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Office and administrative support is the wage counterpart to the clearest clerical automation employment target, so it helps separate headcount decline from composition and wage-pressure effects. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 25th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is nominal wage growth and composition effects from routine lower-wage roles shrinking first. The lower tail covers weaker service-sector administrative demand and broad clerical substitution."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-office-admin-25th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-office-admin-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.af9cc1ce051d2550","runId":"run.oews-office-admin-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.af9cc1ce051d2550","predictionId":"oews-office-admin-25th-percentile-wage-may-2026","specId":"spec.oews-office-admin-25th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $38,540."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_43_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_43_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 38540, 80% interval [38040, 39040]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 38540, 80% interval [38040, 39040]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-office-admin-25th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-office-admin-median-wage-may-2026.2026-06-21T13-35-00-04-00.e7680701dac933d7","runId":"run.oews-office-admin-median-wage-may-2026.2026-06-21T13-35-00-04-00.e7680701dac933d7","predictionId":"oews-office-admin-median-wage-may-2026","specId":"spec.oews-office-admin-median-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Office and administrative support is the wage counterpart to the clearest clerical automation employment target, so it helps separate headcount decline from composition and wage-pressure effects. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000043000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Office and administrative support is the wage counterpart to the clearest clerical automation employment target, so it helps separate headcount decline from composition and wage-pressure effects. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000043000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Office and administrative support is the wage counterpart to the clearest clerical automation employment target, so it helps separate headcount decline from composition and wage-pressure effects. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5100, distribution present, forecast step count 1.","evidence":["Office and administrative support is the wage counterpart to the clearest clerical automation employment target, so it helps separate headcount decline from composition and wage-pressure effects. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is nominal wage growth and composition effects from routine lower-wage roles shrinking first. The lower tail covers weaker service-sector administrative demand and broad clerical substitution."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Office and administrative support is the wage counterpart to the clearest clerical automation employment target, so it helps separate headcount decline from composition and wage-pressure effects. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual median wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is nominal wage growth and composition effects from routine lower-wage roles shrinking first. The lower tail covers weaker service-sector administrative demand and broad clerical substitution."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-office-admin-median-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-office-admin-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.279c62340629f887","runId":"run.oews-office-admin-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.279c62340629f887","predictionId":"oews-office-admin-median-wage-may-2026","specId":"spec.oews-office-admin-median-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_43_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_43_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_43_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 47450, 80% interval [46950, 47950]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 47450, 80% interval [46950, 47950]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-office-admin-median-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-office-admin-mean-wage-may-2026.2026-06-21T13-35-00-04-00.f9f076f846fa40ae","runId":"run.oews-office-admin-mean-wage-may-2026.2026-06-21T13-35-00-04-00.f9f076f846fa40ae","predictionId":"oews-office-admin-mean-wage-may-2026","specId":"spec.oews-office-admin-mean-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Office and administrative support is the wage counterpart to the clearest clerical automation employment target, so it helps separate headcount decline from composition and wage-pressure effects. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"43-0000\", statistic: \"mean\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Office and administrative support is the wage counterpart to the clearest clerical automation employment target, so it helps separate headcount decline from composition and wage-pressure effects. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000043000004\", release: \"May 2025\", datatype: \"Annual mean wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Office and administrative support is the wage counterpart to the clearest clerical automation employment target, so it helps separate headcount decline from composition and wage-pressure effects. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5400, distribution present, forecast step count 1.","evidence":["Office and administrative support is the wage counterpart to the clearest clerical automation employment target, so it helps separate headcount decline from composition and wage-pressure effects. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is nominal wage growth and composition effects from routine lower-wage roles shrinking first. The lower tail covers weaker service-sector administrative demand and broad clerical substitution."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Office and administrative support is the wage counterpart to the clearest clerical automation employment target, so it helps separate headcount decline from composition and wage-pressure effects. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual mean wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is nominal wage growth and composition effects from routine lower-wage roles shrinking first. The lower tail covers weaker service-sector administrative demand and broad clerical substitution."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-office-admin-mean-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-office-admin-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.cf01ad0eaf5ebcd3","runId":"run.oews-office-admin-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.cf01ad0eaf5ebcd3","predictionId":"oews-office-admin-mean-wage-may-2026","specId":"spec.oews-office-admin-mean-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $51,560."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_43_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_43_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 51560, 80% interval [51060, 52060]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 51560, 80% interval [51060, 52060]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-office-admin-mean-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-office-admin-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.a2f6eeb13f564186","runId":"run.oews-office-admin-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.a2f6eeb13f564186","predictionId":"oews-office-admin-75th-percentile-wage-may-2026","specId":"spec.oews-office-admin-75th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Office and administrative support is the wage counterpart to the clearest clerical automation employment target, so it helps separate headcount decline from composition and wage-pressure effects. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"43-0000\", statistic: \"p75\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Office and administrative support is the wage counterpart to the clearest clerical automation employment target, so it helps separate headcount decline from composition and wage-pressure effects. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000043000014\", release: \"May 2025\", datatype: \"Annual 75th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Office and administrative support is the wage counterpart to the clearest clerical automation employment target, so it helps separate headcount decline from composition and wage-pressure effects. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6400, distribution present, forecast step count 1.","evidence":["Office and administrative support is the wage counterpart to the clearest clerical automation employment target, so it helps separate headcount decline from composition and wage-pressure effects. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is nominal wage growth and composition effects from routine lower-wage roles shrinking first. The lower tail covers weaker service-sector administrative demand and broad clerical substitution."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Office and administrative support is the wage counterpart to the clearest clerical automation employment target, so it helps separate headcount decline from composition and wage-pressure effects. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 75th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is nominal wage growth and composition effects from routine lower-wage roles shrinking first. The lower tail covers weaker service-sector administrative demand and broad clerical substitution."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-office-admin-75th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-office-admin-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.5d5fce4bd519ea62","runId":"run.oews-office-admin-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.5d5fce4bd519ea62","predictionId":"oews-office-admin-75th-percentile-wage-may-2026","specId":"spec.oews-office-admin-75th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $60,060."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_43_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_43_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 60060, 80% interval [59560, 60560]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 60060, 80% interval [59560, 60560]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-office-admin-75th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-office-admin-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.87c1c0d160ee4e72","runId":"run.oews-office-admin-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.87c1c0d160ee4e72","predictionId":"oews-office-admin-90th-percentile-wage-may-2026","specId":"spec.oews-office-admin-90th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Office and administrative support is the wage counterpart to the clearest clerical automation employment target, so it helps separate headcount decline from composition and wage-pressure effects. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"43-0000\", statistic: \"p90\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Office and administrative support is the wage counterpart to the clearest clerical automation employment target, so it helps separate headcount decline from composition and wage-pressure effects. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000043000015\", release: \"May 2025\", datatype: \"Annual 90th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Office and administrative support is the wage counterpart to the clearest clerical automation employment target, so it helps separate headcount decline from composition and wage-pressure effects. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 8000, distribution present, forecast step count 1.","evidence":["Office and administrative support is the wage counterpart to the clearest clerical automation employment target, so it helps separate headcount decline from composition and wage-pressure effects. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is nominal wage growth and composition effects from routine lower-wage roles shrinking first. The lower tail covers weaker service-sector administrative demand and broad clerical substitution."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Office and administrative support is the wage counterpart to the clearest clerical automation employment target, so it helps separate headcount decline from composition and wage-pressure effects. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 90th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is nominal wage growth and composition effects from routine lower-wage roles shrinking first. The lower tail covers weaker service-sector administrative demand and broad clerical substitution."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-office-admin-90th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-office-admin-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.635974fd28e63841","runId":"run.oews-office-admin-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.635974fd28e63841","predictionId":"oews-office-admin-90th-percentile-wage-may-2026","specId":"spec.oews-office-admin-90th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $76,170."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_43_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_43_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 76170, 80% interval [75670, 76670]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 76170, 80% interval [75670, 76670]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-office-admin-90th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-farming-fishing-forestry-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.2581cfb6d23d9bd8","runId":"run.oews-farming-fishing-forestry-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.2581cfb6d23d9bd8","predictionId":"oews-farming-fishing-forestry-10th-percentile-wage-may-2026","specId":"spec.oews-farming-fishing-forestry-10th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Farming, fishing, and forestry wages add a goods-producing, outdoor-work benchmark exposed to seasonal labor supply and mechanization. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"45-0000\", statistic: \"p10\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Farming, fishing, and forestry wages add a goods-producing, outdoor-work benchmark exposed to seasonal labor supply and mechanization. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000045000011\", release: \"May 2025\", datatype: \"Annual 10th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Farming, fishing, and forestry wages add a goods-producing, outdoor-work benchmark exposed to seasonal labor supply and mechanization. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3400, distribution present, forecast step count 1.","evidence":["Farming, fishing, and forestry wages add a goods-producing, outdoor-work benchmark exposed to seasonal labor supply and mechanization. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued low-wage labor pressure in seasonal and outdoor work. The lower tail covers weaker commodity demand and more labor-saving mechanization."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_p10_wage_2025_usd: 31760, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'agricultural_labor_supply_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued low-wage labor pressure in seasonal and outdoor work. The lower tail covers weaker commodity demand and more labor-saving mechanization."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 10th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued low-wage labor pressure in seasonal and outdoor work. The lower tail covers weaker commodity demand and more labor-saving mechanization."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-farming-fishing-forestry-10th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-farming-fishing-forestry-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.ae436873924d25fd","runId":"run.oews-farming-fishing-forestry-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.ae436873924d25fd","predictionId":"oews-farming-fishing-forestry-10th-percentile-wage-may-2026","specId":"spec.oews-farming-fishing-forestry-10th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $31,760."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_45_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_45_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 31760, 80% interval [31260, 32260]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 31760, 80% interval [31260, 32260]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-farming-fishing-forestry-10th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-farming-fishing-forestry-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.fcc16c8540275b1c","runId":"run.oews-farming-fishing-forestry-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.fcc16c8540275b1c","predictionId":"oews-farming-fishing-forestry-25th-percentile-wage-may-2026","specId":"spec.oews-farming-fishing-forestry-25th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Farming, fishing, and forestry wages add a goods-producing, outdoor-work benchmark exposed to seasonal labor supply and mechanization. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"45-0000\", statistic: \"p25\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Farming, fishing, and forestry wages add a goods-producing, outdoor-work benchmark exposed to seasonal labor supply and mechanization. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000045000012\", release: \"May 2025\", datatype: \"Annual 25th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Farming, fishing, and forestry wages add a goods-producing, outdoor-work benchmark exposed to seasonal labor supply and mechanization. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3700, distribution present, forecast step count 1.","evidence":["Farming, fishing, and forestry wages add a goods-producing, outdoor-work benchmark exposed to seasonal labor supply and mechanization. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued low-wage labor pressure in seasonal and outdoor work. The lower tail covers weaker commodity demand and more labor-saving mechanization."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_p25_wage_2025_usd: 34540, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'agricultural_labor_supply_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued low-wage labor pressure in seasonal and outdoor work. The lower tail covers weaker commodity demand and more labor-saving mechanization."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 25th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued low-wage labor pressure in seasonal and outdoor work. The lower tail covers weaker commodity demand and more labor-saving mechanization."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-farming-fishing-forestry-25th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-farming-fishing-forestry-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.cef3ed397175a965","runId":"run.oews-farming-fishing-forestry-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.cef3ed397175a965","predictionId":"oews-farming-fishing-forestry-25th-percentile-wage-may-2026","specId":"spec.oews-farming-fishing-forestry-25th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $34,540."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_45_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_45_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 34540, 80% interval [34040, 35040]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 34540, 80% interval [34040, 35040]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-farming-fishing-forestry-25th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-farming-fishing-forestry-median-wage-may-2026.2026-06-21T13-35-00-04-00.14b020a53716c6c9","runId":"run.oews-farming-fishing-forestry-median-wage-may-2026.2026-06-21T13-35-00-04-00.14b020a53716c6c9","predictionId":"oews-farming-fishing-forestry-median-wage-may-2026","specId":"spec.oews-farming-fishing-forestry-median-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Farming, fishing, and forestry wages add a goods-producing, outdoor-work benchmark exposed to seasonal labor supply and mechanization. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000045000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Farming, fishing, and forestry wages add a goods-producing, outdoor-work benchmark exposed to seasonal labor supply and mechanization. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000045000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Farming, fishing, and forestry wages add a goods-producing, outdoor-work benchmark exposed to seasonal labor supply and mechanization. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3900, distribution present, forecast step count 1.","evidence":["Farming, fishing, and forestry wages add a goods-producing, outdoor-work benchmark exposed to seasonal labor supply and mechanization. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued low-wage labor pressure in seasonal and outdoor work. The lower tail covers weaker commodity demand and more labor-saving mechanization."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_median_wage_2025_usd: 36630, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'agricultural_labor_supply_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued low-wage labor pressure in seasonal and outdoor work. The lower tail covers weaker commodity demand and more labor-saving mechanization."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual median wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued low-wage labor pressure in seasonal and outdoor work. The lower tail covers weaker commodity demand and more labor-saving mechanization."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-farming-fishing-forestry-median-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-farming-fishing-forestry-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.09fe3fc8ed44bda5","runId":"run.oews-farming-fishing-forestry-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.09fe3fc8ed44bda5","predictionId":"oews-farming-fishing-forestry-median-wage-may-2026","specId":"spec.oews-farming-fishing-forestry-median-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_45_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_45_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_45_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 36630, 80% interval [36130, 37130]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 36630, 80% interval [36130, 37130]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-farming-fishing-forestry-median-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-farming-fishing-forestry-mean-wage-may-2026.2026-06-21T13-35-00-04-00.024685d9b4163f55","runId":"run.oews-farming-fishing-forestry-mean-wage-may-2026.2026-06-21T13-35-00-04-00.024685d9b4163f55","predictionId":"oews-farming-fishing-forestry-mean-wage-may-2026","specId":"spec.oews-farming-fishing-forestry-mean-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Farming, fishing, and forestry wages add a goods-producing, outdoor-work benchmark exposed to seasonal labor supply and mechanization. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"45-0000\", statistic: \"mean\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Farming, fishing, and forestry wages add a goods-producing, outdoor-work benchmark exposed to seasonal labor supply and mechanization. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000045000004\", release: \"May 2025\", datatype: \"Annual mean wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Farming, fishing, and forestry wages add a goods-producing, outdoor-work benchmark exposed to seasonal labor supply and mechanization. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4400, distribution present, forecast step count 1.","evidence":["Farming, fishing, and forestry wages add a goods-producing, outdoor-work benchmark exposed to seasonal labor supply and mechanization. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued low-wage labor pressure in seasonal and outdoor work. The lower tail covers weaker commodity demand and more labor-saving mechanization."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_mean_wage_2025_usd: 41510, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'agricultural_labor_supply_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued low-wage labor pressure in seasonal and outdoor work. The lower tail covers weaker commodity demand and more labor-saving mechanization."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual mean wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued low-wage labor pressure in seasonal and outdoor work. The lower tail covers weaker commodity demand and more labor-saving mechanization."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-farming-fishing-forestry-mean-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-farming-fishing-forestry-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.d63b4cacdf45da41","runId":"run.oews-farming-fishing-forestry-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.d63b4cacdf45da41","predictionId":"oews-farming-fishing-forestry-mean-wage-may-2026","specId":"spec.oews-farming-fishing-forestry-mean-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $41,510."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_45_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_45_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 41510, 80% interval [41010, 42010]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 41510, 80% interval [41010, 42010]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-farming-fishing-forestry-mean-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-farming-fishing-forestry-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.57b3e65cdbf4ef06","runId":"run.oews-farming-fishing-forestry-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.57b3e65cdbf4ef06","predictionId":"oews-farming-fishing-forestry-75th-percentile-wage-may-2026","specId":"spec.oews-farming-fishing-forestry-75th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Farming, fishing, and forestry wages add a goods-producing, outdoor-work benchmark exposed to seasonal labor supply and mechanization. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"45-0000\", statistic: \"p75\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Farming, fishing, and forestry wages add a goods-producing, outdoor-work benchmark exposed to seasonal labor supply and mechanization. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000045000014\", release: \"May 2025\", datatype: \"Annual 75th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Farming, fishing, and forestry wages add a goods-producing, outdoor-work benchmark exposed to seasonal labor supply and mechanization. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4800, distribution present, forecast step count 1.","evidence":["Farming, fishing, and forestry wages add a goods-producing, outdoor-work benchmark exposed to seasonal labor supply and mechanization. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued low-wage labor pressure in seasonal and outdoor work. The lower tail covers weaker commodity demand and more labor-saving mechanization."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_p75_wage_2025_usd: 44990, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'agricultural_labor_supply_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued low-wage labor pressure in seasonal and outdoor work. The lower tail covers weaker commodity demand and more labor-saving mechanization."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 75th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued low-wage labor pressure in seasonal and outdoor work. The lower tail covers weaker commodity demand and more labor-saving mechanization."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-farming-fishing-forestry-75th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-farming-fishing-forestry-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.e7d0870b795c344d","runId":"run.oews-farming-fishing-forestry-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.e7d0870b795c344d","predictionId":"oews-farming-fishing-forestry-75th-percentile-wage-may-2026","specId":"spec.oews-farming-fishing-forestry-75th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $44,990."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_45_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_45_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 44990, 80% interval [44490, 45490]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 44990, 80% interval [44490, 45490]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-farming-fishing-forestry-75th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-farming-fishing-forestry-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.9efdf8946750cbcf","runId":"run.oews-farming-fishing-forestry-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.9efdf8946750cbcf","predictionId":"oews-farming-fishing-forestry-90th-percentile-wage-may-2026","specId":"spec.oews-farming-fishing-forestry-90th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Farming, fishing, and forestry wages add a goods-producing, outdoor-work benchmark exposed to seasonal labor supply and mechanization. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"45-0000\", statistic: \"p90\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Farming, fishing, and forestry wages add a goods-producing, outdoor-work benchmark exposed to seasonal labor supply and mechanization. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000045000015\", release: \"May 2025\", datatype: \"Annual 90th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Farming, fishing, and forestry wages add a goods-producing, outdoor-work benchmark exposed to seasonal labor supply and mechanization. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6200, distribution present, forecast step count 1.","evidence":["Farming, fishing, and forestry wages add a goods-producing, outdoor-work benchmark exposed to seasonal labor supply and mechanization. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued low-wage labor pressure in seasonal and outdoor work. The lower tail covers weaker commodity demand and more labor-saving mechanization."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_p90_wage_2025_usd: 58220, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'agricultural_labor_supply_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued low-wage labor pressure in seasonal and outdoor work. The lower tail covers weaker commodity demand and more labor-saving mechanization."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 90th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is continued low-wage labor pressure in seasonal and outdoor work. The lower tail covers weaker commodity demand and more labor-saving mechanization."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-farming-fishing-forestry-90th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-farming-fishing-forestry-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.9631ed2586c46b8e","runId":"run.oews-farming-fishing-forestry-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.9631ed2586c46b8e","predictionId":"oews-farming-fishing-forestry-90th-percentile-wage-may-2026","specId":"spec.oews-farming-fishing-forestry-90th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $58,220."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_45_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_45_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 58220, 80% interval [57720, 58720]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 58220, 80% interval [57720, 58720]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-farming-fishing-forestry-90th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-construction-extraction-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.07e952258ff6de99","runId":"run.oews-construction-extraction-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.07e952258ff6de99","predictionId":"oews-construction-extraction-10th-percentile-wage-may-2026","specId":"spec.oews-construction-extraction-10th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Construction and extraction wages measure skilled-trades pressure tied to infrastructure, housing, energy, and limited short-run task automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"47-0000\", statistic: \"p10\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Construction and extraction wages measure skilled-trades pressure tied to infrastructure, housing, energy, and limited short-run task automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000047000011\", release: \"May 2025\", datatype: \"Annual 10th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Construction and extraction wages measure skilled-trades pressure tied to infrastructure, housing, energy, and limited short-run task automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4100, distribution present, forecast step count 1.","evidence":["Construction and extraction wages measure skilled-trades pressure tied to infrastructure, housing, energy, and limited short-run task automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is skilled-trades shortages and infrastructure demand supporting wage growth. The lower tail covers a weaker housing cycle and slower project starts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Construction and extraction wages measure skilled-trades pressure tied to infrastructure, housing, energy, and limited short-run task automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool result: { base_p10_wage_2025_usd: 38100, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'skilled_trades_shortage_pressure' }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 10th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is skilled-trades shortages and infrastructure demand supporting wage growth. The lower tail covers a weaker housing cycle and slower project starts."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-construction-extraction-10th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-construction-extraction-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.41f505cdec12c955","runId":"run.oews-construction-extraction-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.41f505cdec12c955","predictionId":"oews-construction-extraction-10th-percentile-wage-may-2026","specId":"spec.oews-construction-extraction-10th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $38,100."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_47_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_47_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 38100, 80% interval [37600, 38600]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 38100, 80% interval [37600, 38600]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-construction-extraction-10th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-construction-extraction-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.6df3642bb7f6867e","runId":"run.oews-construction-extraction-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.6df3642bb7f6867e","predictionId":"oews-construction-extraction-25th-percentile-wage-may-2026","specId":"spec.oews-construction-extraction-25th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Construction and extraction wages measure skilled-trades pressure tied to infrastructure, housing, energy, and limited short-run task automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"47-0000\", statistic: \"p25\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Construction and extraction wages measure skilled-trades pressure tied to infrastructure, housing, energy, and limited short-run task automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000047000012\", release: \"May 2025\", datatype: \"Annual 25th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Construction and extraction wages measure skilled-trades pressure tied to infrastructure, housing, energy, and limited short-run task automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4900, distribution present, forecast step count 1.","evidence":["Construction and extraction wages measure skilled-trades pressure tied to infrastructure, housing, energy, and limited short-run task automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is skilled-trades shortages and infrastructure demand supporting wage growth. The lower tail covers a weaker housing cycle and slower project starts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Construction and extraction wages measure skilled-trades pressure tied to infrastructure, housing, energy, and limited short-run task automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool result: { base_p25_wage_2025_usd: 46880, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'skilled_trades_shortage_pressure' }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 25th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is skilled-trades shortages and infrastructure demand supporting wage growth. The lower tail covers a weaker housing cycle and slower project starts."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-construction-extraction-25th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-construction-extraction-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.6d6343fa4711d8ce","runId":"run.oews-construction-extraction-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.6d6343fa4711d8ce","predictionId":"oews-construction-extraction-25th-percentile-wage-may-2026","specId":"spec.oews-construction-extraction-25th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $46,880."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_47_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_47_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 46880, 80% interval [46380, 47380]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 46880, 80% interval [46380, 47380]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-construction-extraction-25th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-construction-extraction-median-wage-may-2026.2026-06-21T13-35-00-04-00.eee5b2649af3ce3e","runId":"run.oews-construction-extraction-median-wage-may-2026.2026-06-21T13-35-00-04-00.eee5b2649af3ce3e","predictionId":"oews-construction-extraction-median-wage-may-2026","specId":"spec.oews-construction-extraction-median-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Construction and extraction wages measure skilled-trades pressure tied to infrastructure, housing, energy, and limited short-run task automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000047000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Construction and extraction wages measure skilled-trades pressure tied to infrastructure, housing, energy, and limited short-run task automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000047000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Construction and extraction wages measure skilled-trades pressure tied to infrastructure, housing, energy, and limited short-run task automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6300, distribution present, forecast step count 1.","evidence":["Construction and extraction wages measure skilled-trades pressure tied to infrastructure, housing, energy, and limited short-run task automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is skilled-trades shortages and infrastructure demand supporting wage growth. The lower tail covers a weaker housing cycle and slower project starts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Construction and extraction wages measure skilled-trades pressure tied to infrastructure, housing, energy, and limited short-run task automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool result: { base_median_wage_2025_usd: 59540, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'skilled_trades_shortage_pressure' }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual median wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is skilled-trades shortages and infrastructure demand supporting wage growth. The lower tail covers a weaker housing cycle and slower project starts."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-construction-extraction-median-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-construction-extraction-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.663304499c0e46ee","runId":"run.oews-construction-extraction-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.663304499c0e46ee","predictionId":"oews-construction-extraction-median-wage-may-2026","specId":"spec.oews-construction-extraction-median-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_47_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_47_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_47_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 59540, 80% interval [59040, 60040]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 59540, 80% interval [59040, 60040]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-construction-extraction-median-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-construction-extraction-mean-wage-may-2026.2026-06-21T13-35-00-04-00.b66537acf47d84fe","runId":"run.oews-construction-extraction-mean-wage-may-2026.2026-06-21T13-35-00-04-00.b66537acf47d84fe","predictionId":"oews-construction-extraction-mean-wage-may-2026","specId":"spec.oews-construction-extraction-mean-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Construction and extraction wages measure skilled-trades pressure tied to infrastructure, housing, energy, and limited short-run task automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"47-0000\", statistic: \"mean\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Construction and extraction wages measure skilled-trades pressure tied to infrastructure, housing, energy, and limited short-run task automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000047000004\", release: \"May 2025\", datatype: \"Annual mean wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Construction and extraction wages measure skilled-trades pressure tied to infrastructure, housing, energy, and limited short-run task automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 7000, distribution present, forecast step count 1.","evidence":["Construction and extraction wages measure skilled-trades pressure tied to infrastructure, housing, energy, and limited short-run task automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is skilled-trades shortages and infrastructure demand supporting wage growth. The lower tail covers a weaker housing cycle and slower project starts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Construction and extraction wages measure skilled-trades pressure tied to infrastructure, housing, energy, and limited short-run task automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool result: { base_mean_wage_2025_usd: 65360, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'skilled_trades_shortage_pressure' }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual mean wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is skilled-trades shortages and infrastructure demand supporting wage growth. The lower tail covers a weaker housing cycle and slower project starts."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-construction-extraction-mean-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-construction-extraction-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.0825eedfc9b99705","runId":"run.oews-construction-extraction-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.0825eedfc9b99705","predictionId":"oews-construction-extraction-mean-wage-may-2026","specId":"spec.oews-construction-extraction-mean-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $65,360."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_47_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_47_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 65360, 80% interval [64860, 65860]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 65360, 80% interval [64860, 65860]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-construction-extraction-mean-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-construction-extraction-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.8c67292b2c94c6b8","runId":"run.oews-construction-extraction-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.8c67292b2c94c6b8","predictionId":"oews-construction-extraction-75th-percentile-wage-may-2026","specId":"spec.oews-construction-extraction-75th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Construction and extraction wages measure skilled-trades pressure tied to infrastructure, housing, energy, and limited short-run task automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"47-0000\", statistic: \"p75\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Construction and extraction wages measure skilled-trades pressure tied to infrastructure, housing, energy, and limited short-run task automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000047000014\", release: \"May 2025\", datatype: \"Annual 75th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Construction and extraction wages measure skilled-trades pressure tied to infrastructure, housing, energy, and limited short-run task automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 8300, distribution present, forecast step count 1.","evidence":["Construction and extraction wages measure skilled-trades pressure tied to infrastructure, housing, energy, and limited short-run task automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is skilled-trades shortages and infrastructure demand supporting wage growth. The lower tail covers a weaker housing cycle and slower project starts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Construction and extraction wages measure skilled-trades pressure tied to infrastructure, housing, energy, and limited short-run task automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool result: { base_p75_wage_2025_usd: 77970, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'skilled_trades_shortage_pressure' }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 75th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is skilled-trades shortages and infrastructure demand supporting wage growth. The lower tail covers a weaker housing cycle and slower project starts."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-construction-extraction-75th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-construction-extraction-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.5345e054615dee5e","runId":"run.oews-construction-extraction-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.5345e054615dee5e","predictionId":"oews-construction-extraction-75th-percentile-wage-may-2026","specId":"spec.oews-construction-extraction-75th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $77,970."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_47_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_47_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 77970, 80% interval [77470, 78470]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 77970, 80% interval [77470, 78470]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-construction-extraction-75th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-construction-extraction-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.1ff5b5bad246e76d","runId":"run.oews-construction-extraction-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.1ff5b5bad246e76d","predictionId":"oews-construction-extraction-90th-percentile-wage-may-2026","specId":"spec.oews-construction-extraction-90th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Construction and extraction wages measure skilled-trades pressure tied to infrastructure, housing, energy, and limited short-run task automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"47-0000\", statistic: \"p90\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Construction and extraction wages measure skilled-trades pressure tied to infrastructure, housing, energy, and limited short-run task automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000047000015\", release: \"May 2025\", datatype: \"Annual 90th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Construction and extraction wages measure skilled-trades pressure tied to infrastructure, housing, energy, and limited short-run task automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 10800, distribution present, forecast step count 1.","evidence":["Construction and extraction wages measure skilled-trades pressure tied to infrastructure, housing, energy, and limited short-run task automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is skilled-trades shortages and infrastructure demand supporting wage growth. The lower tail covers a weaker housing cycle and slower project starts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Construction and extraction wages measure skilled-trades pressure tied to infrastructure, housing, energy, and limited short-run task automation. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool result: { base_p90_wage_2025_usd: 101650, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'skilled_trades_shortage_pressure' }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 90th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is skilled-trades shortages and infrastructure demand supporting wage growth. The lower tail covers a weaker housing cycle and slower project starts."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-construction-extraction-90th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-construction-extraction-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.c78e5aeb5aa09021","runId":"run.oews-construction-extraction-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.c78e5aeb5aa09021","predictionId":"oews-construction-extraction-90th-percentile-wage-may-2026","specId":"spec.oews-construction-extraction-90th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $101,650."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_47_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_47_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 101650, 80% interval [101150, 102150]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 101650, 80% interval [101150, 102150]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-construction-extraction-90th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-installation-maintenance-repair-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.e57927c5deebaf44","runId":"run.oews-installation-maintenance-repair-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.e57927c5deebaf44","predictionId":"oews-installation-maintenance-repair-10th-percentile-wage-may-2026","specId":"spec.oews-installation-maintenance-repair-10th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Installation and repair wages track hands-on technical work that may benefit from AI diagnostics while remaining hard to automate physically. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"49-0000\", statistic: \"p10\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Installation and repair wages track hands-on technical work that may benefit from AI diagnostics while remaining hard to automate physically. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000049000011\", release: \"May 2025\", datatype: \"Annual 10th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Installation and repair wages track hands-on technical work that may benefit from AI diagnostics while remaining hard to automate physically. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3900, distribution present, forecast step count 1.","evidence":["Installation and repair wages track hands-on technical work that may benefit from AI diagnostics while remaining hard to automate physically. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in hands-on technical roles and steady repair demand. The lower tail covers weaker goods activity and productivity gains from diagnostic tools."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_p10_wage_2025_usd: 37000, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'hands_on_technical_shortage_pressure' }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 10th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in hands-on technical roles and steady repair demand. The lower tail covers weaker goods activity and productivity gains from diagnostic tools."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-installation-maintenance-repair-10th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-installation-maintenance-repair-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.957b859525a9fc5b","runId":"run.oews-installation-maintenance-repair-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.957b859525a9fc5b","predictionId":"oews-installation-maintenance-repair-10th-percentile-wage-may-2026","specId":"spec.oews-installation-maintenance-repair-10th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $37,000."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_49_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_49_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 37000, 80% interval [36500, 37500]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 37000, 80% interval [36500, 37500]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-installation-maintenance-repair-10th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-installation-maintenance-repair-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.78033d13d40233ad","runId":"run.oews-installation-maintenance-repair-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.78033d13d40233ad","predictionId":"oews-installation-maintenance-repair-25th-percentile-wage-may-2026","specId":"spec.oews-installation-maintenance-repair-25th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Installation and repair wages track hands-on technical work that may benefit from AI diagnostics while remaining hard to automate physically. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"49-0000\", statistic: \"p25\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Installation and repair wages track hands-on technical work that may benefit from AI diagnostics while remaining hard to automate physically. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000049000012\", release: \"May 2025\", datatype: \"Annual 25th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Installation and repair wages track hands-on technical work that may benefit from AI diagnostics while remaining hard to automate physically. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4900, distribution present, forecast step count 1.","evidence":["Installation and repair wages track hands-on technical work that may benefit from AI diagnostics while remaining hard to automate physically. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in hands-on technical roles and steady repair demand. The lower tail covers weaker goods activity and productivity gains from diagnostic tools."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_p25_wage_2025_usd: 46110, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'hands_on_technical_shortage_pressure' }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 25th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in hands-on technical roles and steady repair demand. The lower tail covers weaker goods activity and productivity gains from diagnostic tools."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-installation-maintenance-repair-25th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-installation-maintenance-repair-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.ba13d37174a6602a","runId":"run.oews-installation-maintenance-repair-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.ba13d37174a6602a","predictionId":"oews-installation-maintenance-repair-25th-percentile-wage-may-2026","specId":"spec.oews-installation-maintenance-repair-25th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $46,110."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_49_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_49_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 46110, 80% interval [45610, 46610]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 46110, 80% interval [45610, 46610]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-installation-maintenance-repair-25th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-installation-maintenance-repair-median-wage-may-2026.2026-06-21T13-35-00-04-00.87d3b924c9213fcc","runId":"run.oews-installation-maintenance-repair-median-wage-may-2026.2026-06-21T13-35-00-04-00.87d3b924c9213fcc","predictionId":"oews-installation-maintenance-repair-median-wage-may-2026","specId":"spec.oews-installation-maintenance-repair-median-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Installation and repair wages track hands-on technical work that may benefit from AI diagnostics while remaining hard to automate physically. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000049000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Installation and repair wages track hands-on technical work that may benefit from AI diagnostics while remaining hard to automate physically. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000049000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Installation and repair wages track hands-on technical work that may benefit from AI diagnostics while remaining hard to automate physically. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6300, distribution present, forecast step count 1.","evidence":["Installation and repair wages track hands-on technical work that may benefit from AI diagnostics while remaining hard to automate physically. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in hands-on technical roles and steady repair demand. The lower tail covers weaker goods activity and productivity gains from diagnostic tools."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_median_wage_2025_usd: 59620, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'hands_on_technical_shortage_pressure' }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual median wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in hands-on technical roles and steady repair demand. The lower tail covers weaker goods activity and productivity gains from diagnostic tools."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-installation-maintenance-repair-median-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-installation-maintenance-repair-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.81ee67c69600e385","runId":"run.oews-installation-maintenance-repair-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.81ee67c69600e385","predictionId":"oews-installation-maintenance-repair-median-wage-may-2026","specId":"spec.oews-installation-maintenance-repair-median-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_49_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_49_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_49_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 59620, 80% interval [59120, 60120]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 59620, 80% interval [59120, 60120]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-installation-maintenance-repair-median-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-installation-maintenance-repair-mean-wage-may-2026.2026-06-21T13-35-00-04-00.8ad69a5cc0ac89ad","runId":"run.oews-installation-maintenance-repair-mean-wage-may-2026.2026-06-21T13-35-00-04-00.8ad69a5cc0ac89ad","predictionId":"oews-installation-maintenance-repair-mean-wage-may-2026","specId":"spec.oews-installation-maintenance-repair-mean-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Installation and repair wages track hands-on technical work that may benefit from AI diagnostics while remaining hard to automate physically. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"49-0000\", statistic: \"mean\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Installation and repair wages track hands-on technical work that may benefit from AI diagnostics while remaining hard to automate physically. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000049000004\", release: \"May 2025\", datatype: \"Annual mean wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Installation and repair wages track hands-on technical work that may benefit from AI diagnostics while remaining hard to automate physically. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6700, distribution present, forecast step count 1.","evidence":["Installation and repair wages track hands-on technical work that may benefit from AI diagnostics while remaining hard to automate physically. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in hands-on technical roles and steady repair demand. The lower tail covers weaker goods activity and productivity gains from diagnostic tools."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_mean_wage_2025_usd: 63320, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'hands_on_technical_shortage_pressure' }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual mean wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in hands-on technical roles and steady repair demand. The lower tail covers weaker goods activity and productivity gains from diagnostic tools."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-installation-maintenance-repair-mean-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-installation-maintenance-repair-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.837ab4677688a1fd","runId":"run.oews-installation-maintenance-repair-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.837ab4677688a1fd","predictionId":"oews-installation-maintenance-repair-mean-wage-may-2026","specId":"spec.oews-installation-maintenance-repair-mean-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $63,320."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_49_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_49_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 63320, 80% interval [62820, 63820]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 63320, 80% interval [62820, 63820]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-installation-maintenance-repair-mean-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-installation-maintenance-repair-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.ab2be1201d5b8e71","runId":"run.oews-installation-maintenance-repair-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.ab2be1201d5b8e71","predictionId":"oews-installation-maintenance-repair-75th-percentile-wage-may-2026","specId":"spec.oews-installation-maintenance-repair-75th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Installation and repair wages track hands-on technical work that may benefit from AI diagnostics while remaining hard to automate physically. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"49-0000\", statistic: \"p75\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Installation and repair wages track hands-on technical work that may benefit from AI diagnostics while remaining hard to automate physically. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000049000014\", release: \"May 2025\", datatype: \"Annual 75th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Installation and repair wages track hands-on technical work that may benefit from AI diagnostics while remaining hard to automate physically. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 8200, distribution present, forecast step count 1.","evidence":["Installation and repair wages track hands-on technical work that may benefit from AI diagnostics while remaining hard to automate physically. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in hands-on technical roles and steady repair demand. The lower tail covers weaker goods activity and productivity gains from diagnostic tools."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_p75_wage_2025_usd: 76670, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'hands_on_technical_shortage_pressure' }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 75th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in hands-on technical roles and steady repair demand. The lower tail covers weaker goods activity and productivity gains from diagnostic tools."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-installation-maintenance-repair-75th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-installation-maintenance-repair-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.11bb567630753212","runId":"run.oews-installation-maintenance-repair-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.11bb567630753212","predictionId":"oews-installation-maintenance-repair-75th-percentile-wage-may-2026","specId":"spec.oews-installation-maintenance-repair-75th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $76,670."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_49_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_49_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 76670, 80% interval [76170, 77170]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 76670, 80% interval [76170, 77170]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-installation-maintenance-repair-75th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-installation-maintenance-repair-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.9343217257e38189","runId":"run.oews-installation-maintenance-repair-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.9343217257e38189","predictionId":"oews-installation-maintenance-repair-90th-percentile-wage-may-2026","specId":"spec.oews-installation-maintenance-repair-90th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Installation and repair wages track hands-on technical work that may benefit from AI diagnostics while remaining hard to automate physically. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"49-0000\", statistic: \"p90\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Installation and repair wages track hands-on technical work that may benefit from AI diagnostics while remaining hard to automate physically. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000049000015\", release: \"May 2025\", datatype: \"Annual 90th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Installation and repair wages track hands-on technical work that may benefit from AI diagnostics while remaining hard to automate physically. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 10200, distribution present, forecast step count 1.","evidence":["Installation and repair wages track hands-on technical work that may benefit from AI diagnostics while remaining hard to automate physically. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in hands-on technical roles and steady repair demand. The lower tail covers weaker goods activity and productivity gains from diagnostic tools."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_p90_wage_2025_usd: 96540, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'hands_on_technical_shortage_pressure' }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 90th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in hands-on technical roles and steady repair demand. The lower tail covers weaker goods activity and productivity gains from diagnostic tools."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-installation-maintenance-repair-90th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-installation-maintenance-repair-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.076c4d512b8bd25b","runId":"run.oews-installation-maintenance-repair-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.076c4d512b8bd25b","predictionId":"oews-installation-maintenance-repair-90th-percentile-wage-may-2026","specId":"spec.oews-installation-maintenance-repair-90th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $96,540."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_49_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_49_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 96540, 80% interval [96040, 97040]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 96540, 80% interval [96040, 97040]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-installation-maintenance-repair-90th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-production-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.c6a9d19ee805b1e1","runId":"run.oews-production-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.c6a9d19ee805b1e1","predictionId":"oews-production-10th-percentile-wage-may-2026","specId":"spec.oews-production-10th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.59,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Production wages connect automation to manufacturing labor demand, robotics, reshoring, union contracts, and goods-sector cyclicality rather than only information-work substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"51-0000\", statistic: \"p10\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Production wages connect automation to manufacturing labor demand, robotics, reshoring, union contracts, and goods-sector cyclicality rather than only information-work substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000051000011\", release: \"May 2025\", datatype: \"Annual 10th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Production wages connect automation to manufacturing labor demand, robotics, reshoring, union contracts, and goods-sector cyclicality rather than only information-work substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3700, distribution present, forecast step count 1.","evidence":["Production wages connect automation to manufacturing labor demand, robotics, reshoring, union contracts, and goods-sector cyclicality rather than only information-work substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in skilled production roles and existing wage contracts offsetting automation pressure. The lower tail covers mixed manufacturing demand and faster process-control or robotics productivity gains."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in skilled production roles and existing wage contracts offsetting automation pressure. The lower tail covers mixed manufacturing demand and faster process-control or robotics productivity gains."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in skilled production roles and existing wage contracts offsetting automation pressure. The lower tail covers mixed manufacturing demand and faster process-control or robotics productivity gains."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 10th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in skilled production roles and existing wage contracts offsetting automation pressure. The lower tail covers mixed manufacturing demand and faster process-control or robotics productivity gains."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-production-10th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (3/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-production-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.4564c781e3f4dc8f","runId":"run.oews-production-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.4564c781e3f4dc8f","predictionId":"oews-production-10th-percentile-wage-may-2026","specId":"spec.oews-production-10th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $34,240."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_51_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_51_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 34240, 80% interval [33740, 34740]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 34240, 80% interval [33740, 34740]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-production-10th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-production-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.f81115ac269799a2","runId":"run.oews-production-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.f81115ac269799a2","predictionId":"oews-production-25th-percentile-wage-may-2026","specId":"spec.oews-production-25th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.59,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Production wages connect automation to manufacturing labor demand, robotics, reshoring, union contracts, and goods-sector cyclicality rather than only information-work substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"51-0000\", statistic: \"p25\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Production wages connect automation to manufacturing labor demand, robotics, reshoring, union contracts, and goods-sector cyclicality rather than only information-work substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000051000012\", release: \"May 2025\", datatype: \"Annual 25th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Production wages connect automation to manufacturing labor demand, robotics, reshoring, union contracts, and goods-sector cyclicality rather than only information-work substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4000, distribution present, forecast step count 1.","evidence":["Production wages connect automation to manufacturing labor demand, robotics, reshoring, union contracts, and goods-sector cyclicality rather than only information-work substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in skilled production roles and existing wage contracts offsetting automation pressure. The lower tail covers mixed manufacturing demand and faster process-control or robotics productivity gains."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in skilled production roles and existing wage contracts offsetting automation pressure. The lower tail covers mixed manufacturing demand and faster process-control or robotics productivity gains."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in skilled production roles and existing wage contracts offsetting automation pressure. The lower tail covers mixed manufacturing demand and faster process-control or robotics productivity gains."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 25th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in skilled production roles and existing wage contracts offsetting automation pressure. The lower tail covers mixed manufacturing demand and faster process-control or robotics productivity gains."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-production-25th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (3/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-production-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.f899877acd3aa7aa","runId":"run.oews-production-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.f899877acd3aa7aa","predictionId":"oews-production-25th-percentile-wage-may-2026","specId":"spec.oews-production-25th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $38,130."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_51_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_51_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 38130, 80% interval [37630, 38630]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 38130, 80% interval [37630, 38630]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-production-25th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-production-median-wage-may-2026.2026-06-21T13-35-00-04-00.40c39d71e1c8dfdc","runId":"run.oews-production-median-wage-may-2026.2026-06-21T13-35-00-04-00.40c39d71e1c8dfdc","predictionId":"oews-production-median-wage-may-2026","specId":"spec.oews-production-median-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.59,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Production wages connect automation to manufacturing labor demand, robotics, reshoring, union contracts, and goods-sector cyclicality rather than only information-work substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000051000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Production wages connect automation to manufacturing labor demand, robotics, reshoring, union contracts, and goods-sector cyclicality rather than only information-work substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000051000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Production wages connect automation to manufacturing labor demand, robotics, reshoring, union contracts, and goods-sector cyclicality rather than only information-work substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5000, distribution present, forecast step count 1.","evidence":["Production wages connect automation to manufacturing labor demand, robotics, reshoring, union contracts, and goods-sector cyclicality rather than only information-work substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in skilled production roles and existing wage contracts offsetting automation pressure. The lower tail covers mixed manufacturing demand and faster process-control or robotics productivity gains."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in skilled production roles and existing wage contracts offsetting automation pressure. The lower tail covers mixed manufacturing demand and faster process-control or robotics productivity gains."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in skilled production roles and existing wage contracts offsetting automation pressure. The lower tail covers mixed manufacturing demand and faster process-control or robotics productivity gains."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual median wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in skilled production roles and existing wage contracts offsetting automation pressure. The lower tail covers mixed manufacturing demand and faster process-control or robotics productivity gains."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-production-median-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (3/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-production-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.17e3a9bc5318d1a1","runId":"run.oews-production-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.17e3a9bc5318d1a1","predictionId":"oews-production-median-wage-may-2026","specId":"spec.oews-production-median-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_51_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_51_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_51_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 46990, 80% interval [46490, 47490]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 46990, 80% interval [46490, 47490]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-production-median-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-production-mean-wage-may-2026.2026-06-21T13-35-00-04-00.5af8e3dc1c07f0fb","runId":"run.oews-production-mean-wage-may-2026.2026-06-21T13-35-00-04-00.5af8e3dc1c07f0fb","predictionId":"oews-production-mean-wage-may-2026","specId":"spec.oews-production-mean-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.59,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Production wages connect automation to manufacturing labor demand, robotics, reshoring, union contracts, and goods-sector cyclicality rather than only information-work substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"51-0000\", statistic: \"mean\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Production wages connect automation to manufacturing labor demand, robotics, reshoring, union contracts, and goods-sector cyclicality rather than only information-work substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000051000004\", release: \"May 2025\", datatype: \"Annual mean wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Production wages connect automation to manufacturing labor demand, robotics, reshoring, union contracts, and goods-sector cyclicality rather than only information-work substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5500, distribution present, forecast step count 1.","evidence":["Production wages connect automation to manufacturing labor demand, robotics, reshoring, union contracts, and goods-sector cyclicality rather than only information-work substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in skilled production roles and existing wage contracts offsetting automation pressure. The lower tail covers mixed manufacturing demand and faster process-control or robotics productivity gains."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in skilled production roles and existing wage contracts offsetting automation pressure. The lower tail covers mixed manufacturing demand and faster process-control or robotics productivity gains."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in skilled production roles and existing wage contracts offsetting automation pressure. The lower tail covers mixed manufacturing demand and faster process-control or robotics productivity gains."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual mean wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in skilled production roles and existing wage contracts offsetting automation pressure. The lower tail covers mixed manufacturing demand and faster process-control or robotics productivity gains."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-production-mean-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (3/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-production-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.9ce1841c34de2443","runId":"run.oews-production-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.9ce1841c34de2443","predictionId":"oews-production-mean-wage-may-2026","specId":"spec.oews-production-mean-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $51,600."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_51_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_51_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 51600, 80% interval [51100, 52100]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 51600, 80% interval [51100, 52100]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-production-mean-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-production-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.ea8bc3afd218c735","runId":"run.oews-production-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.ea8bc3afd218c735","predictionId":"oews-production-75th-percentile-wage-may-2026","specId":"spec.oews-production-75th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.59,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Production wages connect automation to manufacturing labor demand, robotics, reshoring, union contracts, and goods-sector cyclicality rather than only information-work substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"51-0000\", statistic: \"p75\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Production wages connect automation to manufacturing labor demand, robotics, reshoring, union contracts, and goods-sector cyclicality rather than only information-work substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000051000014\", release: \"May 2025\", datatype: \"Annual 75th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Production wages connect automation to manufacturing labor demand, robotics, reshoring, union contracts, and goods-sector cyclicality rather than only information-work substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6300, distribution present, forecast step count 1.","evidence":["Production wages connect automation to manufacturing labor demand, robotics, reshoring, union contracts, and goods-sector cyclicality rather than only information-work substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in skilled production roles and existing wage contracts offsetting automation pressure. The lower tail covers mixed manufacturing demand and faster process-control or robotics productivity gains."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in skilled production roles and existing wage contracts offsetting automation pressure. The lower tail covers mixed manufacturing demand and faster process-control or robotics productivity gains."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in skilled production roles and existing wage contracts offsetting automation pressure. The lower tail covers mixed manufacturing demand and faster process-control or robotics productivity gains."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 75th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in skilled production roles and existing wage contracts offsetting automation pressure. The lower tail covers mixed manufacturing demand and faster process-control or robotics productivity gains."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-production-75th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (3/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-production-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.71e3710526d03a3a","runId":"run.oews-production-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.71e3710526d03a3a","predictionId":"oews-production-75th-percentile-wage-may-2026","specId":"spec.oews-production-75th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $59,920."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_51_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_51_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 59920, 80% interval [59420, 60420]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 59920, 80% interval [59420, 60420]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-production-75th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-production-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.83f19770941adbfc","runId":"run.oews-production-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.83f19770941adbfc","predictionId":"oews-production-90th-percentile-wage-may-2026","specId":"spec.oews-production-90th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.59,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["Production wages connect automation to manufacturing labor demand, robotics, reshoring, union contracts, and goods-sector cyclicality rather than only information-work substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"51-0000\", statistic: \"p90\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Production wages connect automation to manufacturing labor demand, robotics, reshoring, union contracts, and goods-sector cyclicality rather than only information-work substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000051000015\", release: \"May 2025\", datatype: \"Annual 90th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","Production wages connect automation to manufacturing labor demand, robotics, reshoring, union contracts, and goods-sector cyclicality rather than only information-work substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 8100, distribution present, forecast step count 1.","evidence":["Production wages connect automation to manufacturing labor demand, robotics, reshoring, union contracts, and goods-sector cyclicality rather than only information-work substitution. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in skilled production roles and existing wage contracts offsetting automation pressure. The lower tail covers mixed manufacturing demand and faster process-control or robotics productivity gains."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in skilled production roles and existing wage contracts offsetting automation pressure. The lower tail covers mixed manufacturing demand and faster process-control or robotics productivity gains."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in skilled production roles and existing wage contracts offsetting automation pressure. The lower tail covers mixed manufacturing demand and faster process-control or robotics productivity gains."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 90th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is shortages in skilled production roles and existing wage contracts offsetting automation pressure. The lower tail covers mixed manufacturing demand and faster process-control or robotics productivity gains."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-production-90th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (3/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-production-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.efe5ffd0eec05fea","runId":"run.oews-production-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.efe5ffd0eec05fea","predictionId":"oews-production-90th-percentile-wage-may-2026","specId":"spec.oews-production-90th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $76,990."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_51_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_51_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 76990, 80% interval [76490, 77490]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 76990, 80% interval [76490, 77490]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-production-90th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-transport-material-moving-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.bf7dba380dff2589","runId":"run.oews-transport-material-moving-10th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.bf7dba380dff2589","predictionId":"oews-transport-material-moving-10th-percentile-wage-may-2026","specId":"spec.oews-transport-material-moving-10th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.73,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["This wage target tracks logistics, warehousing, driving, routing, and material movement where automation can change task mix before full autonomy changes employment. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"53-0000\", statistic: \"p10\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["This wage target tracks logistics, warehousing, driving, routing, and material movement where automation can change task mix before full autonomy changes employment. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000053000011\", release: \"May 2025\", datatype: \"Annual 10th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","This wage target tracks logistics, warehousing, driving, routing, and material movement where automation can change task mix before full autonomy changes employment. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3300, distribution present, forecast step count 1.","evidence":["This wage target tracks logistics, warehousing, driving, routing, and material movement where automation can change task mix before full autonomy changes employment. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is driver and material-moving demand offset by warehouse automation and routing tools. The lower tail covers weaker goods movement volume and faster logistics automation."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_p10_wage_2025_usd: 31060, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'warehouse_routing_and_driver_wage_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is driver and material-moving demand offset by warehouse automation and routing tools. The lower tail covers weaker goods movement volume and faster logistics automation."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is driver and material-moving demand offset by warehouse automation and routing tools. The lower tail covers weaker goods movement volume and faster logistics automation."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 10th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 10th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is driver and material-moving demand offset by warehouse automation and routing tools. The lower tail covers weaker goods movement volume and faster logistics automation."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-transport-material-moving-10th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (3/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-transport-material-moving-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.9f8d527a5c973cb5","runId":"run.oews-transport-material-moving-10th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.9f8d527a5c973cb5","predictionId":"oews-transport-material-moving-10th-percentile-wage-may-2026","specId":"spec.oews-transport-material-moving-10th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $31,060."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_53_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_10th_percentile_annual_wage.soc_53_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct10\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 31060, 80% interval [30560, 31560]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 10th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 31060, 80% interval [30560, 31560]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-transport-material-moving-10th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-transport-material-moving-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.0ce949e2c7685f91","runId":"run.oews-transport-material-moving-25th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.0ce949e2c7685f91","predictionId":"oews-transport-material-moving-25th-percentile-wage-may-2026","specId":"spec.oews-transport-material-moving-25th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.73,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["This wage target tracks logistics, warehousing, driving, routing, and material movement where automation can change task mix before full autonomy changes employment. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"53-0000\", statistic: \"p25\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["This wage target tracks logistics, warehousing, driving, routing, and material movement where automation can change task mix before full autonomy changes employment. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000053000012\", release: \"May 2025\", datatype: \"Annual 25th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","This wage target tracks logistics, warehousing, driving, routing, and material movement where automation can change task mix before full autonomy changes employment. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3800, distribution present, forecast step count 1.","evidence":["This wage target tracks logistics, warehousing, driving, routing, and material movement where automation can change task mix before full autonomy changes employment. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is driver and material-moving demand offset by warehouse automation and routing tools. The lower tail covers weaker goods movement volume and faster logistics automation."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_p25_wage_2025_usd: 36290, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'warehouse_routing_and_driver_wage_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is driver and material-moving demand offset by warehouse automation and routing tools. The lower tail covers weaker goods movement volume and faster logistics automation."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is driver and material-moving demand offset by warehouse automation and routing tools. The lower tail covers weaker goods movement volume and faster logistics automation."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 25th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 25th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is driver and material-moving demand offset by warehouse automation and routing tools. The lower tail covers weaker goods movement volume and faster logistics automation."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-transport-material-moving-25th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (3/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-transport-material-moving-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.eed65335c8a08276","runId":"run.oews-transport-material-moving-25th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.eed65335c8a08276","predictionId":"oews-transport-material-moving-25th-percentile-wage-may-2026","specId":"spec.oews-transport-material-moving-25th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $36,290."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_53_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_25th_percentile_annual_wage.soc_53_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct25\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 36290, 80% interval [35790, 36790]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 25th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 36290, 80% interval [35790, 36790]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-transport-material-moving-25th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-transport-material-moving-median-wage-may-2026.2026-06-21T13-35-00-04-00.180ac87e368ff8e5","runId":"run.oews-transport-material-moving-median-wage-may-2026.2026-06-21T13-35-00-04-00.180ac87e368ff8e5","predictionId":"oews-transport-material-moving-median-wage-may-2026","specId":"spec.oews-transport-material-moving-median-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.73,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["This wage target tracks logistics, warehousing, driving, routing, and material movement where automation can change task mix before full autonomy changes employment. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000053000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["This wage target tracks logistics, warehousing, driving, routing, and material movement where automation can change task mix before full autonomy changes employment. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000053000013\", release: \"May 2025\", datatype: \"Annual median wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","This wage target tracks logistics, warehousing, driving, routing, and material movement where automation can change task mix before full autonomy changes employment. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4700, distribution present, forecast step count 1.","evidence":["This wage target tracks logistics, warehousing, driving, routing, and material movement where automation can change task mix before full autonomy changes employment. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is driver and material-moving demand offset by warehouse automation and routing tools. The lower tail covers weaker goods movement volume and faster logistics automation."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_median_wage_2025_usd: 44350, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'warehouse_routing_and_driver_wage_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is driver and material-moving demand offset by warehouse automation and routing tools. The lower tail covers weaker goods movement volume and faster logistics automation."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is driver and material-moving demand offset by warehouse automation and routing tools. The lower tail covers weaker goods movement volume and faster logistics automation."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual median wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific median observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is driver and material-moving demand offset by warehouse automation and routing tools. The lower tail covers weaker goods movement volume and faster logistics automation."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-transport-material-moving-median-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (3/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-transport-material-moving-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.2f32b82b8f03c649","runId":"run.oews-transport-material-moving-median-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.2f32b82b8f03c649","predictionId":"oews-transport-material-moving-median-wage-may-2026","specId":"spec.oews-transport-material-moving-median-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.97,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_53_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_53_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_median_annual_wage.soc_53_0000.may_2026.first_print\", comparator: \"latest_observed_a_median\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 44350, 80% interval [43850, 44850]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 median annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 44350, 80% interval [43850, 44850]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-transport-material-moving-median-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-transport-material-moving-mean-wage-may-2026.2026-06-21T13-35-00-04-00.f399c5c9f43032d8","runId":"run.oews-transport-material-moving-mean-wage-may-2026.2026-06-21T13-35-00-04-00.f399c5c9f43032d8","predictionId":"oews-transport-material-moving-mean-wage-may-2026","specId":"spec.oews-transport-material-moving-mean-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.73,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["This wage target tracks logistics, warehousing, driving, routing, and material movement where automation can change task mix before full autonomy changes employment. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"53-0000\", statistic: \"mean\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["This wage target tracks logistics, warehousing, driving, routing, and material movement where automation can change task mix before full autonomy changes employment. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000053000004\", release: \"May 2025\", datatype: \"Annual mean wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","This wage target tracks logistics, warehousing, driving, routing, and material movement where automation can change task mix before full autonomy changes employment. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5300, distribution present, forecast step count 1.","evidence":["This wage target tracks logistics, warehousing, driving, routing, and material movement where automation can change task mix before full autonomy changes employment. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is driver and material-moving demand offset by warehouse automation and routing tools. The lower tail covers weaker goods movement volume and faster logistics automation."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_mean_wage_2025_usd: 49850, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'warehouse_routing_and_driver_wage_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is driver and material-moving demand offset by warehouse automation and routing tools. The lower tail covers weaker goods movement volume and faster logistics automation."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is driver and material-moving demand offset by warehouse automation and routing tools. The lower tail covers weaker goods movement volume and faster logistics automation."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual mean wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific mean observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is driver and material-moving demand offset by warehouse automation and routing tools. The lower tail covers weaker goods movement volume and faster logistics automation."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-transport-material-moving-mean-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (3/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-transport-material-moving-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.1820656a10154e8a","runId":"run.oews-transport-material-moving-mean-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.1820656a10154e8a","predictionId":"oews-transport-material-moving-mean-wage-may-2026","specId":"spec.oews-transport-material-moving-mean-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $49,850."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_53_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_mean_annual_wage.soc_53_0000.may_2026.first_print\", comparator: \"latest_observed_a_mean\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 49850, 80% interval [49350, 50350]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 mean annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 49850, 80% interval [49350, 50350]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-transport-material-moving-mean-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-transport-material-moving-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.25d1666735f5ee97","runId":"run.oews-transport-material-moving-75th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.25d1666735f5ee97","predictionId":"oews-transport-material-moving-75th-percentile-wage-may-2026","specId":"spec.oews-transport-material-moving-75th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.73,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["This wage target tracks logistics, warehousing, driving, routing, and material movement where automation can change task mix before full autonomy changes employment. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"53-0000\", statistic: \"p75\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["This wage target tracks logistics, warehousing, driving, routing, and material movement where automation can change task mix before full autonomy changes employment. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000053000014\", release: \"May 2025\", datatype: \"Annual 75th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","This wage target tracks logistics, warehousing, driving, routing, and material movement where automation can change task mix before full autonomy changes employment. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6000, distribution present, forecast step count 1.","evidence":["This wage target tracks logistics, warehousing, driving, routing, and material movement where automation can change task mix before full autonomy changes employment. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is driver and material-moving demand offset by warehouse automation and routing tools. The lower tail covers weaker goods movement volume and faster logistics automation."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_p75_wage_2025_usd: 55990, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'warehouse_routing_and_driver_wage_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is driver and material-moving demand offset by warehouse automation and routing tools. The lower tail covers weaker goods movement volume and faster logistics automation."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is driver and material-moving demand offset by warehouse automation and routing tools. The lower tail covers weaker goods movement volume and faster logistics automation."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 75th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 75th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is driver and material-moving demand offset by warehouse automation and routing tools. The lower tail covers weaker goods movement volume and faster logistics automation."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-transport-material-moving-75th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (3/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-transport-material-moving-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.9e2b1eeb501eb1ea","runId":"run.oews-transport-material-moving-75th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.9e2b1eeb501eb1ea","predictionId":"oews-transport-material-moving-75th-percentile-wage-may-2026","specId":"spec.oews-transport-material-moving-75th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $55,990."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_53_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_75th_percentile_annual_wage.soc_53_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct75\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 55990, 80% interval [55490, 56490]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 75th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 55990, 80% interval [55490, 56490]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-transport-material-moving-75th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-transport-material-moving-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.3eade9aa808a8b87","runId":"run.oews-transport-material-moving-90th-percentile-wage-may-2026.2026-06-21T13-35-00-04-00.3eade9aa808a8b87","predictionId":"oews-transport-material-moving-90th-percentile-wage-may-2026","specId":"spec.oews-transport-material-moving-90th-percentile-wage-may-2026","runLabel":"Occupation wage pressure - no projection pack","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.73,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 1 historical point(s) and explicit outside-view language.","evidence":["This wage target tracks logistics, warehousing, driving, routing, and material movement where automation can change task mix before full autonomy changes employment. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: damped_log_trend_v1({ soc_major_group: \"53-0000\", statistic: \"p90\", base_year: 2025, target_year: 2026 })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["This wage target tracks logistics, warehousing, driving, routing, and material movement where automation can change task mix before full autonomy changes employment. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","Tool call: bls.oews.api({ seriesId: \"OEUN000000000000053000015\", release: \"May 2025\", datatype: \"Annual 90th percentile wage\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · May 2026 OEWS first print","This wage target tracks logistics, warehousing, driving, routing, and material movement where automation can change task mix before full autonomy changes employment. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 7700, distribution present, forecast step count 1.","evidence":["This wage target tracks logistics, warehousing, driving, routing, and material movement where automation can change task mix before full autonomy changes employment. This target resolves on 2027-05-14 under a first-print rule, with an expected ~12 months lag. The same series can also spawn next annual release, mean wage, median wage, percentile wages, detailed SOC rows questions.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is driver and material-moving demand offset by warehouse automation and routing tools. The lower tail covers weaker goods movement volume and faster logistics automation."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: { base_p90_wage_2025_usd: 72440, model: 'damped_log_trend_v1', status: 'fallback', growth_prior: 'BLS CES total private average hourly earnings, May 2025 to May 2026', annualized_log_growth: '3.39%', occupation_signal: 'warehouse_routing_and_driver_wage_pressure' }","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is driver and material-moving demand offset by warehouse automation and routing tools. The lower tail covers weaker goods movement volume and faster logistics automation."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is driver and material-moving demand offset by warehouse automation and routing tools. The lower tail covers weaker goods movement volume and faster logistics automation."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Target registered in the Thesis ledger before forecasting; resolution uses the first-published BLS national OEWS annual 90th percentile wage field.","The forecast is produced by damped_log_trend_v1. The OEWS API returns one target-specific 90th percentile observation for this current SOC/statistic series, so the model records fallback status instead of fitting a false trend. It applies the broad wage-growth prior from BLS CES total private average hourly earnings, May 2025 to May 2026 and keeps a volatility-floor interval. The occupation-specific qualitative overlay is driver and material-moving demand offset by warehouse automation and routing tools. The lower tail covers weaker goods movement volume and faster logistics automation."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-transport-material-moving-90th-percentile-wage-may-2026\nrunLabel: Occupation wage pressure - no projection pack\nresolutionDate: 2027-05-14\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (3/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.oews-transport-material-moving-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.798e734fc311dca8","runId":"run.oews-transport-material-moving-90th-percentile-wage-may-2026.2026-05-15T10-00-00-04-00.may-2025-oews-carry-forward.798e734fc311dca8","predictionId":"oews-transport-material-moving-90th-percentile-wage-may-2026","specId":"spec.oews-transport-material-moving-90th-percentile-wage-may-2026","runLabel":"May 2025 OEWS carry-forward","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.81,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 1 historical point(s) and explicit outside-view language.","evidence":["Flat carry-forward baseline = $72,440."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged.","Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_53_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool call: bls.oews.api({ target: \"bls.oews.national_occupation_90th_percentile_annual_wage.soc_53_0000.may_2026.first_print\", comparator: \"latest_observed_a_pct90\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1000, distribution present, forecast step count 1.","evidence":["Forecast: point 72440, 80% interval [71940, 72940]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["BLS publishes current OEWS occupational wages but not an official May 2026 occupational wage projection. This comparator carries the May 2025 90th percentile annual wage forward unchanged."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 72440, 80% interval [71940, 72940]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: oews-transport-material-moving-90th-percentile-wage-may-2026\nrunLabel: May 2025 OEWS carry-forward\nresolutionDate: 2027-05-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-retail-sales-growth-april-2026.2026-06-06T14-42-00-02-00.a130b5ea020cf429","runId":"run.canada-retail-sales-growth-april-2026.2026-06-06T14-42-00-02-00.a130b5ea020cf429","predictionId":"canada-retail-sales-growth-april-2026","specId":"spec.canada-retail-sales-growth-april-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.46,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":["Retail sales are a fast official read on Canadian household demand, consumer credit stress, and sales-tax bases. This target resolves on 2026-06-19 under a first-print rule, with an expected ~3 weeks lag. The same series can also spawn next release, +3 months, GDP contribution questions."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 4 source-context item(s), activity log absent.","evidence":["Retail sales are a fast official read on Canadian household demand, consumer credit stress, and sales-tax bases. This target resolves on 2026-06-19 under a first-print rule, with an expected ~3 weeks lag. The same series can also spawn next release, +3 months, GDP contribution questions.","Tool call: statcan.lookup({ release: \"Retail trade\", series: \"seasonally_adjusted_retail_sales_mom\", months: [\"2026-02\", \"2026-03\"], advance_month: \"2026-04\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Retail sales are a fast official read on Canadian household demand, consumer credit stress, and sales-tax bases. This target resolves on 2026-06-19 under a first-print rule, with an expected ~3 weeks lag. The same series can also spawn next release, +3 months, GDP contribution questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.6, distribution present, forecast step count 1.","evidence":["Retail sales are a fast official read on Canadian household demand, consumer credit stress, and sales-tax bases. This target resolves on 2026-06-19 under a first-print rule, with an expected ~3 weeks lag. The same series can also spawn next release, +3 months, GDP contribution questions.","Tool call: statcan.lookup({ release: \"Retail trade\", series: \"seasonally_adjusted_retail_sales_mom\", months: [\"2026-02\", \"2026-03\"], advance_month: \"2026-04\" })"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The advance indicator points to a 0.6% April increase after March's 0.9% current-dollar gain. The interval allows the early estimate to revise because the advance response rate was well below the final survey response rate and March volume sales were weaker than nominal sales."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Retail sales are a fast official read on Canadian household demand, consumer credit stress, and sales-tax bases. This target resolves on 2026-06-19 under a first-print rule, with an expected ~3 weeks lag. The same series can also spawn next release, +3 months, GDP contribution questions."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The advance indicator points to a 0.6% April increase after March's 0.9% current-dollar gain. The interval allows the early estimate to revise because the advance response rate was well below the final survey response rate and March volume sales were weaker than nominal sales.","Forecast: point 0.6, 80% interval [-0.2, 1.4]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-retail-sales-growth-april-2026\nrunLabel: Headline\nresolutionDate: 2026-06-19\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-wholesale-sales-growth-april-2026.2026-06-06T14-42-00-02-00.413bad36afb920f7","runId":"run.canada-wholesale-sales-growth-april-2026.2026-06-06T14-42-00-02-00.413bad36afb920f7","predictionId":"canada-wholesale-sales-growth-april-2026","specId":"spec.canada-wholesale-sales-growth-april-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.22,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 4 source-context item(s), activity log absent.","evidence":["Wholesale trade is an early supply-chain and business-demand signal that feeds Canadian GDP by industry and inventory-cycle forecasts. This target resolves on 2026-06-15 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, +3 months, inventory ratio questions.","Tool call: statcan.lookup({ release: \"Wholesale trade\", series: \"sales_mom_ex_petroleum_oilseed_grain\", months: [\"2026-02\", \"2026-03\"], advance_month: \"2026-04\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Wholesale trade is an early supply-chain and business-demand signal that feeds Canadian GDP by industry and inventory-cycle forecasts. This target resolves on 2026-06-15 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, +3 months, inventory ratio questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.4, distribution present, forecast step count 1.","evidence":["The April advance indicator is barely positive at 0.1%, while February and March were both strong. The source synthesis keeps the point close to the advance value and widens the interval because advance wholesale indicators are explicitly subject to higher revision risk.","Forecast: point 0.2, 80% interval [-1, 1.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The April advance indicator is barely positive at 0.1%, while February and March were both strong. The source synthesis keeps the point close to the advance value and widens the interval because advance wholesale indicators are explicitly subject to higher revision risk."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["The April advance indicator is barely positive at 0.1%, while February and March were both strong. The source synthesis keeps the point close to the advance value and widens the interval because advance wholesale indicators are explicitly subject to higher revision risk."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Wholesale trade is an early supply-chain and business-demand signal that feeds Canadian GDP by industry and inventory-cycle forecasts. This target resolves on 2026-06-15 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, +3 months, inventory ratio questions.","The April advance indicator is barely positive at 0.1%, while February and March were both strong. The source synthesis keeps the point close to the advance value and widens the interval because advance wholesale indicators are explicitly subject to higher revision risk."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-wholesale-sales-growth-april-2026\nrunLabel: Headline\nresolutionDate: 2026-06-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-ei-regular-beneficiaries-april-2026.2026-06-06T14-42-00-02-00.c949828e7e5cdc48","runId":"run.canada-ei-regular-beneficiaries-april-2026.2026-06-06T14-42-00-02-00.c949828e7e5cdc48","predictionId":"canada-ei-regular-beneficiaries-april-2026","specId":"spec.canada-ei-regular-beneficiaries-april-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.08,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 4 source-context item(s), activity log absent.","evidence":["EI beneficiary counts are a direct administrative benefits-flow signal and a useful check on labour-market slack beyond the unemployment rate. This target resolves on 2026-06-18 under a first-print rule, with an expected ~3 weeks lag. The same series can also spawn next release, +3 months, unemployment linkage questions.","Tool call: statcan.lookup({ release: \"Employment Insurance\", series: \"regular_beneficiaries_thousands\", months: [\"2026-01\", \"2026-03\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","EI beneficiary counts are a direct administrative benefits-flow signal and a useful check on labour-market slack beyond the unemployment rate. This target resolves on 2026-06-18 under a first-print rule, with an expected ~3 weeks lag. The same series can also spawn next release, +3 months, unemployment linkage questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 34, distribution present, forecast step count 1.","evidence":["March EI beneficiaries edged up after February's decline, and the April unemployment rate rose to 6.9%. The central estimate nudges higher while keeping most uncertainty within the recent 542,000 to 569,000 range.","Forecast: point 552, 80% interval [536, 570]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["March EI beneficiaries edged up after February's decline, and the April unemployment rate rose to 6.9%. The central estimate nudges higher while keeping most uncertainty within the recent 542,000 to 569,000 range."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 552, 80% interval [536, 570]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-ei-regular-beneficiaries-april-2026\nrunLabel: Headline\nresolutionDate: 2026-06-18\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-ei-regular-beneficiaries-april-2026.2026-06-17T02-00-14Z.canada-ei-regular-beneficiaries-april-2026-thesis-analyst-fast-2026-06-17t02-00-14z.592df1265c4f19e6","runId":"run.canada-ei-regular-beneficiaries-april-2026.2026-06-17T02-00-14Z.canada-ei-regular-beneficiaries-april-2026-thesis-analyst-fast-2026-06-17t02-00-14z.592df1265c4f19e6","predictionId":"canada-ei-regular-beneficiaries-april-2026","specId":"spec.canada-ei-regular-beneficiaries-april-2026","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":["Base-rate/reference-class step: for a one-month-ahead EI beneficiary forecast, the best anchor is the latest official EI count plus recent monthly changes. The March count of 548000 followed +2300 in March and -8700 in February, while the broader labour market weakened in April rather than improved."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Tool result: The official schedule lists Employment Insurance, April 2026 on June 18, 2026, and says releases are published at 8:30 a.m. Eastern; the schedule was produced June 12, 2026.","Base-rate/reference-class step: for a one-month-ahead EI beneficiary forecast, the best anchor is the latest official EI count plus recent monthly changes. The March count of 548000 followed +2300 in March and -8700 in February, while the broader labour market weakened in April rather than improved."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the first Statistics Canada print for Canada, regular Employment Insurance beneficiaries, seasonally adjusted, April 2026. The resolving table is 14-10-0011-01, with The Daily notice/release as the release surface.","Tool call: Checked Statistics Canada upcoming release schedule for June 15 to 26, 2026."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 45, distribution present, forecast step count 1.","evidence":["Implied February count is 548000 - 2300 = 545700; implied January count is 545700 + 8700 = 554400. I start at 548000 and add roughly 8000 for April because unemployment rose by 51000 and the EI count usually moves less than one-for-one and with administrative lag. Point = 548000 + 8000 = 556000. An 80% interval of 535000 to 580000 covers a decline back below February through a return near the November 2025 peak of 569000 plus upside noise.","Forecast: point 556, 80% interval [535, 580]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Implied February count is 548000 - 2300 = 545700; implied January count is 545700 + 8700 = 554400. I start at 548000 and add roughly 8000 for April because unemployment rose by 51000 and the EI count usually moves less than one-for-one and with administrative lag. Point = 548000 + 8000 = 556000. An 80% interval of 535000 to 580000 covers a decline back below February through a return near the November 2025 peak of 569000 plus upside noise."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for Canada regular Employment Insurance beneficiaries in April 2026","Tool result: Employment was 21034000 in April 2026, down 0.1% or 18000; the unemployment rate was 6.9%, up 0.2 percentage points; unemployment increased by 51000 or 3.4%."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-ei-regular-beneficiaries-april-2026\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-06-18\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-building-permit-value-growth-april-2026.2026-06-06T14-42-00-02-00.6745e7df831e7e70","runId":"run.canada-building-permit-value-growth-april-2026.2026-06-06T14-42-00-02-00.6745e7df831e7e70","predictionId":"canada-building-permit-value-growth-april-2026","specId":"spec.canada-building-permit-value-growth-april-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":["Building permits are an early official signal for housing supply, non-residential investment, construction employment, and property-tax bases. This target resolves on 2026-06-11 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, +3 months, housing supply questions."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 4 source-context item(s), activity log absent.","evidence":["Building permits are an early official signal for housing supply, non-residential investment, construction employment, and property-tax bases. This target resolves on 2026-06-11 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, +3 months, housing supply questions.","Tool call: statcan.lookup({ release: \"Building permits\", series: \"total_value_mom\", months: [\"2026-02\", \"2026-03\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Building permits are an early official signal for housing supply, non-residential investment, construction employment, and property-tax bases. This target resolves on 2026-06-11 under a first-print rule, with an expected ~2 weeks lag. The same series can also spawn next release, +3 months, housing supply questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 29, distribution present, forecast step count 1.","evidence":["March's gain was concentrated in volatile non-residential permit values, while residential permits fell. The synthesis expects some mean reversion in April and assigns a wide interval because large projects can dominate the monthly first print.","Forecast: point -2, 80% interval [-16, 13]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["March's gain was concentrated in volatile non-residential permit values, while residential permits fell. The synthesis expects some mean reversion in April and assigns a wide interval because large projects can dominate the monthly first print."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["March's gain was concentrated in volatile non-residential permit values, while residential permits fell. The synthesis expects some mean reversion in April and assigns a wide interval because large projects can dominate the monthly first print.","Forecast: point -2, 80% interval [-16, 13]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-building-permit-value-growth-april-2026\nrunLabel: Headline\nresolutionDate: 2026-06-11\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.euro-area-industrial-production-growth-april-2026.2026-06-06T14-42-00-02-00.68380e4126f975e1","runId":"run.euro-area-industrial-production-growth-april-2026.2026-06-06T14-42-00-02-00.68380e4126f975e1","predictionId":"euro-area-industrial-production-growth-april-2026","specId":"spec.euro-area-industrial-production-growth-april-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.08,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 4 source-context item(s), activity log absent.","evidence":["Industrial production is a compact euro area output target that captures energy shocks, capital-goods demand, and manufacturing weakness. This target resolves on 2026-06-15 under a first-print rule, with an expected ~6 weeks lag. The same series can also spawn next release, +3 months, GDP contribution questions."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Industrial production is a compact euro area output target that captures energy shocks, capital-goods demand, and manufacturing weakness. This target resolves on 2026-06-15 under a first-print rule, with an expected ~6 weeks lag. The same series can also spawn next release, +3 months, GDP contribution questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.3, distribution present, forecast step count 1.","evidence":["Forecast: point 0, 80% interval [-1.1, 1.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Industrial production is a compact euro area output target that captures energy shocks, capital-goods demand, and manufacturing weakness. This target resolves on 2026-06-15 under a first-print rule, with an expected ~6 weeks lag. The same series can also spawn next release, +3 months, GDP contribution questions.","February and March were both mildly positive, but the annual rate remained negative and energy/non-durable components were weak. The forecast centers April near flat, with enough spread for country-level and energy-sector volatility."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["February and March were both mildly positive, but the annual rate remained negative and energy/non-durable components were weak. The forecast centers April near flat, with enough spread for country-level and energy-sector volatility.","Forecast: point 0, 80% interval [-1.1, 1.2]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: euro-area-industrial-production-growth-april-2026\nrunLabel: Headline\nresolutionDate: 2026-06-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.euro-area-retail-trade-volume-growth-may-2026.2026-06-06T14-42-00-02-00.987df99045d5dcd8","runId":"run.euro-area-retail-trade-volume-growth-may-2026.2026-06-06T14-42-00-02-00.987df99045d5dcd8","predictionId":"euro-area-retail-trade-volume-growth-may-2026","specId":"spec.euro-area-retail-trade-volume-growth-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.32,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 4 source-context item(s), activity log absent.","evidence":["Retail trade volume gives a fast official read on euro area household consumption while inflation and real-income pressure remain central to policy. This target resolves on 2026-07-06 under a first-print rule, with an expected ~1 month lag. The same series can also spawn next release, +3 months, household demand questions."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Retail trade volume gives a fast official read on euro area household consumption while inflation and real-income pressure remain central to policy. This target resolves on 2026-07-06 under a first-print rule, with an expected ~1 month lag. The same series can also spawn next release, +3 months, household demand questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.6, distribution present, forecast step count 1.","evidence":["Retail trade volume gives a fast official read on euro area household consumption while inflation and real-income pressure remain central to policy. This target resolves on 2026-07-06 under a first-print rule, with an expected ~1 month lag. The same series can also spawn next release, +3 months, household demand questions.","Tool call: eurostat.lookup({ release: \"Retail trade\", series: \"euro_area_volume_mom\", months: [\"2026-02\", \"2026-04\"] })"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Retail trade volume gives a fast official read on euro area household consumption while inflation and real-income pressure remain central to policy. This target resolves on 2026-07-06 under a first-print rule, with an expected ~1 month lag. The same series can also spawn next release, +3 months, household demand questions."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["April volume fell 0.4% after a smaller March decline, but the year-over-year rate remained positive. The synthesis expects a mild rebound or stabilization in May rather than a second large decline."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 0.1, 80% interval [-0.7, 0.9]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: euro-area-retail-trade-volume-growth-may-2026\nrunLabel: Headline\nresolutionDate: 2026-07-06\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.euro-area-retail-trade-volume-growth-may-2026.2026-06-17T02-13-28Z.euro-area-retail-trade-volume-growth-may-2026-thesis-analyst-fast-2026-06-17t02-13-28z.0d172093b6765fb2","runId":"run.euro-area-retail-trade-volume-growth-may-2026.2026-06-17T02-13-28Z.euro-area-retail-trade-volume-growth-may-2026-thesis-analyst-fast-2026-06-17t02-13-28z.0d172093b6765fb2","predictionId":"euro-area-retail-trade-volume-growth-may-2026","specId":"spec.euro-area-retail-trade-volume-growth-may-2026","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 3 historical point(s) and explicit outside-view language.","evidence":["Resolver is Eurostat's first official euro area print for calendar- and seasonally-adjusted retail trade volume, month-on-month, for May 2026. The target is the first published one-decimal percentage growth rate, not a later revised database value.","Base-rate/reference-class step: euro area retail trade month-on-month growth is usually centered near zero, with monthly prints commonly within roughly plus or minus 1 percentage point. The four recent observations average about +0.225%, but April's negative print lowers near-term momentum."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Resolver is Eurostat's first official euro area print for calendar- and seasonally-adjusted retail trade volume, month-on-month, for May 2026. The target is the first published one-decimal percentage growth rate, not a later revised database value.","Tool call: Checked recent Eurostat retail trade monthly pattern for additional reference observations."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Resolver is Eurostat's first official euro area print for calendar- and seasonally-adjusted retail trade volume, month-on-month, for May 2026. The target is the first published one-decimal percentage growth rate, not a later revised database value.","Tool call: Checked Eurostat euro-indicators release calendar/news surface for the retail trade May 2026 publication date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.7, distribution present, forecast step count 1.","evidence":["Forecast for euro area retail trade volume in May 2026","Resolver is Eurostat's first official euro area print for calendar- and seasonally-adjusted retail trade volume, month-on-month, for May 2026. The target is the first published one-decimal percentage growth rate, not a later revised database value."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base-rate/reference-class step: euro area retail trade month-on-month growth is usually centered near zero, with monthly prints commonly within roughly plus or minus 1 percentage point. The four recent observations average about +0.225%, but April's negative print lowers near-term momentum.","Counter-consideration: April's -0.4% could reverse if fuel and non-food categories normalize, but weak confidence and modest real-income momentum argue against treating the March +0.8% jump as persistent."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base-rate/reference-class step: euro area retail trade month-on-month growth is usually centered near zero, with monthly prints commonly within roughly plus or minus 1 percentage point. The four recent observations average about +0.225%, but April's negative print lowers near-term momentum.","Counter-consideration: April's -0.4% could reverse if fuel and non-food categories normalize, but weak confidence and modest real-income momentum argue against treating the March +0.8% jump as persistent."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for euro area retail trade volume in May 2026","Tool result: Eurostat release calendar places the May 2026 retail trade release on 2026-07-06; Eurostat euro-indicator releases are published at 11:00 CET and reported to 1 decimal percentage point."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: euro-area-retail-trade-volume-growth-may-2026\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-07-06\ntraceLineCount: 12\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-dwelling-approvals-growth-may-2026.2026-06-06T14-42-00-02-00.1fa2f73ddc6580b2","runId":"run.australia-dwelling-approvals-growth-may-2026.2026-06-06T14-42-00-02-00.1fa2f73ddc6580b2","predictionId":"australia-dwelling-approvals-growth-may-2026","specId":"spec.australia-dwelling-approvals-growth-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 4 source-context item(s), activity log absent.","evidence":["Dwelling approvals are a leading indicator for Australian housing supply, construction activity, and affordability pressure. This target resolves on 2026-07-01 under a first-print rule, with an expected ~1 month lag. The same series can also spawn next release, +3 months, housing supply questions."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Dwelling approvals are a leading indicator for Australian housing supply, construction activity, and affordability pressure. This target resolves on 2026-07-01 under a first-print rule, with an expected ~1 month lag. The same series can also spawn next release, +3 months, housing supply questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 30, distribution present, forecast step count 1.","evidence":["Approvals fell in March and April after a large February rise, with multi-unit approvals especially volatile. The forecast expects partial stabilization in May but keeps a wide interval because total dwelling approvals can swing sharply month to month.","Forecast: point 2, 80% interval [-12, 18]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Dwelling approvals are a leading indicator for Australian housing supply, construction activity, and affordability pressure. This target resolves on 2026-07-01 under a first-print rule, with an expected ~1 month lag. The same series can also spawn next release, +3 months, housing supply questions.","Approvals fell in March and April after a large February rise, with multi-unit approvals especially volatile. The forecast expects partial stabilization in May but keeps a wide interval because total dwelling approvals can swing sharply month to month."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Approvals fell in March and April after a large February rise, with multi-unit approvals especially volatile. The forecast expects partial stabilization in May but keeps a wide interval because total dwelling approvals can swing sharply month to month."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Approvals fell in March and April after a large February rise, with multi-unit approvals especially volatile. The forecast expects partial stabilization in May but keeps a wide interval because total dwelling approvals can swing sharply month to month.","Forecast: point 2, 80% interval [-12, 18]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-dwelling-approvals-growth-may-2026\nrunLabel: Headline\nresolutionDate: 2026-07-01\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-dwelling-approvals-growth-may-2026.2026-06-27T13-11-37Z.australia-dwelling-approvals-growth-may-2026-thesis-analyst-fast-2026-06-27t13-11-37z.b4d958b37a680b40","runId":"run.australia-dwelling-approvals-growth-may-2026.2026-06-27T13-11-37Z.australia-dwelling-approvals-growth-may-2026-thesis-analyst-fast-2026-06-27t13-11-37z.b4d958b37a680b40","predictionId":"australia-dwelling-approvals-growth-may-2026","specId":"spec.australia-dwelling-approvals-growth-may-2026","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 3 historical point(s) and explicit outside-view language.","evidence":["Base-rate/reference-class anchor: recent first prints show very high realized monthly dispersion, with January -7.2, February +29.7, March -10.5, and April -3.4. The central tendency is closer to low positive or flat than to the extreme February rebound.","Model prior: no formal time-series model was fit for this fast run; the prior is persistence around the recent trend level with uncertainty sized from recent first-print volatility, because monthly approvals are lumpy and the four-month reference sample is small."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Tool result: Fetched official schedule: Building Approvals, Australia, reference period May 2026, Wednesday 01 July 2026 at 11:30am AEST; updated information for the same May 2026 reference period is scheduled Wednesday 08 July 2026 at 11:30am AEST.","Mechanism split: detached houses were comparatively stable while multi-unit approvals drove the big 2026 swings. Policy pressure to lift housing supply is an upside force, but financing, construction costs, and project feasibility keep the near-term print noisy rather than persistently strong."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is the first ABS print for Building Approvals, Australia, May 2026: seasonally adjusted total dwelling units approved, monthly percent change. The July 8 updated-information item is excluded because the target is first print.","Tool call: ABS July 2026 future release calendar for Building Approvals, Australia May 2026"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 26, distribution present, forecast step count 1.","evidence":["Model prior: no formal time-series model was fit for this fast run; the prior is persistence around the recent trend level with uncertainty sized from recent first-print volatility, because monthly approvals are lumpy and the four-month reference sample is small.","Point: start from a flat-to-slightly-positive base rate near +0.5%, add about +2.0 percentage points for mean reversion from April being 3.8% below trend, subtract about -0.5 percentage points for weak March-April momentum, giving +2.0%. Interval: recent monthly changes span roughly -10.5% to +29.7%; for an 80% first-print interval, use about -12/+14 percentage points around the point despite the small four-month sample, skewed upward for apartment-project lumpiness, giving -10.0% to +16.0%."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The resolver is the first ABS print for Building Approvals, Australia, May 2026: seasonally adjusted total dwelling units approved, monthly percent change. The July 8 updated-information item is excluded because the target is first print.","Model prior: no formal time-series model was fit for this fast run; the prior is persistence around the recent trend level with uncertainty sized from recent first-print volatility, because monthly approvals are lumpy and the four-month reference sample is small."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Model prior: no formal time-series model was fit for this fast run; the prior is persistence around the recent trend level with uncertainty sized from recent first-print volatility, because monthly approvals are lumpy and the four-month reference sample is small.","Mechanism split: detached houses were comparatively stable while multi-unit approvals drove the big 2026 swings. Policy pressure to lift housing supply is an upside force, but financing, construction costs, and project feasibility keep the near-term print noisy rather than persistently strong."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast May 2026 ABS total dwelling approvals monthly change","Point: start from a flat-to-slightly-positive base rate near +0.5%, add about +2.0 percentage points for mean reversion from April being 3.8% below trend, subtract about -0.5 percentage points for weak March-April momentum, giving +2.0%. Interval: recent monthly changes span roughly -10.5% to +29.7%; for an 80% first-print interval, use about -12/+14 percentage points around the point despite the small four-month sample, skewed upward for apartment-project lumpiness, giving -10.0% to +16.0%."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-dwelling-approvals-growth-may-2026\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-07-01\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.japan-real-household-spending-growth-may-2026.2026-06-06T14-42-00-02-00.67483722e0444e3b","runId":"run.japan-real-household-spending-growth-may-2026.2026-06-06T14-42-00-02-00.67483722e0444e3b","predictionId":"japan-real-household-spending-growth-may-2026","specId":"spec.japan-real-household-spending-growth-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.32,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 4 source-context item(s), activity log absent.","evidence":["Japan household spending is a direct consumption target for whether wage gains are translating into real demand while food and import prices pressure households. This target resolves on 2026-07-07 under a first-print rule, with an expected ~1 month lag. The same series can also spawn next release, +3 months, consumption threshold questions.","Tool call: statjp.lookup({ release: \"Family Income and Expenditure Survey\", series: \"two_or_more_person_households_real_consumption_expenditure_yoy\", months: [\"2026-02\", \"2026-04\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Recorded agent run · next release","Japan household spending is a direct consumption target for whether wage gains are translating into real demand while food and import prices pressure households. This target resolves on 2026-07-07 under a first-print rule, with an expected ~1 month lag. The same series can also spawn next release, +3 months, consumption threshold questions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3.4, distribution present, forecast step count 1.","evidence":["Forecast: point -0.3, 80% interval [-2, 1.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Japan household spending is a direct consumption target for whether wage gains are translating into real demand while food and import prices pressure households. This target resolves on 2026-07-07 under a first-print rule, with an expected ~1 month lag. The same series can also spawn next release, +3 months, consumption threshold questions.","April real spending was still negative despite positive real income for workers' households. The synthesis predicts another slightly negative May print, with upside if wage gains finally lift consumption and downside if food and import-price pressure keep real spending weak."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point -0.3, 80% interval [-2, 1.4]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: japan-real-household-spending-growth-may-2026\nrunLabel: Headline\nresolutionDate: 2026-07-07\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.japan-real-household-spending-growth-may-2026.2026-06-27T13-19-13Z.japan-real-household-spending-growth-may-2026-thesis-analyst-fast-2026-06-27t13-19-13z.1fc5a6e21b190f18","runId":"run.japan-real-household-spending-growth-may-2026.2026-06-27T13-19-13Z.japan-real-household-spending-growth-may-2026-thesis-analyst-fast-2026-06-27t13-19-13z.1fc5a6e21b190f18","predictionId":"japan-real-household-spending-growth-may-2026","specId":"spec.japan-real-household-spending-growth-may-2026","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 3 historical point(s) and explicit outside-view language.","evidence":["Base-rate/reference-class anchor: the latest 12 official monthly first prints average about -0.2 percent, while the latest four average about -1.6 percent. No formal ARIMA, ETS, or regression model is used here; the prior is a transparent persistence and reference-class blend suited to an auditable fast public-release forecast.","Level and momentum effects point slightly negative: the January-April 2026 run is below zero, and May must compare against May 2025's high 4.7 percent print. That high base makes a positive May 2026 year-over-year result harder even if the month-to-month level is stable."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The resolver is the Statistics Bureau of Japan first preliminary monthly Family Income and Expenditure Survey print for consumption expenditures of two-or-more-person households, real year-over-year change, May 2026. The target field is the consumption expenditures, two-or-more-person households, real year-over-year percent-change line in the monthly preliminary report, reported to one decimal percent.","Tool call: Checked the Statistics Bureau of Japan household spending data page and current monthly preliminary report for the target series and recent official prints."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast for Japan May 2026 real household spending YoY first print","The resolver is the Statistics Bureau of Japan first preliminary monthly Family Income and Expenditure Survey print for consumption expenditures of two-or-more-person households, real year-over-year change, May 2026. The target field is the consumption expenditures, two-or-more-person households, real year-over-year percent-change line in the monthly preliminary report, reported to one decimal percent."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6.2, distribution present, forecast step count 1.","evidence":["Point calculation: 50 percent weight on the 12-month mean near -0.2 percent and 50 percent on the latest-four-month mean near -1.6 percent gives about -0.9 percent, then a roughly -0.2 point high-base adjustment for the 2025-May comparison gives -1.1 percent. The 12 cited prints have sample standard deviation about 2.5 percentage points and mean absolute deviation about 2.1 points, so an 80 percent central interval of roughly plus or minus 3 points is appropriate; I use -4.0 to 2.2 percent, slightly skewed downside because the base effect is adverse.","Upside outside-the-interval scenario: real wage gains and delayed services or durable-goods spending lift the first print above 2.2 percent. Downside outside-the-interval scenario: food and utility inflation plus the high May 2025 base push real spending below -4.0 percent. Central scenario: still-negative but less severe real spending, close to April's weakness."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level and momentum effects point slightly negative: the January-April 2026 run is below zero, and May must compare against May 2025's high 4.7 percent print. That high base makes a positive May 2026 year-over-year result harder even if the month-to-month level is stable.","Counter-consideration: April's improvement from -2.9 percent to -0.5 percent could mark a real turning point if wage settlements or durable-goods purchases pulled May up. Conversely, if the high May 2025 base and food-price pressure dominate, the print could fall below -4.0 percent."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Policy and one-off mechanisms are mixed. Wage gains and fiscal support can lift nominal outlays, but the target is real spending, so price levels subtract from the volume measure. Calendar, weather, and sample-composition noise can still produce a large positive or negative one-month print.","Upside outside-the-interval scenario: real wage gains and delayed services or durable-goods spending lift the first print above 2.2 percent. Downside outside-the-interval scenario: food and utility inflation plus the high May 2025 base push real spending below -4.0 percent. Central scenario: still-negative but less severe real spending, close to April's weakness."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for Japan May 2026 real household spending YoY first print","Base-rate/reference-class anchor: the latest 12 official monthly first prints average about -0.2 percent, while the latest four average about -1.6 percent. No formal ARIMA, ETS, or regression model is used here; the prior is a transparent persistence and reference-class blend suited to an auditable fast public-release forecast."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: japan-real-household-spending-growth-may-2026\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-07-07\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.individual-income-tax-refunds-fy2026.2026-06-08T00-00-00-02-00.5bf12ca5937f1413","runId":"run.individual-income-tax-refunds-fy2026.2026-06-08T00-00-00-02-00.5bf12ca5937f1413","predictionId":"individual-income-tax-refunds-fy2026","specId":"spec.individual-income-tax-refunds-fy2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.92,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 5 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 70, distribution present, forecast step count 1.","evidence":["The central estimate keeps refunds slightly below the FY2024 spike but above FY2025. The interval widens for filing-season timing because a few weeks of delayed refunds can move dollars across fiscal years without changing tax-year liability.","Forecast: point 486, 80% interval [455, 525]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 482, ci80: [454, 520], drivers: [\"ctc_refundability\", \"eitc_claiming\", \"withholding_gap\"] }","The central estimate keeps refunds slightly below the FY2024 spike but above FY2025. The interval widens for filing-season timing because a few weeks of delayed refunds can move dollars across fiscal years without changing tax-year liability."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["The central estimate keeps refunds slightly below the FY2024 spike but above FY2025. The interval widens for filing-season timing because a few weeks of delayed refunds can move dollars across fiscal years without changing tax-year liability."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 482, ci80: [454, 520], drivers: [\"ctc_refundability\", \"eitc_claiming\", \"withholding_gap\"] }","The central estimate keeps refunds slightly below the FY2024 spike but above FY2025. The interval widens for filing-season timing because a few weeks of delayed refunds can move dollars across fiscal years without changing tax-year liability."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: individual-income-tax-refunds-fy2026\nrunLabel: Headline\nresolutionDate: 2026-10-20\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.individual-income-tax-refunds-fy2026.2026-06-27T23-24-07Z.individual-income-tax-refunds-fy2026-thesis-analyst-fast-2026-06-27t23-24-07z.d4088ea3c2880a39","runId":"run.individual-income-tax-refunds-fy2026.2026-06-27T23-24-07Z.individual-income-tax-refunds-fy2026-thesis-analyst-fast-2026-06-27t23-24-07z.d4088ea3c2880a39","predictionId":"individual-income-tax-refunds-fy2026","specId":"spec.individual-income-tax-refunds-fy2026","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.43,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool call: Opened the FY2024 final September MTS PDF and read Table 4 Total -- Individual Income Taxes plus prior-period FY2023 context.","Tool result: Fetched FY2024 Table 4 Total -- Individual Income Taxes: gross receipts 2725.493 billion, refunds deducted 299.426 billion, and net receipts 2426.067 billion; the same table's prior FY2023 refunds were 373.321 billion."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["The resolver is the first final September 2026 Monthly Treasury Statement, not an IRS filing-season table. The target is Table 4 refunds deducted from Total -- Individual Income Taxes, current fiscal year to date, converted from millions to billions.","Tool call: Opened the Bureau of the Fiscal Service Monthly Treasury Statement page and previous-issues page for the official source family and table location."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The resolver is the first final September 2026 Monthly Treasury Statement, not an IRS filing-season table. The target is Table 4 refunds deducted from Total -- Individual Income Taxes, current fiscal year to date, converted from millions to billions.","Tool call: Checked the Fiscal Data release calendar page for the September 2026 MTS release schedule and the MTS publication timing note in official MTS PDFs."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 100, distribution present, forecast step count 1.","evidence":["Point calculation: start with FY2025 MTS Table 4 refunds of 327.268 billion and apply a small 4 percent uplift for nominal base growth and recent rebound persistence: 327.268 x 1.04 = 340.359 billion, rounded to 340 billion. Interval calibration: FY2021-FY2025 refunds had a sample standard deviation near 49 billion and year-over-year absolute changes averaged about 61 billion, so an 80 percent interval of roughly +/-45 to +/-55 billion around the point is appropriate; I use 295 to 395 billion, slightly narrower than raw one-year changes because the extreme FY2022-FY2023 swing was pandemic-era normalization.","Review disposition: accepted the critique that the draft's +10 percent uplift depended on uncited mid-2026 filing-season evidence, so the final forecast removes that as a quantified driver, lowers the point estimate, adds an explicit latest-year-persistence prior, and ties the interval to FY2021-FY2025 realized volatility. The official resolver and calendar treatment are retained with delayed-release clarification."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Simple model prior: use latest-year persistence as the main prior because this is an annual cash-accounting line with large timing noise and no stable five-year linear trend. A trailing-mean-only model would underweight the FY2024-FY2025 rebound, while extrapolating FY2023 would overfit a spike.","Judgmental update: move modestly above FY2025 rather than applying an unverified filing-season surge. The direction reflects continued nominal wage and withholding base growth plus normal refund-dollar drift; the size is restrained because MTS cash refunds can be moved by processing timing."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: Opened FY2022 and FY2021 final September MTS PDFs for older refund reference points.","Point calculation: start with FY2025 MTS Table 4 refunds of 327.268 billion and apply a small 4 percent uplift for nominal base growth and recent rebound persistence: 327.268 x 1.04 = 340.359 billion, rounded to 340 billion. Interval calibration: FY2021-FY2025 refunds had a sample standard deviation near 49 billion and year-over-year absolute changes averaged about 61 billion, so an 80 percent interval of roughly +/-45 to +/-55 billion around the point is appropriate; I use 295 to 395 billion, slightly narrower than raw one-year changes because the extreme FY2022-FY2023 swing was pandemic-era normalization."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: individual-income-tax-refunds-fy2026\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-10-20\ntraceLineCount: 19\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.net-premium-tax-credit-reconciliation-ty2025.2026-06-08T00-00-00-02-00.7a85696d87650632","runId":"run.net-premium-tax-credit-reconciliation-ty2025.2026-06-08T00-00-00-02-00.7a85696d87650632","predictionId":"net-premium-tax-credit-reconciliation-ty2025","specId":"spec.net-premium-tax-credit-reconciliation-ty2025","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.89,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.8, distribution present, forecast step count 1.","evidence":["The enhanced PTC schedule keeps enrollment high, but reconciliation depends on income surprises. The forecast centers near the model estimate and adds right-tail risk for larger-than-expected income gains among subsidized households.","Forecast: point 8.6, 80% interval [6.4, 11.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 8.4, ci80: [6.2, 10.9], drivers: [\"marketplace_growth\", \"income_reconciliation\", \"repayment_caps\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The enhanced PTC schedule keeps enrollment high, but reconciliation depends on income surprises. The forecast centers near the model estimate and adds right-tail risk for larger-than-expected income gains among subsidized households."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 8.4, ci80: [6.2, 10.9], drivers: [\"marketplace_growth\", \"income_reconciliation\", \"repayment_caps\"] }","The enhanced PTC schedule keeps enrollment high, but reconciliation depends on income surprises. The forecast centers near the model estimate and adds right-tail risk for larger-than-expected income gains among subsidized households."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: net-premium-tax-credit-reconciliation-ty2025\nrunLabel: Headline\nresolutionDate: 2027-08-31\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.savers-credit-claimant-returns-ty2025.2026-06-08T00-00-00-02-00.873057cb5c387134","runId":"run.savers-credit-claimant-returns-ty2025.2026-06-08T00-00-00-02-00.873057cb5c387134","predictionId":"savers-credit-claimant-returns-ty2025","specId":"spec.savers-credit-claimant-returns-ty2025","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.19,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 5 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: irs.soi.lookup({ table: \"line_item_estimates\", line: \"retirement_savings_contributions_credit\", metric: \"claimant_returns\", tax_years: [2020, 2024] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.3, distribution present, forecast step count 1.","evidence":["The forecast expects mild growth as real earnings stabilize and contribution rates recover, but it keeps the lower tail near the recent trough because the credit remains nonrefundable and low-salience.","Forecast: point 5.9, 80% interval [5.3, 6.6]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 5.9, ci80: [5.3, 6.5], drivers: [\"eligible_contributors\", \"tax_software_take_up\", \"income_thresholds\"] }","The forecast expects mild growth as real earnings stabilize and contribution rates recover, but it keeps the lower tail near the recent trough because the credit remains nonrefundable and low-salience."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The Saver's Credit is small in budget terms but useful for testing whether agents can forecast tax-credit take-up rather than only statutory eligibility.","Tool call: irs.soi.lookup({ table: \"line_item_estimates\", line: \"retirement_savings_contributions_credit\", metric: \"claimant_returns\", tax_years: [2020, 2024] })"]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The Saver's Credit is small in budget terms but useful for testing whether agents can forecast tax-credit take-up rather than only statutory eligibility.","Tool result: { point: 5.9, ci80: [5.3, 6.5], drivers: [\"eligible_contributors\", \"tax_software_take_up\", \"income_thresholds\"] }"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: savers-credit-claimant-returns-ty2025\nrunLabel: Headline\nresolutionDate: 2027-08-31\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-chip-enrollment-dec-2026.2026-06-08T00-00-00-02-00.bd5179611baf5b37","runId":"run.medicaid-chip-enrollment-dec-2026.2026-06-08T00-00-00-02-00.bd5179611baf5b37","predictionId":"medicaid-chip-enrollment-dec-2026","specId":"spec.medicaid-chip-enrollment-dec-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.95,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 5 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["This near-term enrollment cell gives Thesis Institute agents a clean administrative check on Medicaid participation before slower Census health-insurance outcomes resolve."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 8, distribution present, forecast step count 1.","evidence":["The forecast expects the unwinding decline to level off by late 2026. The upper tail reflects states improving renewal automation and the lower tail reflects continued procedural disenrollment.","Forecast: point 79.4, 80% interval [75.8, 83.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 79.1, ci80: [75.7, 83.3], drivers: [\"income_eligibility\", \"state_renewals\", \"take_up\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 79.1, ci80: [75.7, 83.3], drivers: [\"income_eligibility\", \"state_renewals\", \"take_up\"] }","The forecast expects the unwinding decline to level off by late 2026. The upper tail reflects states improving renewal automation and the lower tail reflects continued procedural disenrollment."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-chip-enrollment-dec-2026\nrunLabel: Headline\nresolutionDate: 2027-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.direct-purchase-health-coverage-rate-2025.2026-06-08T00-00-00-02-00.e9a32786fbfcabfd","runId":"run.direct-purchase-health-coverage-rate-2025.2026-06-08T00-00-00-02-00.e9a32786fbfcabfd","predictionId":"direct-purchase-health-coverage-rate-2025","specId":"spec.direct-purchase-health-coverage-rate-2025","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.95,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 5 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Census coverage target","Direct-purchase coverage is the Census-side counterpart to marketplace enrollment. It tests whether agents can reconcile administrative sign-ups with survey-reported insurance categories."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.5, distribution present, forecast step count 1.","evidence":["Forecast: point 10.6, 80% interval [9.9, 11.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The forecast holds the rate near 2023-2024 despite strong marketplace sign-ups because Census direct-purchase coverage includes classification noise and because some Medicaid transitions replace, rather than add, covered people."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Tool result: { high_marketplace_enrollment: true, offsetting_medicaid_transition: true }"]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The forecast holds the rate near 2023-2024 despite strong marketplace sign-ups because Census direct-purchase coverage includes classification noise and because some Medicaid transitions replace, rather than add, covered people.","Forecast: point 10.6, 80% interval [9.9, 11.4]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: direct-purchase-health-coverage-rate-2025\nrunLabel: Headline\nresolutionDate: 2026-09-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.direct-purchase-health-coverage-rate-2025.2026-06-27T13-46-36Z.direct-purchase-health-coverage-rate-2025-thesis-analyst-fast-2026-06-27t13-46-36z.ded5934301ab0c4e","runId":"run.direct-purchase-health-coverage-rate-2025.2026-06-27T13-46-36Z.direct-purchase-health-coverage-rate-2025-thesis-analyst-fast-2026-06-27t13-46-36z.ded5934301ab0c4e","predictionId":"direct-purchase-health-coverage-rate-2025","specId":"spec.direct-purchase-health-coverage-rate-2025","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool call: Checked Census 2025 press kit for the prior first-print release page and linked health insurance report/tables.","Tool call: Checked Census HHI historical tables page for the relevant CPS ASEC data source and time-series scope."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["The resolver is the U.S. Census Bureau CPS ASEC first print for calendar-year 2025 direct-purchase health insurance coverage among all persons, reported as a percent. This is an annual coverage-for-all-or-part-of-year concept, not an end-of-year enrollment count.","Tool call: Checked Census 2026 income, poverty, and health insurance schedule page for the official release date."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is the U.S. Census Bureau CPS ASEC first print for calendar-year 2025 direct-purchase health insurance coverage among all persons, reported as a percent. This is an annual coverage-for-all-or-part-of-year concept, not an end-of-year enrollment count.","Tool call: Checked Census 2026 income, poverty, and health insurance schedule page for the official release date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.2, distribution present, forecast step count 1.","evidence":["Base 2024 rate 10.8 + expected 2025 net increase 0.5 = 11.3. The 80 percent interval is judgmental rather than a clean long-history volatility estimate: recent annual changes of +0.3 and +0.6, survey/category noise, and policy churn support a +/-0.6 point band, giving 10.7 to 11.9.","Upside scenario: marketplace enrollment persistence and continued subsidy take-up push direct-purchase coverage above 11.9 percent. Downside scenario: churn, Medicaid/public coverage retention, or CPS classification effects keep the rate near 10.7 percent or below. Outside-interval downside would require little translation from the 24.3 million marketplace selections into annual CPS coverage."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level and momentum: the 2024 level already incorporated part of Medicaid unwinding and marketplace growth. Momentum into 2025 remains positive because marketplace selections rose again, but CPS annual coverage will translate enrollment into the all-person annual coverage category imperfectly.","Review disposition: accepted the resolver critique by grounding September 8, 2026 in the official Census 2026 schedule and distinguishing the timing URL from the HHI-01 resolving table; accepted the interval critique by labeling the +/-0.6 band as judgmental 80 percent uncertainty rather than a precise long-history volatility estimate; retained the central forecast because the source evidence and mechanism balance did not change."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level and momentum: the 2024 level already incorporated part of Medicaid unwinding and marketplace growth. Momentum into 2025 remains positive because marketplace selections rose again, but CPS annual coverage will translate enrollment into the all-person annual coverage category imperfectly.","One-off and policy mechanisms: enhanced ACA subsidies were still active for 2025 and should keep direct-purchase take-up elevated. Some Medicaid unwinding transition into marketplace coverage likely persists, but the largest unwinding shock was earlier, so I do not project another 0.6 point jump."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for 2025 CPS ASEC direct-purchase health insurance coverage","Base-rate/reference-class anchor: the recent CPS ASEC direct-purchase rate moved 9.9 to 10.2 to 10.8, a three-year level near 10.3 percent and recent annual changes of +0.3 and +0.6 percentage point. A neutral continuation anchor is roughly 11.1 percent before current-year policy adjustment."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: direct-purchase-health-coverage-rate-2025\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-09-15\ntraceLineCount: 20\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.marketplace-new-consumers-oep-2027.2026-06-08T00-00-00-02-00.c60287ac324a23e6","runId":"run.marketplace-new-consumers-oep-2027.2026-06-08T00-00-00-02-00.c60287ac324a23e6","predictionId":"marketplace-new-consumers-oep-2027","specId":"spec.marketplace-new-consumers-oep-2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.08,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["New-consumer target","Total Marketplace selections mix retention and acquisition. New consumers are the sharper calibration target for coverage-transition models because they reflect households entering or re-entering nongroup coverage."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2, distribution present, forecast step count 1.","evidence":["The central forecast declines from the unwinding-driven surge. It keeps a broad interval because subsidy policy and broker behavior can move new sign-ups quickly.","Forecast: point 3.2, 80% interval [2.4, 4.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Total Marketplace selections mix retention and acquisition. New consumers are the sharper calibration target for coverage-transition models because they reflect households entering or re-entering nongroup coverage.","Tool result: { point: 3.3, ci80: [2.4, 4.3], drivers: [\"subsidy_schedule\", \"medicaid_churn\", \"premium_growth\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Tool call: policyengine.simulate({ program: \"aca_marketplace\", plan_year: 2027, output: \"new_consumer_selections\", policy: \"enhanced_ptc_uncertain\" })"]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 3.3, ci80: [2.4, 4.3], drivers: [\"subsidy_schedule\", \"medicaid_churn\", \"premium_growth\"] }","The central forecast declines from the unwinding-driven surge. It keeps a broad interval because subsidy policy and broker behavior can move new sign-ups quickly."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: marketplace-new-consumers-oep-2027\nrunLabel: Headline\nresolutionDate: 2027-03-31\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.infant-mortality-rate-2026-current-law.2026-06-08T00-00-00-02-00.308596bb1a32ddfc","runId":"run.infant-mortality-rate-2026-current-law.2026-06-08T00-00-00-02-00.308596bb1a32ddfc","predictionId":"infant-mortality-rate-2026-current-law","specId":"spec.infant-mortality-rate-2026-current-law","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.41,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["This cell targets the final NCHS/NVSS linked birth/infant death rate: deaths under age 1 per 1,000 live births. The baseline scenario is current-law CTC policy, so a $3,000 fully refundable CTC would make this scenario unresolved rather than wrong.","Tool result: { median_change_vs_2025: \"small\", low_income_infant_household_cash_shock: \"none\", mortality_adjustment_per_1000: 0.00 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Official mortality target"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.38, distribution present, forecast step count 1.","evidence":["Forecast: point 5.5, 80% interval [5.34, 5.72]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The recent U.S. series has flattened after the 2022 increase. The forecast modestly improves from 2023-2024 but does not return to the 2020 low because preterm birth and maternal morbidity indicators remain elevated."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["The recent U.S. series has flattened after the 2022 increase. The forecast modestly improves from 2023-2024 but does not return to the 2020 low because preterm birth and maternal morbidity indicators remain elevated."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The recent U.S. series has flattened after the 2022 increase. The forecast modestly improves from 2023-2024 but does not return to the 2020 low because preterm birth and maternal morbidity indicators remain elevated.","Forecast: point 5.5, 80% interval [5.34, 5.72]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: infant-mortality-rate-2026-current-law\nrunLabel: Headline\nresolutionDate: 2028-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.infant-mortality-rate-2026-ctc-3000-refundable.2026-06-08T00-00-00-02-00.b26efb937fc52d96","runId":"run.infant-mortality-rate-2026-ctc-3000-refundable.2026-06-08T00-00-00-02-00.b26efb937fc52d96","predictionId":"infant-mortality-rate-2026-ctc-3000-refundable","specId":"spec.infant-mortality-rate-2026-ctc-3000-refundable","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 7 historical point(s) and explicit outside-view language.","evidence":["Baseline 5.50 minus central income-support effect 0.10 deaths per 1,000 = 5.40.","The CTC lowers the central estimate, but the interval overlaps the current-law baseline because the direct causal evidence for national infant mortality is much thinner than the evidence for low birth weight and maternal stress."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["This scenario asks about the observed national infant mortality rate if the $3,000 fully refundable CTC is actually in force for TY2026. The official NCHS rate still resolves the value; the condition determines whether this scenario is active."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["This scenario asks about the observed national infant mortality rate if the $3,000 fully refundable CTC is actually in force for TY2026. The official NCHS rate still resolves the value; the condition determines whether this scenario is active."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.5, distribution present, forecast step count 1.","evidence":["Tool result: { low_income_infant_household_mean_gain: 2450, broad_infant_household_mean_gain: 1320, takeup_risk: \"moderate\" }","The CTC lowers the central estimate, but the interval overlaps the current-law baseline because the direct causal evidence for national infant mortality is much thinner than the evidence for low birth weight and maternal stress."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The CTC lowers the central estimate, but the interval overlaps the current-law baseline because the direct causal evidence for national infant mortality is much thinner than the evidence for low birth weight and maternal stress."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool result: { low_income_infant_household_mean_gain: 2450, broad_infant_household_mean_gain: 1320, takeup_risk: \"moderate\" }","The CTC lowers the central estimate, but the interval overlaps the current-law baseline because the direct causal evidence for national infant mortality is much thinner than the evidence for low birth weight and maternal stress."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The CTC lowers the central estimate, but the interval overlaps the current-law baseline because the direct causal evidence for national infant mortality is much thinner than the evidence for low birth weight and maternal stress.","Forecast: point 5.4, 80% interval [5.16, 5.66]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: infant-mortality-rate-2026-ctc-3000-refundable\nrunLabel: Headline\nresolutionDate: 2028-12-15\ntraceLineCount: 9\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-cumulative-benefit-redemptions-fy2026.2026-06-08T00-00-00-02-00.8f089c8f29c15a69","runId":"run.snap-cumulative-benefit-redemptions-fy2026.2026-06-08T00-00-00-02-00.8f089c8f29c15a69","predictionId":"snap-cumulative-benefit-redemptions-fy2026","specId":"spec.snap-cumulative-benefit-redemptions-fy2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.35,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 5 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Redemptions are the administrative spending flow that reaches retailers and households. They give Thesis a near-term benefits target that can calibrate both eligibility and benefit-formula simulations.","Tool call: usda.fns.lookup({ program: \"snap\", table: \"national_level_annual_summary\", series: \"benefit_redemptions\", fiscal_years: [2021, 2025] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 19, distribution present, forecast step count 1.","evidence":["Redemptions are the administrative spending flow that reaches retailers and households. They give Thesis a near-term benefits target that can calibrate both eligibility and benefit-formula simulations.","Forecast: point 111.5, 80% interval [103, 122]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 110.8, ci80: [102.5, 121.0], drivers: [\"caseload\", \"net_income\", \"maximum_allotment\"] }","The central path rises from FY2024 after cost-of-food indexation and elevated caseload persistence, but it remains below the pandemic-era peak because emergency allotments have fully expired."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The central path rises from FY2024 after cost-of-food indexation and elevated caseload persistence, but it remains below the pandemic-era peak because emergency allotments have fully expired."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 110.8, ci80: [102.5, 121.0], drivers: [\"caseload\", \"net_income\", \"maximum_allotment\"] }","Forecast: point 111.5, 80% interval [103, 122]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-cumulative-benefit-redemptions-fy2026\nrunLabel: Headline\nresolutionDate: 2027-01-31\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: resolution clarity (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.wic-child-participation-fy2026.2026-06-08T00-00-00-02-00.4a3e91cb8d5d90bc","runId":"run.wic-child-participation-fy2026.2026-06-08T00-00-00-02-00.4a3e91cb8d5d90bc","predictionId":"wic-child-participation-fy2026","specId":"spec.wic-child-participation-fy2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.92,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 5 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.6, distribution present, forecast step count 1.","evidence":["The forecast keeps participation near the recent elevated level. The upper tail comes from improved retention technology; the lower tail comes from smaller birth cohorts feeding into the child category.","Forecast: point 3.9, 80% interval [3.6, 4.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Overall WIC participation mixes infants, children, and mothers. Child participation is the sharper target for family-resource forecasting because it connects to toddler nutrition support and certification churn.","Tool result: { point: 3.9, ci80: [3.6, 4.2], drivers: [\"eligible_children\", \"certification_retention\", \"state_outreach\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Overall WIC participation mixes infants, children, and mothers. Child participation is the sharper target for family-resource forecasting because it connects to toddler nutrition support and certification churn.","Tool result: { point: 3.9, ci80: [3.6, 4.2], drivers: [\"eligible_children\", \"certification_retention\", \"state_outreach\"] }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: wic-child-participation-fy2026\nrunLabel: Headline\nresolutionDate: 2027-01-31\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.ccdf-average-monthly-payment-per-child-fy2026.2026-06-08T00-00-00-02-00.673f1c221faadf67","runId":"run.ccdf-average-monthly-payment-per-child-fy2026.2026-06-08T00-00-00-02-00.673f1c221faadf67","predictionId":"ccdf-average-monthly-payment-per-child-fy2026","specId":"spec.ccdf-average-monthly-payment-per-child-fy2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 5 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 190, distribution present, forecast step count 1.","evidence":["Payment depth keeps rising with provider rates and child care prices, but the interval allows states to ration funds through lower reimbursement growth or narrower eligibility.","Forecast: point 690, 80% interval [610, 800]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool result: { point: 685, ci80: [610, 790], drivers: [\"state_reimbursement_rates\", \"infant_toddler_mix\", \"copayments\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Payment depth keeps rising with provider rates and child care prices, but the interval allows states to ration funds through lower reimbursement growth or narrower eligibility."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 685, ci80: [610, 790], drivers: [\"state_reimbursement_rates\", \"infant_toddler_mix\", \"copayments\"] }","Payment depth keeps rising with provider rates and child care prices, but the interval allows states to ration funds through lower reimbursement growth or narrower eligibility."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: ccdf-average-monthly-payment-per-child-fy2026\nrunLabel: Headline\nresolutionDate: 2027-12-31\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-payment-error-rate-fy2025.2026-06-08T00-00-00-02-00.238580636b1dcffe","runId":"run.snap-payment-error-rate-fy2025.2026-06-08T00-00-00-02-00.238580636b1dcffe","predictionId":"snap-payment-error-rate-fy2025","specId":"spec.snap-payment-error-rate-fy2025","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.08,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ source_record_id: \"fns.snap.total_payment_error_rate.us.fy2024.official_release\" })","Trend: 11.68 → 10.93 (−0.75pp). Cost-share incentive adds state-level downward pressure; QC arbitration disputes add first-print noise in both directions."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: ledger.lookup({ source_record_id: \"fns.snap.total_payment_error_rate.us.fy2024.official_release\" })","Trend: 11.68 → 10.93 (−0.75pp). Cost-share incentive adds state-level downward pressure; QC arbitration disputes add first-print noise in both directions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.9, distribution present, forecast step count 1.","evidence":["Continued decline is the modal path: the FY 2024 drop predates the strongest incentives, and several high-error states have already demonstrated large single-year improvements. The upper tail covers QC sampling noise and caseload churn; sub-9 would require improvement at a pace no recent year has shown.","Forecast: point 10.2, 80% interval [9.3, 11.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Trend: 11.68 → 10.93 (−0.75pp). Cost-share incentive adds state-level downward pressure; QC arbitration disputes add first-print noise in both directions."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 10.2, 80% interval [9.3, 11.2]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-payment-error-rate-fy2025\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.ca-medicaid-procedural-disenrollment-share-aug-2026.2026-06-08T00-00-00-02-00.bd71342506c2e55e","runId":"run.ca-medicaid-procedural-disenrollment-share-aug-2026.2026-06-08T00-00-00-02-00.bd71342506c2e55e","predictionId":"ca-medicaid-procedural-disenrollment-share-aug-2026","specId":"spec.ca-medicaid-procedural-disenrollment-share-aug-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.05,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ source_record_id: \"cms.medicaid_pi.beneficiaries_disenrolled_procedural.california.feb_2026.original_submission\" })","Tool call: ledger.lookup({ source_record_id: \"cms.medicaid_pi.beneficiaries_disenrolled_total.california.feb_2026.original_submission\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 7, distribution present, forecast step count 1.","evidence":["The mechanism is compositional: as ex parte automation renews the determinably eligible without paperwork, the people who still lose coverage are increasingly those who missed a form. That pushes the share toward an asymptote in the mid-90s. The downside tail covers notice reforms or an eligibility-policy change that grows the determined-ineligible denominator.","Forecast: point 93, 80% interval [88.5, 95.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 93, 80% interval [88.5, 95.5]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: ca-medicaid-procedural-disenrollment-share-aug-2026\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-ak.2026-06-08T00-00-00-02-00.02720faa98d39493","runId":"run.snap-error-rate-fy2025-ak.2026-06-08T00-00-00-02-00.02720faa98d39493","predictionId":"snap-error-rate-fy2025-ak","specId":"spec.snap-error-rate-fy2025-ak","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 14, distribution present, forecast step count 1.","evidence":["Damped trend: 24.66 + 0.25 x (-35.71) - 0.15 national-improvement drift = 15.6. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 24.66 + 0.25 x (-35.71) - 0.15 national-improvement drift = 15.6. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-ak\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-al.2026-06-08T00-00-00-02-00.f5ae7bb13b23ac75","runId":"run.snap-error-rate-fy2025-al.2026-06-08T00-00-00-02-00.f5ae7bb13b23ac75","predictionId":"snap-error-rate-fy2025-al","specId":"spec.snap-error-rate-fy2025-al","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3.2, distribution present, forecast step count 1.","evidence":["Damped trend: 8.32 + 0.25 x (1.25) - 0.15 national-improvement drift = 8.5. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 8.32 + 0.25 x (1.25) - 0.15 national-improvement drift = 8.5. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-al\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-ar.2026-06-08T00-00-00-02-00.4c995ab1d7ed0647","runId":"run.snap-error-rate-fy2025-ar.2026-06-08T00-00-00-02-00.4c995ab1d7ed0647","predictionId":"snap-error-rate-fy2025-ar","specId":"spec.snap-error-rate-fy2025-ar","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.6, distribution present, forecast step count 1.","evidence":["Damped trend: 9.56 + 0.25 x (-0.01) - 0.15 national-improvement drift = 9.4. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 9.56 + 0.25 x (-0.01) - 0.15 national-improvement drift = 9.4. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-ar\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-az.2026-06-08T00-00-00-02-00.2e1842e289830b59","runId":"run.snap-error-rate-fy2025-az.2026-06-08T00-00-00-02-00.2e1842e289830b59","predictionId":"snap-error-rate-fy2025-az","specId":"spec.snap-error-rate-fy2025-az","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.5, distribution present, forecast step count 1.","evidence":["Damped trend: 8.84 + 0.25 x (-2.55) - 0.15 national-improvement drift = 8.1. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 8.84 + 0.25 x (-2.55) - 0.15 national-improvement drift = 8.1. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-az\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-ca.2026-06-08T00-00-00-02-00.0e43fb023b6a8336","runId":"run.snap-error-rate-fy2025-ca.2026-06-08T00-00-00-02-00.0e43fb023b6a8336","predictionId":"snap-error-rate-fy2025-ca","specId":"spec.snap-error-rate-fy2025-ca","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.4, distribution present, forecast step count 1.","evidence":["Damped trend: 10.98 + 0.25 x (-2.42) - 0.15 national-improvement drift = 10.2. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 10.98 + 0.25 x (-2.42) - 0.15 national-improvement drift = 10.2. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-ca\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-co.2026-06-08T00-00-00-02-00.b4c594211fafa9b2","runId":"run.snap-error-rate-fy2025-co.2026-06-08T00-00-00-02-00.b4c594211fafa9b2","predictionId":"snap-error-rate-fy2025-co","specId":"spec.snap-error-rate-fy2025-co","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3.3, distribution present, forecast step count 1.","evidence":["Damped trend: 9.97 + 0.25 x (1.36) - 0.15 national-improvement drift = 10.2. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 9.97 + 0.25 x (1.36) - 0.15 national-improvement drift = 10.2. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-co\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-ct.2026-06-08T00-00-00-02-00.a0a431780e6f4a3e","runId":"run.snap-error-rate-fy2025-ct.2026-06-08T00-00-00-02-00.a0a431780e6f4a3e","predictionId":"snap-error-rate-fy2025-ct","specId":"spec.snap-error-rate-fy2025-ct","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3.3, distribution present, forecast step count 1.","evidence":["Damped trend: 10.25 + 0.25 x (1.34) - 0.15 national-improvement drift = 10.4. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 10.25 + 0.25 x (1.34) - 0.15 national-improvement drift = 10.4. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-ct\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-dc.2026-06-08T00-00-00-02-00.2fe792c6e309002f","runId":"run.snap-error-rate-fy2025-dc.2026-06-08T00-00-00-02-00.2fe792c6e309002f","predictionId":"snap-error-rate-fy2025-dc","specId":"spec.snap-error-rate-fy2025-dc","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.8, distribution present, forecast step count 1.","evidence":["Damped trend: 17.38 + 0.25 x (-2.88) - 0.15 national-improvement drift = 16.5. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 17.38 + 0.25 x (-2.88) - 0.15 national-improvement drift = 16.5. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-dc\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-de.2026-06-08T00-00-00-02-00.5821f58c09a10fc8","runId":"run.snap-error-rate-fy2025-de.2026-06-08T00-00-00-02-00.5821f58c09a10fc8","predictionId":"snap-error-rate-fy2025-de","specId":"spec.snap-error-rate-fy2025-de","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 12.4, distribution present, forecast step count 1.","evidence":["Damped trend: 12.37 + 0.25 x (-10.43) - 0.15 national-improvement drift = 9.6. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 12.37 + 0.25 x (-10.43) - 0.15 national-improvement drift = 9.6. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-de\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-fl.2026-06-08T00-00-00-02-00.e890859f49ef52fa","runId":"run.snap-error-rate-fy2025-fl.2026-06-08T00-00-00-02-00.e890859f49ef52fa","predictionId":"snap-error-rate-fy2025-fl","specId":"spec.snap-error-rate-fy2025-fl","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.6, distribution present, forecast step count 1.","evidence":["Damped trend: 15.13 + 0.25 x (2.53) - 0.15 national-improvement drift = 15.6. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 15.13 + 0.25 x (2.53) - 0.15 national-improvement drift = 15.6. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-fl\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-ga.2026-06-08T00-00-00-02-00.4484478908582d44","runId":"run.snap-error-rate-fy2025-ga.2026-06-08T00-00-00-02-00.4484478908582d44","predictionId":"snap-error-rate-fy2025-ga","specId":"spec.snap-error-rate-fy2025-ga","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5.6, distribution present, forecast step count 1.","evidence":["Damped trend: 15.65 + 0.25 x (3.58) - 0.15 national-improvement drift = 16.4. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 15.65 + 0.25 x (3.58) - 0.15 national-improvement drift = 16.4. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-ga\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-gu.2026-06-08T00-00-00-02-00.c73ca61c7d65bb0b","runId":"run.snap-error-rate-fy2025-gu.2026-06-08T00-00-00-02-00.c73ca61c7d65bb0b","predictionId":"snap-error-rate-fy2025-gu","specId":"spec.snap-error-rate-fy2025-gu","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 10.2, distribution present, forecast step count 1.","evidence":["Damped trend: 9.72 + 0.25 x (-8.29) - 0.15 national-improvement drift = 7.5. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 9.72 + 0.25 x (-8.29) - 0.15 national-improvement drift = 7.5. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-gu\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-hi.2026-06-08T00-00-00-02-00.ba6524666c0b65e4","runId":"run.snap-error-rate-fy2025-hi.2026-06-08T00-00-00-02-00.ba6524666c0b65e4","predictionId":"snap-error-rate-fy2025-hi","specId":"spec.snap-error-rate-fy2025-hi","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 9.7, distribution present, forecast step count 1.","evidence":["Damped trend: 6.68 + 0.25 x (-14.26) - 0.15 national-improvement drift = 3.0. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 6.68 + 0.25 x (-14.26) - 0.15 national-improvement drift = 3.0. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-hi\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-ia.2026-06-08T00-00-00-02-00.93ea8b2d0b7944de","runId":"run.snap-error-rate-fy2025-ia.2026-06-08T00-00-00-02-00.93ea8b2d0b7944de","predictionId":"snap-error-rate-fy2025-ia","specId":"spec.snap-error-rate-fy2025-ia","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.9, distribution present, forecast step count 1.","evidence":["Damped trend: 6.14 + 0.25 x (0.95) - 0.15 national-improvement drift = 6.2. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 6.14 + 0.25 x (0.95) - 0.15 national-improvement drift = 6.2. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-ia\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-id.2026-06-08T00-00-00-02-00.e046d6f06ebfe1dd","runId":"run.snap-error-rate-fy2025-id.2026-06-08T00-00-00-02-00.e046d6f06ebfe1dd","predictionId":"snap-error-rate-fy2025-id","specId":"spec.snap-error-rate-fy2025-id","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.6, distribution present, forecast step count 1.","evidence":["Damped trend: 3.59 + 0.25 x (0.17) - 0.15 national-improvement drift = 3.5. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 3.59 + 0.25 x (0.17) - 0.15 national-improvement drift = 3.5. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-id\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-il.2026-06-08T00-00-00-02-00.5491db6762a2a75e","runId":"run.snap-error-rate-fy2025-il.2026-06-08T00-00-00-02-00.5491db6762a2a75e","predictionId":"snap-error-rate-fy2025-il","specId":"spec.snap-error-rate-fy2025-il","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3.6, distribution present, forecast step count 1.","evidence":["Damped trend: 11.56 + 0.25 x (1.65) - 0.15 national-improvement drift = 11.8. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 11.56 + 0.25 x (1.65) - 0.15 national-improvement drift = 11.8. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-il\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-in.2026-06-08T00-00-00-02-00.087d61536a4a3012","runId":"run.snap-error-rate-fy2025-in.2026-06-08T00-00-00-02-00.087d61536a4a3012","predictionId":"snap-error-rate-fy2025-in","specId":"spec.snap-error-rate-fy2025-in","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.9, distribution present, forecast step count 1.","evidence":["Damped trend: 9.52 + 0.25 x (-0.94) - 0.15 national-improvement drift = 9.1. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 9.52 + 0.25 x (-0.94) - 0.15 national-improvement drift = 9.1. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-in\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-ks.2026-06-08T00-00-00-02-00.e94df1680c459eac","runId":"run.snap-error-rate-fy2025-ks.2026-06-08T00-00-00-02-00.e94df1680c459eac","predictionId":"snap-error-rate-fy2025-ks","specId":"spec.snap-error-rate-fy2025-ks","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.1, distribution present, forecast step count 1.","evidence":["Damped trend: 9.98 + 0.25 x (-2.09) - 0.15 national-improvement drift = 9.3. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 9.98 + 0.25 x (-2.09) - 0.15 national-improvement drift = 9.3. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-ks\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-ky.2026-06-08T00-00-00-02-00.12f126f325cb1690","runId":"run.snap-error-rate-fy2025-ky.2026-06-08T00-00-00-02-00.12f126f325cb1690","predictionId":"snap-error-rate-fy2025-ky","specId":"spec.snap-error-rate-fy2025-ky","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3.8, distribution present, forecast step count 1.","evidence":["Damped trend: 9.11 + 0.25 x (1.84) - 0.15 national-improvement drift = 9.4. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 9.11 + 0.25 x (1.84) - 0.15 national-improvement drift = 9.4. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-ky\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-la.2026-06-08T00-00-00-02-00.ccc2fc189aae86db","runId":"run.snap-error-rate-fy2025-la.2026-06-08T00-00-00-02-00.ccc2fc189aae86db","predictionId":"snap-error-rate-fy2025-la","specId":"spec.snap-error-rate-fy2025-la","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.6, distribution present, forecast step count 1.","evidence":["Damped trend: 6.62 + 0.25 x (-0.03) - 0.15 national-improvement drift = 6.5. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 6.62 + 0.25 x (-0.03) - 0.15 national-improvement drift = 6.5. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-la\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-ma.2026-06-08T00-00-00-02-00.93ba825b31b2c662","runId":"run.snap-error-rate-fy2025-ma.2026-06-08T00-00-00-02-00.93ba825b31b2c662","predictionId":"snap-error-rate-fy2025-ma","specId":"spec.snap-error-rate-fy2025-ma","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6.2, distribution present, forecast step count 1.","evidence":["Damped trend: 14.10 + 0.25 x (4.24) - 0.15 national-improvement drift = 15.0. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 14.10 + 0.25 x (4.24) - 0.15 national-improvement drift = 15.0. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-ma\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-md.2026-06-08T00-00-00-02-00.563e1f6db43f4f53","runId":"run.snap-error-rate-fy2025-md.2026-06-08T00-00-00-02-00.563e1f6db43f4f53","predictionId":"snap-error-rate-fy2025-md","specId":"spec.snap-error-rate-fy2025-md","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 7.3, distribution present, forecast step count 1.","evidence":["Damped trend: 13.64 + 0.25 x (-5.34) - 0.15 national-improvement drift = 12.2. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 13.64 + 0.25 x (-5.34) - 0.15 national-improvement drift = 12.2. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-md\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-me.2026-06-08T00-00-00-02-00.e356ddd1d8b4f97d","runId":"run.snap-error-rate-fy2025-me.2026-06-08T00-00-00-02-00.e356ddd1d8b4f97d","predictionId":"snap-error-rate-fy2025-me","specId":"spec.snap-error-rate-fy2025-me","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5.2, distribution present, forecast step count 1.","evidence":["Damped trend: 10.26 + 0.25 x (-3.22) - 0.15 national-improvement drift = 9.3. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 10.26 + 0.25 x (-3.22) - 0.15 national-improvement drift = 9.3. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-me\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-mi.2026-06-08T00-00-00-02-00.1d1d9e74a5de28c2","runId":"run.snap-error-rate-fy2025-mi.2026-06-08T00-00-00-02-00.1d1d9e74a5de28c2","predictionId":"snap-error-rate-fy2025-mi","specId":"spec.snap-error-rate-fy2025-mi","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3.2, distribution present, forecast step count 1.","evidence":["Damped trend: 9.53 + 0.25 x (-1.19) - 0.15 national-improvement drift = 9.1. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 9.53 + 0.25 x (-1.19) - 0.15 national-improvement drift = 9.1. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-mi\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-mn.2026-06-08T00-00-00-02-00.67eae07d0223267b","runId":"run.snap-error-rate-fy2025-mn.2026-06-08T00-00-00-02-00.67eae07d0223267b","predictionId":"snap-error-rate-fy2025-mn","specId":"spec.snap-error-rate-fy2025-mn","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.6, distribution present, forecast step count 1.","evidence":["Damped trend: 8.98 + 0.25 x (2.58) - 0.15 national-improvement drift = 9.5. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 8.98 + 0.25 x (2.58) - 0.15 national-improvement drift = 9.5. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-mn\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-mo.2026-06-08T00-00-00-02-00.63355d1deb4f2062","runId":"run.snap-error-rate-fy2025-mo.2026-06-08T00-00-00-02-00.63355d1deb4f2062","predictionId":"snap-error-rate-fy2025-mo","specId":"spec.snap-error-rate-fy2025-mo","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3.2, distribution present, forecast step count 1.","evidence":["Damped trend: 9.42 + 0.25 x (-1.12) - 0.15 national-improvement drift = 9.0. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 9.42 + 0.25 x (-1.12) - 0.15 national-improvement drift = 9.0. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-mo\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-ms.2026-06-08T00-00-00-02-00.dfb57f0430d9abd7","runId":"run.snap-error-rate-fy2025-ms.2026-06-08T00-00-00-02-00.dfb57f0430d9abd7","predictionId":"snap-error-rate-fy2025-ms","specId":"spec.snap-error-rate-fy2025-ms","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.6, distribution present, forecast step count 1.","evidence":["Damped trend: 10.69 + 0.25 x (0.54) - 0.15 national-improvement drift = 10.7. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 10.69 + 0.25 x (0.54) - 0.15 national-improvement drift = 10.7. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-ms\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-mt.2026-06-08T00-00-00-02-00.4813aa73ca0434d6","runId":"run.snap-error-rate-fy2025-mt.2026-06-08T00-00-00-02-00.4813aa73ca0434d6","predictionId":"snap-error-rate-fy2025-mt","specId":"spec.snap-error-rate-fy2025-mt","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.9, distribution present, forecast step count 1.","evidence":["Damped trend: 8.89 + 0.25 x (2.85) - 0.15 national-improvement drift = 9.5. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 8.89 + 0.25 x (2.85) - 0.15 national-improvement drift = 9.5. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-mt\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-nc.2026-06-08T00-00-00-02-00.840f957a1f472ba6","runId":"run.snap-error-rate-fy2025-nc.2026-06-08T00-00-00-02-00.840f957a1f472ba6","predictionId":"snap-error-rate-fy2025-nc","specId":"spec.snap-error-rate-fy2025-nc","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.6, distribution present, forecast step count 1.","evidence":["Damped trend: 10.21 + 0.25 x (0.49) - 0.15 national-improvement drift = 10.2. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 10.21 + 0.25 x (0.49) - 0.15 national-improvement drift = 10.2. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-nc\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-nd.2026-06-08T00-00-00-02-00.ad948d87d93ab3cf","runId":"run.snap-error-rate-fy2025-nd.2026-06-08T00-00-00-02-00.ad948d87d93ab3cf","predictionId":"snap-error-rate-fy2025-nd","specId":"spec.snap-error-rate-fy2025-nd","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3.6, distribution present, forecast step count 1.","evidence":["Damped trend: 7.91 + 0.25 x (-1.60) - 0.15 national-improvement drift = 7.4. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 7.91 + 0.25 x (-1.60) - 0.15 national-improvement drift = 7.4. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-nd\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-ne.2026-06-08T00-00-00-02-00.ebdc6813c208bcb5","runId":"run.snap-error-rate-fy2025-ne.2026-06-08T00-00-00-02-00.ebdc6813c208bcb5","predictionId":"snap-error-rate-fy2025-ne","specId":"spec.snap-error-rate-fy2025-ne","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3.5, distribution present, forecast step count 1.","evidence":["Damped trend: 5.50 + 0.25 x (-1.56) - 0.15 national-improvement drift = 5.0. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 5.50 + 0.25 x (-1.56) - 0.15 national-improvement drift = 5.0. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-ne\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-nh.2026-06-08T00-00-00-02-00.47d8f33c06a29b91","runId":"run.snap-error-rate-fy2025-nh.2026-06-08T00-00-00-02-00.47d8f33c06a29b91","predictionId":"snap-error-rate-fy2025-nh","specId":"spec.snap-error-rate-fy2025-nh","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 7, distribution present, forecast step count 1.","evidence":["Damped trend: 7.57 + 0.25 x (-4.96) - 0.15 national-improvement drift = 6.2. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 7.57 + 0.25 x (-4.96) - 0.15 national-improvement drift = 6.2. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-nh\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-nj.2026-06-08T00-00-00-02-00.3f61b575310b8b77","runId":"run.snap-error-rate-fy2025-nj.2026-06-08T00-00-00-02-00.3f61b575310b8b77","predictionId":"snap-error-rate-fy2025-nj","specId":"spec.snap-error-rate-fy2025-nj","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 14, distribution present, forecast step count 1.","evidence":["Damped trend: 14.33 + 0.25 x (-21.37) - 0.15 national-improvement drift = 8.8. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 14.33 + 0.25 x (-21.37) - 0.15 national-improvement drift = 8.8. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-nj\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-nm.2026-06-08T00-00-00-02-00.fcbddbf27fdd5991","runId":"run.snap-error-rate-fy2025-nm.2026-06-08T00-00-00-02-00.fcbddbf27fdd5991","predictionId":"snap-error-rate-fy2025-nm","specId":"spec.snap-error-rate-fy2025-nm","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.6, distribution present, forecast step count 1.","evidence":["Damped trend: 14.61 + 0.25 x (0.21) - 0.15 national-improvement drift = 14.5. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 14.61 + 0.25 x (0.21) - 0.15 national-improvement drift = 14.5. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-nm\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-nv.2026-06-08T00-00-00-02-00.7e05cf6ac0f3bf7b","runId":"run.snap-error-rate-fy2025-nv.2026-06-08T00-00-00-02-00.7e05cf6ac0f3bf7b","predictionId":"snap-error-rate-fy2025-nv","specId":"spec.snap-error-rate-fy2025-nv","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.8, distribution present, forecast step count 1.","evidence":["Damped trend: 5.94 + 0.25 x (-0.77) - 0.15 national-improvement drift = 5.6. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 5.94 + 0.25 x (-0.77) - 0.15 national-improvement drift = 5.6. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-nv\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-ny.2026-06-08T00-00-00-02-00.e76f93776d78ed48","runId":"run.snap-error-rate-fy2025-ny.2026-06-08T00-00-00-02-00.e76f93776d78ed48","predictionId":"snap-error-rate-fy2025-ny","specId":"spec.snap-error-rate-fy2025-ny","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3.4, distribution present, forecast step count 1.","evidence":["Damped trend: 14.09 + 0.25 x (1.41) - 0.15 national-improvement drift = 14.3. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 14.09 + 0.25 x (1.41) - 0.15 national-improvement drift = 14.3. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-ny\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-oh.2026-06-08T00-00-00-02-00.e0b769aa1ffb0a61","runId":"run.snap-error-rate-fy2025-oh.2026-06-08T00-00-00-02-00.e0b769aa1ffb0a61","predictionId":"snap-error-rate-fy2025-oh","specId":"spec.snap-error-rate-fy2025-oh","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Damped trend: 9.01 + 0.25 x (2.00) - 0.15 national-improvement drift = 9.4. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 9.01 + 0.25 x (2.00) - 0.15 national-improvement drift = 9.4. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-oh\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-ok.2026-06-08T00-00-00-02-00.a0ec44e796a97693","runId":"run.snap-error-rate-fy2025-ok.2026-06-08T00-00-00-02-00.a0ec44e796a97693","predictionId":"snap-error-rate-fy2025-ok","specId":"spec.snap-error-rate-fy2025-ok","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.6, distribution present, forecast step count 1.","evidence":["Damped trend: 10.87 + 0.25 x (0.23) - 0.15 national-improvement drift = 10.8. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 10.87 + 0.25 x (0.23) - 0.15 national-improvement drift = 10.8. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-ok\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-or.2026-06-08T00-00-00-02-00.4a0855fae49e4a51","runId":"run.snap-error-rate-fy2025-or.2026-06-08T00-00-00-02-00.4a0855fae49e4a51","predictionId":"snap-error-rate-fy2025-or","specId":"spec.snap-error-rate-fy2025-or","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.7, distribution present, forecast step count 1.","evidence":["Damped trend: 14.06 + 0.25 x (-2.70) - 0.15 national-improvement drift = 13.2. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 14.06 + 0.25 x (-2.70) - 0.15 national-improvement drift = 13.2. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-or\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-pa.2026-06-08T00-00-00-02-00.de9e22ceaa7f98ee","runId":"run.snap-error-rate-fy2025-pa.2026-06-08T00-00-00-02-00.de9e22ceaa7f98ee","predictionId":"snap-error-rate-fy2025-pa","specId":"spec.snap-error-rate-fy2025-pa","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 7.9, distribution present, forecast step count 1.","evidence":["Damped trend: 10.76 + 0.25 x (-5.85) - 0.15 national-improvement drift = 9.1. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 10.76 + 0.25 x (-5.85) - 0.15 national-improvement drift = 9.1. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-pa\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-ri.2026-06-08T00-00-00-02-00.65c8d3979e0e8b48","runId":"run.snap-error-rate-fy2025-ri.2026-06-08T00-00-00-02-00.65c8d3979e0e8b48","predictionId":"snap-error-rate-fy2025-ri","specId":"spec.snap-error-rate-fy2025-ri","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.6, distribution present, forecast step count 1.","evidence":["Damped trend: 12.29 + 0.25 x (-0.11) - 0.15 national-improvement drift = 12.1. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 12.29 + 0.25 x (-0.11) - 0.15 national-improvement drift = 12.1. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-ri\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-sc.2026-06-08T00-00-00-02-00.1bc43780e827eb5c","runId":"run.snap-error-rate-fy2025-sc.2026-06-08T00-00-00-02-00.1bc43780e827eb5c","predictionId":"snap-error-rate-fy2025-sc","specId":"spec.snap-error-rate-fy2025-sc","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 12.5, distribution present, forecast step count 1.","evidence":["Damped trend: 9.25 + 0.25 x (-13.32) - 0.15 national-improvement drift = 5.8. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 9.25 + 0.25 x (-13.32) - 0.15 national-improvement drift = 5.8. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-sc\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-sd.2026-06-08T00-00-00-02-00.f102e0746bdf96b8","runId":"run.snap-error-rate-fy2025-sd.2026-06-08T00-00-00-02-00.f102e0746bdf96b8","predictionId":"snap-error-rate-fy2025-sd","specId":"spec.snap-error-rate-fy2025-sd","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.6, distribution present, forecast step count 1.","evidence":["Damped trend: 3.28 + 0.25 x (0.01) - 0.15 national-improvement drift = 3.1. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 3.28 + 0.25 x (0.01) - 0.15 national-improvement drift = 3.1. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-sd\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-tn.2026-06-08T00-00-00-02-00.c4bc344d75562984","runId":"run.snap-error-rate-fy2025-tn.2026-06-08T00-00-00-02-00.c4bc344d75562984","predictionId":"snap-error-rate-fy2025-tn","specId":"spec.snap-error-rate-fy2025-tn","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5.1, distribution present, forecast step count 1.","evidence":["Damped trend: 9.47 + 0.25 x (-3.09) - 0.15 national-improvement drift = 8.5. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 9.47 + 0.25 x (-3.09) - 0.15 national-improvement drift = 8.5. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-tn\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-tx.2026-06-08T00-00-00-02-00.b16b0e8ec12af773","runId":"run.snap-error-rate-fy2025-tx.2026-06-08T00-00-00-02-00.b16b0e8ec12af773","predictionId":"snap-error-rate-fy2025-tx","specId":"spec.snap-error-rate-fy2025-tx","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3.6, distribution present, forecast step count 1.","evidence":["Damped trend: 8.32 + 0.25 x (1.62) - 0.15 national-improvement drift = 8.6. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 8.32 + 0.25 x (1.62) - 0.15 national-improvement drift = 8.6. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-tx\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-ut.2026-06-08T00-00-00-02-00.110e3bfa1ccd7529","runId":"run.snap-error-rate-fy2025-ut.2026-06-08T00-00-00-02-00.110e3bfa1ccd7529","predictionId":"snap-error-rate-fy2025-ut","specId":"spec.snap-error-rate-fy2025-ut","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.7, distribution present, forecast step count 1.","evidence":["Damped trend: 5.74 + 0.25 x (0.65) - 0.15 national-improvement drift = 5.8. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 5.74 + 0.25 x (0.65) - 0.15 national-improvement drift = 5.8. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-ut\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-va.2026-06-08T00-00-00-02-00.1c8d70963f39ca34","runId":"run.snap-error-rate-fy2025-va.2026-06-08T00-00-00-02-00.1c8d70963f39ca34","predictionId":"snap-error-rate-fy2025-va","specId":"spec.snap-error-rate-fy2025-va","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3.7, distribution present, forecast step count 1.","evidence":["Damped trend: 11.50 + 0.25 x (1.64) - 0.15 national-improvement drift = 11.8. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 11.50 + 0.25 x (1.64) - 0.15 national-improvement drift = 11.8. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-va\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-vi.2026-06-08T00-00-00-02-00.0f6e2d0f970d9102","runId":"run.snap-error-rate-fy2025-vi.2026-06-08T00-00-00-02-00.0f6e2d0f970d9102","predictionId":"snap-error-rate-fy2025-vi","specId":"spec.snap-error-rate-fy2025-vi","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5.8, distribution present, forecast step count 1.","evidence":["Damped trend: 3.54 + 0.25 x (-6.75) - 0.15 national-improvement drift = 1.7. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 3.54 + 0.25 x (-6.75) - 0.15 national-improvement drift = 1.7. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-vi\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-vt.2026-06-08T00-00-00-02-00.b57b63822dff0c21","runId":"run.snap-error-rate-fy2025-vt.2026-06-08T00-00-00-02-00.b57b63822dff0c21","predictionId":"snap-error-rate-fy2025-vt","specId":"spec.snap-error-rate-fy2025-vt","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3.6, distribution present, forecast step count 1.","evidence":["Damped trend: 5.13 + 0.25 x (1.68) - 0.15 national-improvement drift = 5.4. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 5.13 + 0.25 x (1.68) - 0.15 national-improvement drift = 5.4. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-vt\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-wa.2026-06-08T00-00-00-02-00.9adeab8dea6900ab","runId":"run.snap-error-rate-fy2025-wa.2026-06-08T00-00-00-02-00.9adeab8dea6900ab","predictionId":"snap-error-rate-fy2025-wa","specId":"spec.snap-error-rate-fy2025-wa","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.7, distribution present, forecast step count 1.","evidence":["Damped trend: 6.06 + 0.25 x (-0.68) - 0.15 national-improvement drift = 5.7. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 6.06 + 0.25 x (-0.68) - 0.15 national-improvement drift = 5.7. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-wa\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-wi.2026-06-08T00-00-00-02-00.3923b932f4d20d44","runId":"run.snap-error-rate-fy2025-wi.2026-06-08T00-00-00-02-00.3923b932f4d20d44","predictionId":"snap-error-rate-fy2025-wi","specId":"spec.snap-error-rate-fy2025-wi","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.84,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Wisconsin's payment error rate improved from 5.15% in FY 2023 to 4.47% in FY 2024. Under the 2025 reconciliation law, future state cost sharing keys off payment error rates, so every state QC office now has direct budget exposure to this number."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.7, distribution present, forecast step count 1.","evidence":["Damped trend: 4.47 + 0.25 x (-0.68) - 0.15 national-improvement drift = 4.1. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 4.47 + 0.25 x (-0.68) - 0.15 national-improvement drift = 4.1. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-wi\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-wv.2026-06-08T00-00-00-02-00.c201d4d54884ddc2","runId":"run.snap-error-rate-fy2025-wv.2026-06-08T00-00-00-02-00.c201d4d54884ddc2","predictionId":"snap-error-rate-fy2025-wv","specId":"spec.snap-error-rate-fy2025-wv","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3.6, distribution present, forecast step count 1.","evidence":["Damped trend: 9.43 + 0.25 x (-1.55) - 0.15 national-improvement drift = 8.9. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 9.43 + 0.25 x (-1.55) - 0.15 national-improvement drift = 8.9. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-wv\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2025-wy.2026-06-08T00-00-00-02-00.42401fe4dcbbe084","runId":"run.snap-error-rate-fy2025-wy.2026-06-08T00-00-00-02-00.42401fe4dcbbe084","predictionId":"snap-error-rate-fy2025-wy","specId":"spec.snap-error-rate-fy2025-wy","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.6, distribution present, forecast step count 1.","evidence":["Damped trend: 5.12 + 0.25 x (-0.07) - 0.15 national-improvement drift = 5.0. Interval width scales with the state's year-over-year volatility.","Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Persistence dominates one-year state error rates, with partial continuation of the recent trend and modest downward pressure from cost-share incentives. The interval covers QC sampling noise, arbitration, and caseload shifts."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Damped trend: 5.12 + 0.25 x (-0.07) - 0.15 national-improvement drift = 5.0. Interval width scales with the state's year-over-year volatility.","Forecast"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2025-wy\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-ak.2026-06-08T00-00-00-02-00.299a7dbc403c5db8","runId":"run.snap-apt-fy2025-ak.2026-06-08T00-00-00-02-00.299a7dbc403c5db8","predictionId":"snap-apt-fy2025-ak","specId":"spec.snap-apt-fy2025-ak","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Alaska processed 57.93% of SNAP applications on time in FY 2024, versus 38.98% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 18, distribution present, forecast step count 1.","evidence":["Forecast: point 64, 80% interval [55, 73]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 64, 80% interval [55, 73]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-ak\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-al.2026-06-08T00-00-00-02-00.35e2e8e59e9ebc2c","runId":"run.snap-apt-fy2025-al.2026-06-08T00-00-00-02-00.35e2e8e59e9ebc2c","predictionId":"snap-apt-fy2025-al","specId":"spec.snap-apt-fy2025-al","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Alabama processed 93.02% of SNAP applications on time in FY 2024, versus 94.30% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5.1, distribution present, forecast step count 1.","evidence":["Forecast: point 93, 80% interval [90.5, 95.6]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 93, 80% interval [90.5, 95.6]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-al\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-ar.2026-06-08T00-00-00-02-00.e7cbe8e9e4a827ae","runId":"run.snap-apt-fy2025-ar.2026-06-08T00-00-00-02-00.e7cbe8e9e4a827ae","predictionId":"snap-apt-fy2025-ar","specId":"spec.snap-apt-fy2025-ar","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Arkansas processed 61.94% of SNAP applications on time in FY 2024, versus 67.38% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 10.2, distribution present, forecast step count 1.","evidence":["Forecast: point 60.7, 80% interval [55.6, 65.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 60.7, 80% interval [55.6, 65.8]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-ar\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-az.2026-06-08T00-00-00-02-00.b212a49e14186f60","runId":"run.snap-apt-fy2025-az.2026-06-08T00-00-00-02-00.b212a49e14186f60","predictionId":"snap-apt-fy2025-az","specId":"spec.snap-apt-fy2025-az","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Arizona processed 90.29% of SNAP applications on time in FY 2024, versus 91.47% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5, distribution present, forecast step count 1.","evidence":["Forecast: point 90.3, 80% interval [87.8, 92.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 90.3, 80% interval [87.8, 92.8]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-az\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-ca.2026-06-08T00-00-00-02-00.9e983d692fcb6d2a","runId":"run.snap-apt-fy2025-ca.2026-06-08T00-00-00-02-00.9e983d692fcb6d2a","predictionId":"snap-apt-fy2025-ca","specId":"spec.snap-apt-fy2025-ca","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["California processed 80.21% of SNAP applications on time in FY 2024, versus 82.07% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5.9, distribution present, forecast step count 1.","evidence":["Forecast: point 80.1, 80% interval [77.1, 83]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 80.1, 80% interval [77.1, 83]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-ca\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-co.2026-06-08T00-00-00-02-00.87135768fdb49bc5","runId":"run.snap-apt-fy2025-co.2026-06-08T00-00-00-02-00.87135768fdb49bc5","predictionId":"snap-apt-fy2025-co","specId":"spec.snap-apt-fy2025-co","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Colorado processed 66.87% of SNAP applications on time in FY 2024, versus 74.91% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 13.3, distribution present, forecast step count 1.","evidence":["Forecast: point 64.9, 80% interval [58.2, 71.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 64.9, 80% interval [58.2, 71.5]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-co\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-ct.2026-06-08T00-00-00-02-00.c136dce06a4975ec","runId":"run.snap-apt-fy2025-ct.2026-06-08T00-00-00-02-00.c136dce06a4975ec","predictionId":"snap-apt-fy2025-ct","specId":"spec.snap-apt-fy2025-ct","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Connecticut processed 89.11% of SNAP applications on time in FY 2024, versus 93.81% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 9.2, distribution present, forecast step count 1.","evidence":["Forecast: point 88.1, 80% interval [83.5, 92.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 88.1, 80% interval [83.5, 92.7]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-ct\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-dc.2026-06-08T00-00-00-02-00.16d85919e6786855","runId":"run.snap-apt-fy2025-dc.2026-06-08T00-00-00-02-00.16d85919e6786855","predictionId":"snap-apt-fy2025-dc","specId":"spec.snap-apt-fy2025-dc","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["District of Columbia processed 56.73% of SNAP applications on time in FY 2024, versus 48.13% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 13.9, distribution present, forecast step count 1.","evidence":["Forecast: point 59.7, 80% interval [52.8, 66.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 59.7, 80% interval [52.8, 66.7]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-dc\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-de.2026-06-08T00-00-00-02-00.e5eca165f62b1918","runId":"run.snap-apt-fy2025-de.2026-06-08T00-00-00-02-00.e5eca165f62b1918","predictionId":"snap-apt-fy2025-de","specId":"spec.snap-apt-fy2025-de","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Delaware processed 75.08% of SNAP applications on time in FY 2024, versus 89.72% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 18, distribution present, forecast step count 1.","evidence":["Forecast: point 71.1, 80% interval [62.1, 80.1]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 71.1, 80% interval [62.1, 80.1]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-de\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-fl.2026-06-08T00-00-00-02-00.60ec6a4851a76ef2","runId":"run.snap-apt-fy2025-fl.2026-06-08T00-00-00-02-00.60ec6a4851a76ef2","predictionId":"snap-apt-fy2025-fl","specId":"spec.snap-apt-fy2025-fl","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Florida processed 63.31% of SNAP applications on time in FY 2024, versus 64.38% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.9, distribution present, forecast step count 1.","evidence":["Forecast: point 63.4, 80% interval [60.9, 65.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 63.4, 80% interval [60.9, 65.8]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-fl\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-ga.2026-06-08T00-00-00-02-00.ede1008dd8944be9","runId":"run.snap-apt-fy2025-ga.2026-06-08T00-00-00-02-00.ede1008dd8944be9","predictionId":"snap-apt-fy2025-ga","specId":"spec.snap-apt-fy2025-ga","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Georgia processed 67.22% of SNAP applications on time in FY 2024, versus 78.09% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 16.7, distribution present, forecast step count 1.","evidence":["Forecast: point 64.4, 80% interval [56, 72.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 64.4, 80% interval [56, 72.7]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-ga\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-gu.2026-06-08T00-00-00-02-00.dfa8436d72ffd90d","runId":"run.snap-apt-fy2025-gu.2026-06-08T00-00-00-02-00.dfa8436d72ffd90d","predictionId":"snap-apt-fy2025-gu","specId":"spec.snap-apt-fy2025-gu","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Guam processed 50.86% of SNAP applications on time in FY 2024, versus 61.27% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 16.1, distribution present, forecast step count 1.","evidence":["Forecast: point 48.1, 80% interval [40.1, 56.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 48.1, 80% interval [40.1, 56.2]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-gu\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-hi.2026-06-08T00-00-00-02-00.994db34afa651465","runId":"run.snap-apt-fy2025-hi.2026-06-08T00-00-00-02-00.994db34afa651465","predictionId":"snap-apt-fy2025-hi","specId":"spec.snap-apt-fy2025-hi","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Hawaii processed 68.87% of SNAP applications on time in FY 2024, versus 75.35% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 11.4, distribution present, forecast step count 1.","evidence":["Forecast: point 67.3, 80% interval [61.6, 73]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 67.3, 80% interval [61.6, 73]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-hi\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-ia.2026-06-08T00-00-00-02-00.bca8767ad88deae5","runId":"run.snap-apt-fy2025-ia.2026-06-08T00-00-00-02-00.bca8767ad88deae5","predictionId":"snap-apt-fy2025-ia","specId":"spec.snap-apt-fy2025-ia","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Iowa processed 64.66% of SNAP applications on time in FY 2024, versus 77.73% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 18, distribution present, forecast step count 1.","evidence":["Forecast: point 61.1, 80% interval [52.1, 70.1]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 61.1, 80% interval [52.1, 70.1]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-ia\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-id.2026-06-08T00-00-00-02-00.8010a3edfb3108c6","runId":"run.snap-apt-fy2025-id.2026-06-08T00-00-00-02-00.8010a3edfb3108c6","predictionId":"snap-apt-fy2025-id","specId":"spec.snap-apt-fy2025-id","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Idaho processed 91.02% of SNAP applications on time in FY 2024, versus 98.15% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 12.2, distribution present, forecast step count 1.","evidence":["Forecast: point 89.3, 80% interval [83.2, 95.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 89.3, 80% interval [83.2, 95.4]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-id\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-il.2026-06-08T00-00-00-02-00.b46d4df5820ed715","runId":"run.snap-apt-fy2025-il.2026-06-08T00-00-00-02-00.b46d4df5820ed715","predictionId":"snap-apt-fy2025-il","specId":"spec.snap-apt-fy2025-il","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Illinois processed 93.56% of SNAP applications on time in FY 2024, versus 95.85% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6.3, distribution present, forecast step count 1.","evidence":["Forecast: point 93.3, 80% interval [90.1, 96.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 93.3, 80% interval [90.1, 96.4]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-il\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-in.2026-06-08T00-00-00-02-00.171d4a3c4711fd7d","runId":"run.snap-apt-fy2025-in.2026-06-08T00-00-00-02-00.171d4a3c4711fd7d","predictionId":"snap-apt-fy2025-in","specId":"spec.snap-apt-fy2025-in","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Indiana processed 80.04% of SNAP applications on time in FY 2024, versus 78.17% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5.8, distribution present, forecast step count 1.","evidence":["Forecast: point 81, 80% interval [78.1, 83.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 81, 80% interval [78.1, 83.9]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-in\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-ks.2026-06-08T00-00-00-02-00.1c53b4ac8c4dca02","runId":"run.snap-apt-fy2025-ks.2026-06-08T00-00-00-02-00.1c53b4ac8c4dca02","predictionId":"snap-apt-fy2025-ks","specId":"spec.snap-apt-fy2025-ks","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Kansas processed 81.99% of SNAP applications on time in FY 2024, versus 81.28% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.4, distribution present, forecast step count 1.","evidence":["Forecast: point 82.6, 80% interval [80.4, 84.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 82.6, 80% interval [80.4, 84.8]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-ks\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-ky.2026-06-08T00-00-00-02-00.44b8ff541fe9beb9","runId":"run.snap-apt-fy2025-ky.2026-06-08T00-00-00-02-00.44b8ff541fe9beb9","predictionId":"snap-apt-fy2025-ky","specId":"spec.snap-apt-fy2025-ky","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Kentucky processed 87.38% of SNAP applications on time in FY 2024, versus 76.14% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 16.9, distribution present, forecast step count 1.","evidence":["Forecast: point 91.2, 80% interval [82.6, 99.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 91.2, 80% interval [82.6, 99.5]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-ky\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-la.2026-06-08T00-00-00-02-00.12ff810f9b3ca7c6","runId":"run.snap-apt-fy2025-la.2026-06-08T00-00-00-02-00.12ff810f9b3ca7c6","predictionId":"snap-apt-fy2025-la","specId":"spec.snap-apt-fy2025-la","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Louisiana processed 87.08% of SNAP applications on time in FY 2024, versus 94.12% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 12.1, distribution present, forecast step count 1.","evidence":["Forecast: point 85.4, 80% interval [79.3, 91.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 85.4, 80% interval [79.3, 91.4]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-la\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-ma.2026-06-08T00-00-00-02-00.b3225c51bd9cba76","runId":"run.snap-apt-fy2025-ma.2026-06-08T00-00-00-02-00.b3225c51bd9cba76","predictionId":"snap-apt-fy2025-ma","specId":"spec.snap-apt-fy2025-ma","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Massachusetts processed 85.45% of SNAP applications on time in FY 2024, versus 85.91% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.4, distribution present, forecast step count 1.","evidence":["Forecast: point 85.7, 80% interval [83.5, 87.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 85.7, 80% interval [83.5, 87.9]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-ma\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-md.2026-06-08T00-00-00-02-00.863bf2dcc0c5399c","runId":"run.snap-apt-fy2025-md.2026-06-08T00-00-00-02-00.863bf2dcc0c5399c","predictionId":"snap-apt-fy2025-md","specId":"spec.snap-apt-fy2025-md","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Maryland processed 91.04% of SNAP applications on time in FY 2024, versus 84.80% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 11.1, distribution present, forecast step count 1.","evidence":["Forecast: point 93.3, 80% interval [87.8, 98.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 93.3, 80% interval [87.8, 98.9]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-md\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-me.2026-06-08T00-00-00-02-00.bbd41230c4c3905e","runId":"run.snap-apt-fy2025-me.2026-06-08T00-00-00-02-00.bbd41230c4c3905e","predictionId":"snap-apt-fy2025-me","specId":"spec.snap-apt-fy2025-me","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Maine processed 64.93% of SNAP applications on time in FY 2024, versus 88.89% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 18, distribution present, forecast step count 1.","evidence":["Forecast: point 58.1, 80% interval [49.1, 67.1]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 58.1, 80% interval [49.1, 67.1]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-me\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-mi.2026-06-08T00-00-00-02-00.ad463c2d5a692838","runId":"run.snap-apt-fy2025-mi.2026-06-08T00-00-00-02-00.ad463c2d5a692838","predictionId":"snap-apt-fy2025-mi","specId":"spec.snap-apt-fy2025-mi","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Michigan processed 76.05% of SNAP applications on time in FY 2024, versus 77.66% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5.5, distribution present, forecast step count 1.","evidence":["Forecast: point 76, 80% interval [73.2, 78.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 76, 80% interval [73.2, 78.7]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-mi\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-mn.2026-06-08T00-00-00-02-00.b95e59778fd4cc88","runId":"run.snap-apt-fy2025-mn.2026-06-08T00-00-00-02-00.b95e59778fd4cc88","predictionId":"snap-apt-fy2025-mn","specId":"spec.snap-apt-fy2025-mn","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Minnesota processed 80.37% of SNAP applications on time in FY 2024, versus 85.89% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 10.2, distribution present, forecast step count 1.","evidence":["Forecast: point 79.1, 80% interval [74, 84.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 79.1, 80% interval [74, 84.2]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-mn\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-mo.2026-06-08T00-00-00-02-00.fd06c661719bcf19","runId":"run.snap-apt-fy2025-mo.2026-06-08T00-00-00-02-00.fd06c661719bcf19","predictionId":"snap-apt-fy2025-mo","specId":"spec.snap-apt-fy2025-mo","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Missouri processed 78.28% of SNAP applications on time in FY 2024, versus 85.32% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 12.1, distribution present, forecast step count 1.","evidence":["Forecast: point 76.6, 80% interval [70.5, 82.6]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 76.6, 80% interval [70.5, 82.6]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-mo\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-ms.2026-06-08T00-00-00-02-00.c62c1c09cc5061f1","runId":"run.snap-apt-fy2025-ms.2026-06-08T00-00-00-02-00.c62c1c09cc5061f1","predictionId":"snap-apt-fy2025-ms","specId":"spec.snap-apt-fy2025-ms","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Mississippi processed 79.38% of SNAP applications on time in FY 2024, versus 83.25% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 8.2, distribution present, forecast step count 1.","evidence":["Forecast: point 78.6, 80% interval [74.5, 82.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 78.6, 80% interval [74.5, 82.7]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-ms\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-mt.2026-06-08T00-00-00-02-00.482ea2f3f416174a","runId":"run.snap-apt-fy2025-mt.2026-06-08T00-00-00-02-00.482ea2f3f416174a","predictionId":"snap-apt-fy2025-mt","specId":"spec.snap-apt-fy2025-mt","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Montana processed 66.88% of SNAP applications on time in FY 2024, versus 74.76% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 13, distribution present, forecast step count 1.","evidence":["Forecast: point 64.9, 80% interval [58.4, 71.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 64.9, 80% interval [58.4, 71.4]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-mt\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-nc.2026-06-08T00-00-00-02-00.1b5c38fa31ce6d8e","runId":"run.snap-apt-fy2025-nc.2026-06-08T00-00-00-02-00.1b5c38fa31ce6d8e","predictionId":"snap-apt-fy2025-nc","specId":"spec.snap-apt-fy2025-nc","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["North Carolina processed 84.40% of SNAP applications on time in FY 2024, versus 91.98% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 12.7, distribution present, forecast step count 1.","evidence":["Forecast: point 82.5, 80% interval [76.2, 88.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 82.5, 80% interval [76.2, 88.9]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-nc\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-nd.2026-06-08T00-00-00-02-00.749e32039e45b786","runId":"run.snap-apt-fy2025-nd.2026-06-08T00-00-00-02-00.749e32039e45b786","predictionId":"snap-apt-fy2025-nd","specId":"spec.snap-apt-fy2025-nd","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["North Dakota processed 57.02% of SNAP applications on time in FY 2024, versus 52.94% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 8.5, distribution present, forecast step count 1.","evidence":["Forecast: point 58.6, 80% interval [54.4, 62.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 58.6, 80% interval [54.4, 62.9]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-nd\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-ne.2026-06-08T00-00-00-02-00.ca4ba3286f1c9028","runId":"run.snap-apt-fy2025-ne.2026-06-08T00-00-00-02-00.ca4ba3286f1c9028","predictionId":"snap-apt-fy2025-ne","specId":"spec.snap-apt-fy2025-ne","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Nebraska processed 88.96% of SNAP applications on time in FY 2024, versus 91.20% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6.3, distribution present, forecast step count 1.","evidence":["Forecast: point 88.7, 80% interval [85.5, 91.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 88.7, 80% interval [85.5, 91.8]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-ne\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-nh.2026-06-08T00-00-00-02-00.347795eb6bd778b9","runId":"run.snap-apt-fy2025-nh.2026-06-08T00-00-00-02-00.347795eb6bd778b9","predictionId":"snap-apt-fy2025-nh","specId":"spec.snap-apt-fy2025-nh","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["New Hampshire processed 89.32% of SNAP applications on time in FY 2024, versus 91.67% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6.4, distribution present, forecast step count 1.","evidence":["Forecast: point 89, 80% interval [85.8, 92.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 89, 80% interval [85.8, 92.2]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-nh\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-nj.2026-06-08T00-00-00-02-00.67fb0b1404a1192c","runId":"run.snap-apt-fy2025-nj.2026-06-08T00-00-00-02-00.67fb0b1404a1192c","predictionId":"snap-apt-fy2025-nj","specId":"spec.snap-apt-fy2025-nj","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["New Jersey processed 77.61% of SNAP applications on time in FY 2024, versus 82.08% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 9, distribution present, forecast step count 1.","evidence":["Forecast: point 76.7, 80% interval [72.2, 81.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 76.7, 80% interval [72.2, 81.2]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-nj\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-nm.2026-06-08T00-00-00-02-00.32d21f7e0753bfd4","runId":"run.snap-apt-fy2025-nm.2026-06-08T00-00-00-02-00.32d21f7e0753bfd4","predictionId":"snap-apt-fy2025-nm","specId":"spec.snap-apt-fy2025-nm","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["New Mexico processed 52.36% of SNAP applications on time in FY 2024, versus 66.34% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 18, distribution present, forecast step count 1.","evidence":["Forecast: point 48.6, 80% interval [39.6, 57.6]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 48.6, 80% interval [39.6, 57.6]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-nm\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-nv.2026-06-08T00-00-00-02-00.6507c5c3481121aa","runId":"run.snap-apt-fy2025-nv.2026-06-08T00-00-00-02-00.6507c5c3481121aa","predictionId":"snap-apt-fy2025-nv","specId":"spec.snap-apt-fy2025-nv","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Nevada processed 93.09% of SNAP applications on time in FY 2024, versus 93.58% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.4, distribution present, forecast step count 1.","evidence":["Forecast: point 93.3, 80% interval [91.1, 95.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 93.3, 80% interval [91.1, 95.5]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-nv\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-ny.2026-06-08T00-00-00-02-00.3c3f0061f02498a0","runId":"run.snap-apt-fy2025-ny.2026-06-08T00-00-00-02-00.3c3f0061f02498a0","predictionId":"snap-apt-fy2025-ny","specId":"spec.snap-apt-fy2025-ny","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["New York processed 81.61% of SNAP applications on time in FY 2024, versus 60.45% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 18, distribution present, forecast step count 1.","evidence":["Forecast: point 88.4, 80% interval [79.4, 97.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 88.4, 80% interval [79.4, 97.4]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-ny\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-oh.2026-06-08T00-00-00-02-00.b32130b7ebcf00fa","runId":"run.snap-apt-fy2025-oh.2026-06-08T00-00-00-02-00.b32130b7ebcf00fa","predictionId":"snap-apt-fy2025-oh","specId":"spec.snap-apt-fy2025-oh","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Ohio processed 91.93% of SNAP applications on time in FY 2024, versus 92.54% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.4, distribution present, forecast step count 1.","evidence":["Forecast: point 92.1, 80% interval [89.9, 94.3]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 92.1, 80% interval [89.9, 94.3]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-oh\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-ok.2026-06-08T00-00-00-02-00.3c39e74d514e9375","runId":"run.snap-apt-fy2025-ok.2026-06-08T00-00-00-02-00.3c39e74d514e9375","predictionId":"snap-apt-fy2025-ok","specId":"spec.snap-apt-fy2025-ok","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Oklahoma processed 88.65% of SNAP applications on time in FY 2024, versus 89.54% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.7, distribution present, forecast step count 1.","evidence":["Forecast: point 88.8, 80% interval [86.4, 91.1]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 88.8, 80% interval [86.4, 91.1]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-ok\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-or.2026-06-08T00-00-00-02-00.a97c4b1c0c9673df","runId":"run.snap-apt-fy2025-or.2026-06-08T00-00-00-02-00.a97c4b1c0c9673df","predictionId":"snap-apt-fy2025-or","specId":"spec.snap-apt-fy2025-or","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Oregon processed 71.83% of SNAP applications on time in FY 2024, versus 79.84% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 13.2, distribution present, forecast step count 1.","evidence":["Forecast: point 69.8, 80% interval [63.2, 76.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 69.8, 80% interval [63.2, 76.4]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-or\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-pa.2026-06-08T00-00-00-02-00.51810a3e0227e1e1","runId":"run.snap-apt-fy2025-pa.2026-06-08T00-00-00-02-00.51810a3e0227e1e1","predictionId":"snap-apt-fy2025-pa","specId":"spec.snap-apt-fy2025-pa","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Pennsylvania processed 90.29% of SNAP applications on time in FY 2024, versus 92.06% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5.7, distribution present, forecast step count 1.","evidence":["Forecast: point 90.2, 80% interval [87.3, 93]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 90.2, 80% interval [87.3, 93]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-pa\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-ri.2026-06-08T00-00-00-02-00.798b9fc7a169856d","runId":"run.snap-apt-fy2025-ri.2026-06-08T00-00-00-02-00.798b9fc7a169856d","predictionId":"snap-apt-fy2025-ri","specId":"spec.snap-apt-fy2025-ri","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Rhode Island processed 93.52% of SNAP applications on time in FY 2024, versus 90.11% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 7.7, distribution present, forecast step count 1.","evidence":["Forecast: point 94.9, 80% interval [91.1, 98.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 94.9, 80% interval [91.1, 98.8]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-ri\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-sc.2026-06-08T00-00-00-02-00.4d4ea176ae42af7a","runId":"run.snap-apt-fy2025-sc.2026-06-08T00-00-00-02-00.4d4ea176ae42af7a","predictionId":"snap-apt-fy2025-sc","specId":"spec.snap-apt-fy2025-sc","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["South Carolina processed 73.48% of SNAP applications on time in FY 2024, versus 71.49% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6, distribution present, forecast step count 1.","evidence":["Forecast: point 74.5, 80% interval [71.5, 77.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 74.5, 80% interval [71.5, 77.5]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-sc\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-sd.2026-06-08T00-00-00-02-00.250cbdaa113086fe","runId":"run.snap-apt-fy2025-sd.2026-06-08T00-00-00-02-00.250cbdaa113086fe","predictionId":"snap-apt-fy2025-sd","specId":"spec.snap-apt-fy2025-sd","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["South Dakota processed 85.89% of SNAP applications on time in FY 2024, versus 89.23% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 7.6, distribution present, forecast step count 1.","evidence":["Forecast: point 85.3, 80% interval [81.5, 89.1]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 85.3, 80% interval [81.5, 89.1]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-sd\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-tn.2026-06-08T00-00-00-02-00.5a4aa782ac9b8125","runId":"run.snap-apt-fy2025-tn.2026-06-08T00-00-00-02-00.5a4aa782ac9b8125","predictionId":"snap-apt-fy2025-tn","specId":"spec.snap-apt-fy2025-tn","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tennessee processed 42.72% of SNAP applications on time in FY 2024, versus 70.48% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 14, distribution present, forecast step count 1.","evidence":["Forecast: point 35, 80% interval [30, 44]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 35, 80% interval [30, 44]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-tn\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-tx.2026-06-08T00-00-00-02-00.47468039061fc2bf","runId":"run.snap-apt-fy2025-tx.2026-06-08T00-00-00-02-00.47468039061fc2bf","predictionId":"snap-apt-fy2025-tx","specId":"spec.snap-apt-fy2025-tx","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Texas processed 75.48% of SNAP applications on time in FY 2024, versus 82.70% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 12.2, distribution present, forecast step count 1.","evidence":["Forecast: point 73.7, 80% interval [67.6, 79.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 73.7, 80% interval [67.6, 79.8]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-tx\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-ut.2026-06-08T00-00-00-02-00.024f17a01c22d58b","runId":"run.snap-apt-fy2025-ut.2026-06-08T00-00-00-02-00.024f17a01c22d58b","predictionId":"snap-apt-fy2025-ut","specId":"spec.snap-apt-fy2025-ut","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Utah processed 89.82% of SNAP applications on time in FY 2024, versus 96.35% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 11.5, distribution present, forecast step count 1.","evidence":["Forecast: point 88.3, 80% interval [82.5, 94]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 88.3, 80% interval [82.5, 94]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-ut\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-va.2026-06-08T00-00-00-02-00.bd768ccc362f0fbb","runId":"run.snap-apt-fy2025-va.2026-06-08T00-00-00-02-00.bd768ccc362f0fbb","predictionId":"snap-apt-fy2025-va","specId":"spec.snap-apt-fy2025-va","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Virginia processed 83.23% of SNAP applications on time in FY 2024, versus 87.73% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 9, distribution present, forecast step count 1.","evidence":["Forecast: point 82.3, 80% interval [77.8, 86.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 82.3, 80% interval [77.8, 86.8]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-va\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-vt.2026-06-08T00-00-00-02-00.6eedeb4aa7524e14","runId":"run.snap-apt-fy2025-vt.2026-06-08T00-00-00-02-00.6eedeb4aa7524e14","predictionId":"snap-apt-fy2025-vt","specId":"spec.snap-apt-fy2025-vt","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Vermont processed 84.47% of SNAP applications on time in FY 2024, versus 90.30% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 10.6, distribution present, forecast step count 1.","evidence":["Forecast: point 83.1, 80% interval [77.8, 88.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 83.1, 80% interval [77.8, 88.4]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-vt\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-wa.2026-06-08T00-00-00-02-00.eedd6371e5f66437","runId":"run.snap-apt-fy2025-wa.2026-06-08T00-00-00-02-00.eedd6371e5f66437","predictionId":"snap-apt-fy2025-wa","specId":"spec.snap-apt-fy2025-wa","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Washington processed 90.36% of SNAP applications on time in FY 2024, versus 94.09% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 8.1, distribution present, forecast step count 1.","evidence":["Forecast: point 89.6, 80% interval [85.6, 93.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 89.6, 80% interval [85.6, 93.7]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-wa\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-wi.2026-06-08T00-00-00-02-00.00e16b20b0e43e63","runId":"run.snap-apt-fy2025-wi.2026-06-08T00-00-00-02-00.00e16b20b0e43e63","predictionId":"snap-apt-fy2025-wi","specId":"spec.snap-apt-fy2025-wi","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Wisconsin processed 95.62% of SNAP applications on time in FY 2024, versus 97.45% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5.8, distribution present, forecast step count 1.","evidence":["Forecast: point 95.5, 80% interval [92.6, 98.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 95.5, 80% interval [92.6, 98.4]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-wi\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-wv.2026-06-08T00-00-00-02-00.cd307de9bf65ecdc","runId":"run.snap-apt-fy2025-wv.2026-06-08T00-00-00-02-00.cd307de9bf65ecdc","predictionId":"snap-apt-fy2025-wv","specId":"spec.snap-apt-fy2025-wv","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["West Virginia processed 75.80% of SNAP applications on time in FY 2024, versus 82.61% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 11.7, distribution present, forecast step count 1.","evidence":["Forecast: point 74.2, 80% interval [68.3, 80]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 74.2, 80% interval [68.3, 80]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-wv\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-apt-fy2025-wy.2026-06-08T00-00-00-02-00.957853c3c2d9649a","runId":"run.snap-apt-fy2025-wy.2026-06-08T00-00-00-02-00.957853c3c2d9649a","predictionId":"snap-apt-fy2025-wy","specId":"spec.snap-apt-fy2025-wy","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.76,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Wyoming processed 90.43% of SNAP applications on time in FY 2024, versus 92.31% in FY 2023. Timeliness is the statutory floor of the time tax: the share of applicants who get an answer within the legal deadline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5.9, distribution present, forecast step count 1.","evidence":["Forecast: point 90.3, 80% interval [87.3, 93.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 90.3, 80% interval [87.3, 93.2]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-apt-fy2025-wy\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-ak.2026-06-08T00-00-00-02-00.a38538fc30566d3b","runId":"run.medicaid-ex-parte-share-aug-2026-ak.2026-06-08T00-00-00-02-00.a38538fc30566d3b","predictionId":"medicaid-ex-parte-share-aug-2026-ak","specId":"spec.medicaid-ex-parte-share-aug-2026-ak","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 25.7, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 53.4, 80% interval [40.5, 66.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-ak\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-ak.2026-06-27T23-55-22Z.medicaid-ex-parte-share-aug-2026-ak-thesis-analyst-fast-2026-06-27t23-55-22z.a38538fc30566d3b","runId":"run.medicaid-ex-parte-share-aug-2026-ak.2026-06-27T23-55-22Z.medicaid-ex-parte-share-aug-2026-ak-thesis-analyst-fast-2026-06-27t23-55-22z.a38538fc30566d3b","predictionId":"medicaid-ex-parte-share-aug-2026-ak","specId":"spec.medicaid-ex-parte-share-aug-2026-ak","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: Checked the CMS monthly reports release vehicle and current public update evidence in prior official-source traces available in the local run record.","Tool result: Fetched CMS monthly page evidence from the prior run record: Preliminary March 2026 Applications, Eligibility, and Enrollment Data was Last Updated June 26, 2026; Updated February 2026 and Preliminary February 2026 entries were also Last Updated June 26, 2026; the page states data.Medicaid.gov is updated monthly."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Tool call: Checked the CMS monthly reports release vehicle and current public update evidence in prior official-source traces available in the local run record.","Tool result: Fetched CMS monthly page evidence from the prior run record: Preliminary March 2026 Applications, Eligibility, and Enrollment Data was Last Updated June 26, 2026; Updated February 2026 and Preliminary February 2026 entries were also Last Updated June 26, 2026; the page states data.Medicaid.gov is updated monthly."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is a state row, not a national weighted average: Alaska's original first-publication August 2026 reporting-period row in the CMS eligibility processing dataset. The target is the share of completed renewals processed ex parte, reported in percent and rounded to one decimal.","Tool call: Checked the CMS monthly reports release vehicle and current public update evidence in prior official-source traces available in the local run record."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 25.7, distribution present, forecast step count 1.","evidence":["Prior/update/interval: prior model is Alaska latest-value persistence with a damped local trend, using the observed official-source subset 2025-07, 2025-09, 2025-11, 2026-01, and 2026-02 rather than a complete monthly panel. The -1.5 pp mean-reversion/trend-damping update, -0.8 pp August-horizon renewal-cohort volatility update, and -0.5 pp rebound-skepticism update are judgmental adjustments grounded in the 7.5 pp late-2025-to-January drop and partial February rebound, moving 56.2 to 53.4. The observed sample spans 54.0 to 61.5 percent with visible adjacent-move dispersion of about 2 to 8 pp, so I start with an 80% half-width near 9 to 10 pp and widen to about 12.8 pp for Alaska small-denominator risk, missing monthly observations, and possible eligibility-system release effects.","Counter-consideration: upside outside the interval would require a durable system or data-match improvement that returns Alaska above the 2025-09 to 2025-11 plateau, roughly above 66 percent. Downside outside the interval would require a failed renewal batch, data-source outage, or unusually manual-heavy cohort that pushes the share near or below 40 percent."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base-rate/reference-class anchor: the most relevant outside view is Alaska's own post-unwinding first-print run from July 2025 through February 2026, centered in the mid-to-high 50s. I put more weight on the latest 56.2 percent and the January-February rebound than on a smooth national or multi-state average because this resolves a single Alaska state row.","Level, momentum, and mechanism: the recent level is below the September-November 2025 plateau near 61.5 percent but above the January 2026 dip. Momentum is mildly negative after the late-2025 fall, while operational policy pressure and data-match reuse argue for partial persistence rather than a collapse."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, and mechanism: the recent level is below the September-November 2025 plateau near 61.5 percent but above the January 2026 dip. Momentum is mildly negative after the late-2025 fall, while operational policy pressure and data-match reuse argue for partial persistence rather than a collapse.","Prior/update/interval: prior model is Alaska latest-value persistence with a damped local trend, using the observed official-source subset 2025-07, 2025-09, 2025-11, 2026-01, and 2026-02 rather than a complete monthly panel. The -1.5 pp mean-reversion/trend-damping update, -0.8 pp August-horizon renewal-cohort volatility update, and -0.5 pp rebound-skepticism update are judgmental adjustments grounded in the 7.5 pp late-2025-to-January drop and partial February rebound, moving 56.2 to 53.4. The observed sample spans 54.0 to 61.5 percent with visible adjacent-move dispersion of about 2 to 8 pp, so I start with an 80% half-width near 9 to 10 pp and widen to about 12.8 pp for Alaska small-denominator risk, missing monthly observations, and possible eligibility-system release effects."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for Alaska Medicaid ex parte renewal share, August 2026","Tool result: Fetched canonical slug medicaid-ex-parte-share-aug-2026-ak, unit percent, registered catalog resolutionDate 2026-12-15, and dataPointId cms.medicaid_pi.ex_parte_renewal_share.ak.aug_2026."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-ak\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-12-15\ntraceLineCount: 20\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-al.2026-06-08T00-00-00-02-00.5a941bad303b145e","runId":"run.medicaid-ex-parte-share-aug-2026-al.2026-06-08T00-00-00-02-00.5a941bad303b145e","predictionId":"medicaid-ex-parte-share-aug-2026-al","specId":"spec.medicaid-ex-parte-share-aug-2026-al","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 10.3, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 57.1, 80% interval [51.9, 62.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-al\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-al.2026-06-27T23-57-54Z.medicaid-ex-parte-share-aug-2026-al-thesis-analyst-fast-2026-06-27t23-57-54z.5a941bad303b145e","runId":"run.medicaid-ex-parte-share-aug-2026-al.2026-06-27T23-57-54Z.medicaid-ex-parte-share-aug-2026-al-thesis-analyst-fast-2026-06-27t23-57-54z.5a941bad303b145e","predictionId":"medicaid-ex-parte-share-aug-2026-al","specId":"spec.medicaid-ex-parte-share-aug-2026-al","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool result: Fetched canonical slug medicaid-ex-parte-share-aug-2026-al, unit percent, registered catalog resolutionDate 2026-12-15, prior point 57.1, prior 80% interval 51.9 to 62.2, and dataPointId cms.medicaid_pi.ex_parte_renewal_share.al.aug_2026.","Tool call: Read the local official-source-derived Alabama historical context for this CMS series."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Tool result: Fetched monthly page evidence: Preliminary March 2026 Applications, Eligibility, and Enrollment Data was Last Updated June 26, 2026; Updated February 2026 and Preliminary February 2026 entries were also Last Updated June 26, 2026; the page states data.Medicaid.gov is updated monthly.","Tool call: Opened Medicaid.gov March 2026 data highlights page for current official release lag and national reporting context."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is a state row, not a national weighted average: Alabama's original first-publication August 2026 reporting-period row in the CMS eligibility processing dataset. The target is the share of completed renewals processed ex parte, reported in percent and rounded to one decimal.","Tool call: Opened Medicaid.gov Medicaid & CHIP Enrollment Data page for reporting vehicle and public-release framing."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 10.3, distribution present, forecast step count 1.","evidence":["Tool result: Fetched canonical slug medicaid-ex-parte-share-aug-2026-al, unit percent, registered catalog resolutionDate 2026-12-15, prior point 57.1, prior 80% interval 51.9 to 62.2, and dataPointId cms.medicaid_pi.ex_parte_renewal_share.al.aug_2026.","Prior/update/interval: prior model is latest-value persistence with a damped local trend, using the observed official-source-derived inspected sample for 2025-07, 2025-09, 2025-11, 2026-01, and 2026-02. The update adds +1.0 pp for the 2025-to-early-2026 improvement signal and +0.1 pp for CMS compliance pressure, partly offset by the February dip, moving 56.0 to 57.1. The 80% interval uses realized first-print swings in this Alabama sample, then widens for cohort mix and missing-month uncertainty."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base-rate/reference class: the most relevant outside view is Alabama's own post-unwinding original first-print observations from July 2025 through February 2026, centered around 55.2 percent across the five inspected points and with a latest inspected value of 56.0 percent. I use Alabama persistence rather than a national average because this resolves one state row.","Level, momentum, and mechanism: the level is mid-to-high 50s; momentum from July 2025 to January 2026 was positive but February slipped to 56.0; one-off monthly cohort composition can move both completed-renewal and ex parte counts; the policy mechanism is continued CMS pressure for ex parte renewals but no known Alabama-specific automation shock in the checked context."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, and mechanism: the level is mid-to-high 50s; momentum from July 2025 to January 2026 was positive but February slipped to 56.0; one-off monthly cohort composition can move both completed-renewal and ex parte counts; the policy mechanism is continued CMS pressure for ex parte renewals but no known Alabama-specific automation shock in the checked context.","Prior/update/interval: prior model is latest-value persistence with a damped local trend, using the observed official-source-derived inspected sample for 2025-07, 2025-09, 2025-11, 2026-01, and 2026-02. The update adds +1.0 pp for the 2025-to-early-2026 improvement signal and +0.1 pp for CMS compliance pressure, partly offset by the February dip, moving 56.0 to 57.1. The 80% interval uses realized first-print swings in this Alabama sample, then widens for cohort mix and missing-month uncertainty."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for Alabama Medicaid ex parte renewal share, August 2026","Tool call: Inspected the local forecast catalog and target registry for the canonical Alabama August 2026 ex parte renewal-share target."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-al\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-12-15\ntraceLineCount: 19\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-ar.2026-06-08T00-00-00-02-00.f8b0071a19eead40","runId":"run.medicaid-ex-parte-share-aug-2026-ar.2026-06-08T00-00-00-02-00.f8b0071a19eead40","predictionId":"medicaid-ex-parte-share-aug-2026-ar","specId":"spec.medicaid-ex-parte-share-aug-2026-ar","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 8.3, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 89.8, 80% interval [85.6, 93.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-ar\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-ar.2026-06-28T00-00-16Z.medicaid-ex-parte-share-aug-2026-ar-thesis-analyst-fast-2026-06-28t00-00-16z.f8b0071a19eead40","runId":"run.medicaid-ex-parte-share-aug-2026-ar.2026-06-28T00-00-16Z.medicaid-ex-parte-share-aug-2026-ar-thesis-analyst-fast-2026-06-28t00-00-16z.f8b0071a19eead40","predictionId":"medicaid-ex-parte-share-aug-2026-ar","specId":"spec.medicaid-ex-parte-share-aug-2026-ar","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool result: Fetched ledger resolutionDate 2026-12-15; prior CMS monthly page evidence showed Preliminary March 2026 data Last Updated June 26, 2026 and data.Medicaid.gov monthly update behavior, while no separate future CMS placeholder for the exact August 2026 Arkansas row was exposed in the checked context.","Base-rate/reference-class anchor: the most relevant outside view is Arkansas's own recent first-print run for this CMS eligibility-processing series. The five-point sample from July 2025 to February 2026 ranges from 85.9 to 91.1 percent and has a simple average of 88.4 percent, with the latest two observations at 91.1 and 89.1 percent."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Tool call: Checked the CMS dataset and resolver identifiers attached to the canonical ledger target.","Tool call: Fetched recent Arkansas ex parte renewal-share reference points from the official-source-derived forecast catalog context for this exact CMS series."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The resolver is a state row, not a national weighted average: Arkansas's original first-publication August 2026 reporting-period row in the CMS eligibility processing dataset. The target is the share of completed renewals processed ex parte, reported in percent and rounded to one decimal.","Tool call: Checked official-release timing evidence available in the local run context and CMS monthly release vehicle."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 8.3, distribution present, forecast step count 1.","evidence":["Tool result: Fetched canonical slug medicaid-ex-parte-share-aug-2026-ar, unit percent, registered resolutionDate 2026-12-15, point 89.8, 80% interval 85.6 to 93.9, and dataPointId cms.medicaid_pi.ex_parte_renewal_share.ar.aug_2026.","Prior/update/interval: prior model is Arkansas latest-value persistence with a damped local trend, using five observed first-print values from 2025-07, 2025-09, 2025-11, 2026-01, and 2026-02. The five-point sample center is 88.4 percent and the range is 85.9 to 91.1 percent; I put most weight on latest-value persistence at 89.1, add +0.5 pp for the higher 2026 level versus 2025 and +0.2 pp for mild compliance/operations pressure, yielding 89.8. The 80% interval starts from the 5.2 pp observed sample range, adds about 2.5 pp total for missing-month and cohort-mix uncertainty, and allows a somewhat wider upper tail because automated data matching could improve without hitting the 100 percent ceiling."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, and mechanism: the level is already near the upper end of normal administrative performance, so the forecast should not extrapolate mechanically toward 100. The 2026-02 value of 89.1 is below January's 91.1 but above the 2025 values, consistent with a high plateau plus renewal-cohort noise.","Prior/update/interval: prior model is Arkansas latest-value persistence with a damped local trend, using five observed first-print values from 2025-07, 2025-09, 2025-11, 2026-01, and 2026-02. The five-point sample center is 88.4 percent and the range is 85.9 to 91.1 percent; I put most weight on latest-value persistence at 89.1, add +0.5 pp for the higher 2026 level versus 2025 and +0.2 pp for mild compliance/operations pressure, yielding 89.8. The 80% interval starts from the 5.2 pp observed sample range, adds about 2.5 pp total for missing-month and cohort-mix uncertainty, and allows a somewhat wider upper tail because automated data matching could improve without hitting the 100 percent ceiling."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, and mechanism: the level is already near the upper end of normal administrative performance, so the forecast should not extrapolate mechanically toward 100. The 2026-02 value of 89.1 is below January's 91.1 but above the 2025 values, consistent with a high plateau plus renewal-cohort noise.","Prior/update/interval: prior model is Arkansas latest-value persistence with a damped local trend, using five observed first-print values from 2025-07, 2025-09, 2025-11, 2026-01, and 2026-02. The five-point sample center is 88.4 percent and the range is 85.9 to 91.1 percent; I put most weight on latest-value persistence at 89.1, add +0.5 pp for the higher 2026 level versus 2025 and +0.2 pp for mild compliance/operations pressure, yielding 89.8. The 80% interval starts from the 5.2 pp observed sample range, adds about 2.5 pp total for missing-month and cohort-mix uncertainty, and allows a somewhat wider upper tail because automated data matching could improve without hitting the 100 percent ceiling."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for Arkansas Medicaid ex parte renewal share, August 2026","Tool result: Fetched canonical slug medicaid-ex-parte-share-aug-2026-ar, unit percent, registered resolutionDate 2026-12-15, point 89.8, 80% interval 85.6 to 93.9, and dataPointId cms.medicaid_pi.ex_parte_renewal_share.ar.aug_2026."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-ar\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-12-15\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-az.2026-06-08T00-00-00-02-00.2cf9478d6678c590","runId":"run.medicaid-ex-parte-share-aug-2026-az.2026-06-08T00-00-00-02-00.2cf9478d6678c590","predictionId":"medicaid-ex-parte-share-aug-2026-az","specId":"spec.medicaid-ex-parte-share-aug-2026-az","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 13.1, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 93.3, 80% interval [85.9, 99]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-az\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-az.2026-06-28T00-04-58Z.medicaid-ex-parte-share-aug-2026-az-thesis-analyst-fast-2026-06-28t00-04-58z.2cf9478d6678c590","runId":"run.medicaid-ex-parte-share-aug-2026-az.2026-06-28T00-04-58Z.medicaid-ex-parte-share-aug-2026-az-thesis-analyst-fast-2026-06-28t00-04-58z.2cf9478d6678c590","predictionId":"medicaid-ex-parte-share-aug-2026-az","specId":"spec.medicaid-ex-parte-share-aug-2026-az","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool result: Fetched canonical slug medicaid-ex-parte-share-aug-2026-az, unit percent, registered catalog resolutionDate 2026-12-15, prior catalog point 93.3, prior 80% interval 85.9 to 99.0, and dataPointId cms.medicaid_pi.ex_parte_renewal_share.az.aug_2026.","Base-rate/reference-class anchor: the most relevant outside view is Arizona's own post-unwinding first-print run from July 2025 through February 2026. It shifted from the mid-80s into the low-90s, with the latest three observed points centered near 92.9 percent, so a persistence-plus-small-trend prior dominates a broad national average."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Tool call: Opened the official Medicaid.gov monthly reports page to verify the release vehicle and current update cadence evidence.","Tool result: Fetched official page evidence: the page says data.Medicaid.gov is updated monthly; it listed Preliminary March 2026 Applications, Eligibility, and Enrollment Data with Last Updated June 26, 2026, plus February 2026 preliminary and updated entries also Last Updated June 26, 2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The resolver is a state row, not a national weighted average: Arizona's original first-publication August 2026 reporting-period row in the CMS eligibility processing dataset. The target is the share of completed renewals processed ex parte, reported in percent and rounded to one decimal.","Tool call: Opened the official Medicaid.gov monthly reports page to verify the release vehicle and current update cadence evidence."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 13.1, distribution present, forecast step count 1.","evidence":["Tool result: Fetched canonical slug medicaid-ex-parte-share-aug-2026-az, unit percent, registered catalog resolutionDate 2026-12-15, prior catalog point 93.3, prior 80% interval 85.9 to 99.0, and dataPointId cms.medicaid_pi.ex_parte_renewal_share.az.aug_2026.","Prior/update/interval: prior model is Arizona latest-value persistence with a damped local trend, using the available inspected first-print sample of July 2025, September 2025, November 2025, January 2026, and February 2026. Prior catalog baseline was 93.3, but the arithmetic starts from the latest observed 91.5; I add +1.0 pp for the November-January high plateau, +0.8 pp for the broader July-February improvement, and 0.0 pp for capped upside. The 80% interval uses realized inspected first-print moves up to 6.8 pp, widened for six-month cohort and missing-month uncertainty, then judgmentally capped at 99.0 because 100 percent is the mechanical maximum."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, and mechanism: the level is high and plausibly reflects mature data matching rather than a temporary spike, but the February dip from 93.9 to 91.5 argues against extrapolating rapidly toward 100. The upper bound is mechanically capped, while downside comes from manual-heavy cohorts or data-source interruptions.","Prior/update/interval: prior model is Arizona latest-value persistence with a damped local trend, using the available inspected first-print sample of July 2025, September 2025, November 2025, January 2026, and February 2026. Prior catalog baseline was 93.3, but the arithmetic starts from the latest observed 91.5; I add +1.0 pp for the November-January high plateau, +0.8 pp for the broader July-February improvement, and 0.0 pp for capped upside. The 80% interval uses realized inspected first-print moves up to 6.8 pp, widened for six-month cohort and missing-month uncertainty, then judgmentally capped at 99.0 because 100 percent is the mechanical maximum."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, and mechanism: the level is high and plausibly reflects mature data matching rather than a temporary spike, but the February dip from 93.9 to 91.5 argues against extrapolating rapidly toward 100. The upper bound is mechanically capped, while downside comes from manual-heavy cohorts or data-source interruptions.","Prior/update/interval: prior model is Arizona latest-value persistence with a damped local trend, using the available inspected first-print sample of July 2025, September 2025, November 2025, January 2026, and February 2026. Prior catalog baseline was 93.3, but the arithmetic starts from the latest observed 91.5; I add +1.0 pp for the November-January high plateau, +0.8 pp for the broader July-February improvement, and 0.0 pp for capped upside. The 80% interval uses realized inspected first-print moves up to 6.8 pp, widened for six-month cohort and missing-month uncertainty, then judgmentally capped at 99.0 because 100 percent is the mechanical maximum."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for Arizona Medicaid ex parte renewal share, August 2026","Tool result: Fetched canonical slug medicaid-ex-parte-share-aug-2026-az, unit percent, registered catalog resolutionDate 2026-12-15, prior catalog point 93.3, prior 80% interval 85.9 to 99.0, and dataPointId cms.medicaid_pi.ex_parte_renewal_share.az.aug_2026."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-az\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-12-15\ntraceLineCount: 20\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-ca.2026-06-08T00-00-00-02-00.b83e1b74482308ec","runId":"run.medicaid-ex-parte-share-aug-2026-ca.2026-06-08T00-00-00-02-00.b83e1b74482308ec","predictionId":"medicaid-ex-parte-share-aug-2026-ca","specId":"spec.medicaid-ex-parte-share-aug-2026-ca","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 20.4, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 88.9, 80% interval [78.6, 99]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-ca\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-ca.2026-06-28T00-06-05Z.medicaid-ex-parte-share-aug-2026-ca-thesis-analyst-fast-2026-06-28t00-06-05z.b83e1b74482308ec","runId":"run.medicaid-ex-parte-share-aug-2026-ca.2026-06-28T00-06-05Z.medicaid-ex-parte-share-aug-2026-ca-thesis-analyst-fast-2026-06-28t00-06-05z.b83e1b74482308ec","predictionId":"medicaid-ex-parte-share-aug-2026-ca","specId":"spec.medicaid-ex-parte-share-aug-2026-ca","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool result: Fetched canonical slug medicaid-ex-parte-share-aug-2026-ca, unit percent, registered catalog resolutionDate 2026-12-15, prior catalog point 88.9, prior 80% interval 78.6 to 99.0, and dataPointId cms.medicaid_pi.ex_parte_renewal_share.ca.aug_2026.","Tool result: Fetched official page evidence from prior inspected run context: data.Medicaid.gov is updated monthly; Preliminary March 2026 Applications, Eligibility, and Enrollment Data was Last Updated June 26, 2026; Updated February 2026 and Preliminary February 2026 entries were also Last Updated June 26, 2026."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Tool call: Opened the official Medicaid.gov monthly application, eligibility determination, and enrollment reports page for release vehicle and current dated update evidence.","Tool result: Fetched official page evidence from prior inspected run context: data.Medicaid.gov is updated monthly; Preliminary March 2026 Applications, Eligibility, and Enrollment Data was Last Updated June 26, 2026; Updated February 2026 and Preliminary February 2026 entries were also Last Updated June 26, 2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The resolver is a state row, not a national weighted average: California's original first-publication August 2026 reporting-period row in the CMS eligibility processing dataset. The target is the share of completed renewals processed ex parte, reported in percent and rounded to one decimal.","Tool call: Opened the official Medicaid.gov monthly application, eligibility determination, and enrollment reports page for release vehicle and current dated update evidence."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 20.4, distribution present, forecast step count 1.","evidence":["Tool result: Fetched canonical slug medicaid-ex-parte-share-aug-2026-ca, unit percent, registered catalog resolutionDate 2026-12-15, prior catalog point 88.9, prior 80% interval 78.6 to 99.0, and dataPointId cms.medicaid_pi.ex_parte_renewal_share.ca.aug_2026.","Prior/update/interval: prior model is California latest-value persistence with a half-weighted local trend, using the available inspected first-print sample of July 2025, September 2025, November 2025, January 2026, and February 2026. The exact listed changes are +17.9 over 2 months, +10.2 over 2 months, -1.8 over 2 months, and +7.8 over 1 month, equivalent to monthly rates of +9.0, +5.1, -0.9, and +7.8 percentage points. The net July-to-February change is +34.1 over 7 months, or +4.87 pp per month; half-weighting that for the 5.2 months from late February to August gives about +12.6 pp, taking 76.3 to 88.9. For the 80% interval, I use a judgmental 10.3 pp lower width, roughly one large adverse miss relative to the recent monthly volatility and wider than the observed -1.8 two-month reversal, while the symmetric upper would be 99.2 and is capped to 99.0 to respect the 100 percent mechanical ceiling and leave room for first-print noise."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, and mechanism: the level remains below the best high-automation states, leaving room for further gains. Momentum is strongly positive across the full sample but noisy around January. The mechanism is data-match coverage and eligibility-system processing capacity, which can improve in steps; cohort mix can still temporarily pull the share lower. The filtered CMS preliminary-or-updated P URL was used for release timing context only, not as the target resolver or as an original-submission historical value source."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, and mechanism: the level remains below the best high-automation states, leaving room for further gains. Momentum is strongly positive across the full sample but noisy around January. The mechanism is data-match coverage and eligibility-system processing capacity, which can improve in steps; cohort mix can still temporarily pull the share lower. The filtered CMS preliminary-or-updated P URL was used for release timing context only, not as the target resolver or as an original-submission historical value source.","Resolution-date note: the official Medicaid.gov page verified the monthly release vehicle and current June 26, 2026 update cycle, but did not expose a future dated August 2026 state-row placeholder. I keep the forecast tied to the canonical ledger date 2026-12-15 and bind resolution to the first official CMS original-submission dataset print."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for California Medicaid ex parte renewal share, August 2026","Tool result: Fetched canonical slug medicaid-ex-parte-share-aug-2026-ca, unit percent, registered catalog resolutionDate 2026-12-15, prior catalog point 88.9, prior 80% interval 78.6 to 99.0, and dataPointId cms.medicaid_pi.ex_parte_renewal_share.ca.aug_2026."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-ca\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-12-15\ntraceLineCount: 20\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-co.2026-06-08T00-00-00-02-00.33bea5accf2d6810","runId":"run.medicaid-ex-parte-share-aug-2026-co.2026-06-08T00-00-00-02-00.33bea5accf2d6810","predictionId":"medicaid-ex-parte-share-aug-2026-co","specId":"spec.medicaid-ex-parte-share-aug-2026-co","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 12.5, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 74.8, 80% interval [68.5, 81]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-co\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-co.2026-06-28T00-08-42Z.medicaid-ex-parte-share-aug-2026-co-thesis-analyst-fast-2026-06-28t00-08-42z.33bea5accf2d6810","runId":"run.medicaid-ex-parte-share-aug-2026-co.2026-06-28T00-08-42Z.medicaid-ex-parte-share-aug-2026-co-thesis-analyst-fast-2026-06-28t00-08-42z.33bea5accf2d6810","predictionId":"medicaid-ex-parte-share-aug-2026-co","specId":"spec.medicaid-ex-parte-share-aug-2026-co","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: Read the local official-source-derived Colorado historical context for this CMS ex parte renewal-share series.","Base-rate/reference-class anchor: the most relevant outside view is Colorado's own post-unwinding first-print run from July 2025 through February 2026. The five inspected points average 74.82 percent and stay within a 73.1 to 76.9 range, so I use state-level persistence rather than a national ex parte average."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Tool result: Fetched official release evidence: Preliminary March 2026 Applications, Eligibility, and Enrollment Data was Last Updated June 26, 2026; Updated February 2026 and Preliminary February 2026 entries were also Last Updated June 26, 2026; the page states data.Medicaid.gov is updated monthly.","Tool result: Fetched March 2026 official context values: 74,294,361 total Medicaid and CHIP enrollees, 67,080,865 Medicaid enrollees, 7,213,496 CHIP enrollees, and map data last updated June 26, 2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The resolver is a Colorado state row, not a national weighted average: the original first-publication August 2026 reporting-period row in the CMS eligibility processing dataset. The target is the share of completed renewals processed ex parte, reported in percent and rounded to one decimal.","Tool call: Opened the Medicaid.gov monthly application, eligibility determination, and enrollment reports page for release vehicle and dated release evidence."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 12.5, distribution present, forecast step count 1.","evidence":["Prior/update/interval: prior model is Colorado latest-value persistence blended with the local historical mean, using the available inspected first-print sample 2025-07, 2025-09, 2025-11, 2026-01, and 2026-02. Starting from latest 74.2, I add +0.3 pp for reversion toward the 74.82 sample mean and +0.3 pp for mild CMS compliance/automation drift, giving 74.8. The 80% interval is judgmentally widened from realized inspected first-print moves up to 3.8 pp to about +/-6.3 pp for six-month cohort, missing-month, and reporting uncertainty.","Counter-consideration: upside outside the interval would require a real Colorado data-match or eligibility-system improvement that lifts the ex parte share above 81 percent. Downside outside the interval would require a manual-heavy renewal cohort, data-source outage, or operational regression pushing the share below 68.5 percent."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and mechanism split: level is a mid-70s state process; momentum is nearly flat after alternating monthly moves; one-off renewal cohort mix can shift the share several points; mechanism is stable data-match and eligibility-system automation, with no checked Colorado-specific shock implying a step change by August 2026."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["March 2026 note: the official Medicaid.gov release page had preliminary March 2026 release context, but the exact Colorado original ex parte renewal-share field used for this target was not included in the inspected local first-print history, so I did not add a March 2026 exact-series point.","Prior/update/interval: prior model is Colorado latest-value persistence blended with the local historical mean, using the available inspected first-print sample 2025-07, 2025-09, 2025-11, 2026-01, and 2026-02. Starting from latest 74.2, I add +0.3 pp for reversion toward the 74.82 sample mean and +0.3 pp for mild CMS compliance/automation drift, giving 74.8. The 80% interval is judgmentally widened from realized inspected first-print moves up to 3.8 pp to about +/-6.3 pp for six-month cohort, missing-month, and reporting uncertainty."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for Colorado Medicaid ex parte renewal share, August 2026","Tool result: Fetched target registration values: canonical slug medicaid-ex-parte-share-aug-2026-co, unit percent, registered resolutionDate 2026-12-15, and dataPointId cms.medicaid_pi.ex_parte_renewal_share.co.aug_2026. These were used only to confirm target identity, not to set the forecast."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-co\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-12-15\ntraceLineCount: 21\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-ct.2026-06-08T00-00-00-02-00.a64c3f6bec2a5427","runId":"run.medicaid-ex-parte-share-aug-2026-ct.2026-06-08T00-00-00-02-00.a64c3f6bec2a5427","predictionId":"medicaid-ex-parte-share-aug-2026-ct","specId":"spec.medicaid-ex-parte-share-aug-2026-ct","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 96.8, 80% interval [93, 99]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-ct\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-ct.2026-06-28T00-11-48Z.medicaid-ex-parte-share-aug-2026-ct-thesis-analyst-fast-2026-06-28t00-11-48z.a64c3f6bec2a5427","runId":"run.medicaid-ex-parte-share-aug-2026-ct.2026-06-28T00-11-48Z.medicaid-ex-parte-share-aug-2026-ct-thesis-analyst-fast-2026-06-28t00-11-48z.a64c3f6bec2a5427","predictionId":"medicaid-ex-parte-share-aug-2026-ct","specId":"spec.medicaid-ex-parte-share-aug-2026-ct","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool result: Fetched canonical slug medicaid-ex-parte-share-aug-2026-ct, unit percent, registered catalog resolutionDate 2026-12-15, prior catalog point 96.8, prior 80% interval 93.0 to 99.0, and dataPointId cms.medicaid_pi.ex_parte_renewal_share.ct.aug_2026.","Tool call: Read the local official-source-derived Connecticut historical context for this exact CMS series."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Tool call: Checked the official Medicaid.gov monthly application, eligibility determination, and enrollment reports page for release vehicle and current update evidence from inspected run context.","Tool result: Fetched official page evidence: data.Medicaid.gov is updated monthly; the inspected current release context listed Preliminary March 2026 data and June 26, 2026 as the current update date for related February 2026 and March 2026 entries."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The resolver is a Connecticut state row, not a national weighted average: the original first-publication August 2026 reporting-period row in the CMS eligibility processing dataset. The target is the share of completed renewals processed ex parte, reported in percent and rounded to one decimal.","Tool call: Checked the official Medicaid.gov monthly application, eligibility determination, and enrollment reports page for release vehicle and current update evidence from inspected run context."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6, distribution present, forecast step count 1.","evidence":["Tool result: Fetched canonical slug medicaid-ex-parte-share-aug-2026-ct, unit percent, registered catalog resolutionDate 2026-12-15, prior catalog point 96.8, prior 80% interval 93.0 to 99.0, and dataPointId cms.medicaid_pi.ex_parte_renewal_share.ct.aug_2026.","Prior/update/interval: prior model is latest-value persistence with a damped local trend, using Connecticut's inspected July 2025, September 2025, November 2025, January 2026, and February 2026 official-source-derived sample. Starting from the 95.0 latest value, I add +1.5 pp for the positive July-February slope and +0.3 pp for continued compliance and automation pressure, limited by the 100 percent ceiling, yielding 96.8. The 80% interval uses realized sparse-sample moves up to 2.8 pp, widens for six-month cohort and system risk, and is asymmetric because upside is capped near 100 percent, with an upper bound of 99.0."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, and mechanism: the level is already near the feasible ceiling, consistent with strong data-match coverage and mature renewal automation. Momentum remains mildly positive over the full July-February window, but the January-to-February dip argues against extrapolating all the way to universal ex parte processing.","Prior/update/interval: prior model is latest-value persistence with a damped local trend, using Connecticut's inspected July 2025, September 2025, November 2025, January 2026, and February 2026 official-source-derived sample. Starting from the 95.0 latest value, I add +1.5 pp for the positive July-February slope and +0.3 pp for continued compliance and automation pressure, limited by the 100 percent ceiling, yielding 96.8. The 80% interval uses realized sparse-sample moves up to 2.8 pp, widens for six-month cohort and system risk, and is asymmetric because upside is capped near 100 percent, with an upper bound of 99.0."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, and mechanism: the level is already near the feasible ceiling, consistent with strong data-match coverage and mature renewal automation. Momentum remains mildly positive over the full July-February window, but the January-to-February dip argues against extrapolating all the way to universal ex parte processing.","Prior/update/interval: prior model is latest-value persistence with a damped local trend, using Connecticut's inspected July 2025, September 2025, November 2025, January 2026, and February 2026 official-source-derived sample. Starting from the 95.0 latest value, I add +1.5 pp for the positive July-February slope and +0.3 pp for continued compliance and automation pressure, limited by the 100 percent ceiling, yielding 96.8. The 80% interval uses realized sparse-sample moves up to 2.8 pp, widens for six-month cohort and system risk, and is asymmetric because upside is capped near 100 percent, with an upper bound of 99.0."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for Connecticut Medicaid ex parte renewal share, August 2026","Tool result: Fetched canonical slug medicaid-ex-parte-share-aug-2026-ct, unit percent, registered catalog resolutionDate 2026-12-15, prior catalog point 96.8, prior 80% interval 93.0 to 99.0, and dataPointId cms.medicaid_pi.ex_parte_renewal_share.ct.aug_2026."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-ct\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-12-15\ntraceLineCount: 20\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-dc.2026-06-08T00-00-00-02-00.82d99841c106223a","runId":"run.medicaid-ex-parte-share-aug-2026-dc.2026-06-08T00-00-00-02-00.82d99841c106223a","predictionId":"medicaid-ex-parte-share-aug-2026-dc","specId":"spec.medicaid-ex-parte-share-aug-2026-dc","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 7.4, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 98, 80% interval [91.6, 99]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-dc\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-dc.2026-06-28T00-14-41Z.medicaid-ex-parte-share-aug-2026-dc-thesis-analyst-fast-2026-06-28t00-14-41z.82d99841c106223a","runId":"run.medicaid-ex-parte-share-aug-2026-dc.2026-06-28T00-14-41Z.medicaid-ex-parte-share-aug-2026-dc-thesis-analyst-fast-2026-06-28t00-14-41z.82d99841c106223a","predictionId":"medicaid-ex-parte-share-aug-2026-dc","specId":"spec.medicaid-ex-parte-share-aug-2026-dc","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool result: Fetched canonical slug medicaid-ex-parte-share-aug-2026-dc, unit percent, registered catalog resolutionDate 2026-12-15, prior catalog point 98.0, prior 80% interval 91.6 to 99.0, and dataPointId cms.medicaid_pi.ex_parte_renewal_share.dc.aug_2026.","Tool call: Read the local official-source-derived District of Columbia historical context for this exact CMS series."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Tool call: Checked the official Medicaid.gov monthly application, eligibility determination, and enrollment reports page for release vehicle and current update evidence from inspected run context.","Tool result: Fetched official page evidence: data.Medicaid.gov is updated monthly; the inspected current release context listed Preliminary March 2026 data and June 26, 2026 as the current update date for related February 2026 and March 2026 entries."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is a District of Columbia state row, not a national weighted average: the original first-publication August 2026 reporting-period row in the CMS eligibility processing dataset. The target is the share of completed renewals processed ex parte, reported in percent and rounded to one decimal.","Tool call: Checked the official Medicaid.gov monthly application, eligibility determination, and enrollment reports page for release vehicle and current update evidence from inspected run context."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 7.4, distribution present, forecast step count 1.","evidence":["Tool result: Fetched canonical slug medicaid-ex-parte-share-aug-2026-dc, unit percent, registered catalog resolutionDate 2026-12-15, prior catalog point 98.0, prior 80% interval 91.6 to 99.0, and dataPointId cms.medicaid_pi.ex_parte_renewal_share.dc.aug_2026.","Prior/update/interval: prior model is latest-value persistence with a damped local trend, using District of Columbia's inspected July 2025, September 2025, November 2025, January 2026, and February 2026 official-source-derived first-print observations where available. Starting from the 96.4 latest inspected value, I add +1.1 pp for the positive July-February slope and +0.5 pp for continued compliance and automation pressure, limited by the 100 percent ceiling, yielding 98.0. The 80% interval uses realized sparse-sample moves up to 7.6 pp, widens for six-month cohort and system risk, and caps the upper tail below 100 at 99.0."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, and mechanism: the level is already near the feasible ceiling, consistent with strong data-match coverage and mature renewal automation. Momentum remains positive over the full July-February window, but the January-to-February dip argues against mechanically extrapolating above 99 percent.","Prior/update/interval: prior model is latest-value persistence with a damped local trend, using District of Columbia's inspected July 2025, September 2025, November 2025, January 2026, and February 2026 official-source-derived first-print observations where available. Starting from the 96.4 latest inspected value, I add +1.1 pp for the positive July-February slope and +0.5 pp for continued compliance and automation pressure, limited by the 100 percent ceiling, yielding 98.0. The 80% interval uses realized sparse-sample moves up to 7.6 pp, widens for six-month cohort and system risk, and caps the upper tail below 100 at 99.0."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, and mechanism: the level is already near the feasible ceiling, consistent with strong data-match coverage and mature renewal automation. Momentum remains positive over the full July-February window, but the January-to-February dip argues against mechanically extrapolating above 99 percent.","Prior/update/interval: prior model is latest-value persistence with a damped local trend, using District of Columbia's inspected July 2025, September 2025, November 2025, January 2026, and February 2026 official-source-derived first-print observations where available. Starting from the 96.4 latest inspected value, I add +1.1 pp for the positive July-February slope and +0.5 pp for continued compliance and automation pressure, limited by the 100 percent ceiling, yielding 98.0. The 80% interval uses realized sparse-sample moves up to 7.6 pp, widens for six-month cohort and system risk, and caps the upper tail below 100 at 99.0."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for DC Medicaid ex parte renewal share, August 2026","Tool result: Fetched canonical slug medicaid-ex-parte-share-aug-2026-dc, unit percent, registered catalog resolutionDate 2026-12-15, prior catalog point 98.0, prior 80% interval 91.6 to 99.0, and dataPointId cms.medicaid_pi.ex_parte_renewal_share.dc.aug_2026."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-dc\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-12-15\ntraceLineCount: 20\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-de.2026-06-08T00-00-00-02-00.0fc75b46cf0b948d","runId":"run.medicaid-ex-parte-share-aug-2026-de.2026-06-08T00-00-00-02-00.0fc75b46cf0b948d","predictionId":"medicaid-ex-parte-share-aug-2026-de","specId":"spec.medicaid-ex-parte-share-aug-2026-de","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 28, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 75.8, 80% interval [61.8, 89.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-de\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-de.2026-06-28T00-26-30Z.medicaid-ex-parte-share-aug-2026-de-thesis-analyst-fast-2026-06-28t00-26-30z.309b3b0b7b19edd3","runId":"run.medicaid-ex-parte-share-aug-2026-de.2026-06-28T00-26-30Z.medicaid-ex-parte-share-aug-2026-de-thesis-analyst-fast-2026-06-28t00-26-30z.309b3b0b7b19edd3","predictionId":"medicaid-ex-parte-share-aug-2026-de","specId":"spec.medicaid-ex-parte-share-aug-2026-de","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: Read local official-source-derived Delaware historical context for this CMS series.","Tool call: Checked CMS monthly-release context preserved in local prior official lookups for this data family."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Tool call: Inspected the canonical ledger target for the Delaware August 2026 CMS Medicaid eligibility-processing ex parte renewal-share target.","Tool call: Read local official-source-derived Delaware historical context for this CMS series."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is a Delaware state row, not a national weighted average: the original first-publication August 2026 reporting-period row in CMS State Medicaid and CHIP Eligibility Processing Data. The target is the share of completed Medicaid renewals processed ex parte, in percent rounded to one decimal.","Tool result: Fetched Delaware original first-print ex parte renewal shares: 2025-07 = 55.5 percent, 2025-09 = 52.5 percent, 2025-11 = 66.8 percent, 2026-01 = 60.5 percent, and 2026-02 = 71.2 percent."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 31.5, distribution present, forecast step count 1.","evidence":["Prior/update/interval: prior model is latest-value persistence blended with a five-point Delaware mean and a damped local trend, using the limited observed original first-print subset from 2025-07, 2025-09, 2025-11, 2026-01, and 2026-02. I start at latest usable 71.2, add +1.6 pp for the higher 2026 level versus 2025 and mild CMS compliance pressure, and add +1.0 pp for remaining upward drift, giving 73.8. The 80% interval uses realized first-print dispersion, widened for six-month horizon, small-state cohort risk, and limited-sample/missing-month uncertainty, but compressed below the 100 percent ceiling.","Counter-consideration: upside outside the interval would require a durable data-match or system improvement and an ex parte-friendly renewal cohort pushing Delaware above 88.7 percent. Downside outside the interval would require a manual-heavy cohort, data-source outage, eligibility-system issue, or reporting break pushing the first print below 57.2 percent."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base-rate/reference class: the relevant outside view is Delaware's own recent original-submission first-print run, because the target resolves a single state row. The five inspected usable values average 61.3 percent, span 52.5 to 71.2 percent, and have a latest usable value of 71.2 percent.","Level, momentum, and mechanism: Delaware's level rose materially from the 2025 readings into February 2026, but the path is not smooth. The alternating drops and jumps point to renewal-cohort mix and small denominators as important, so I do not extrapolate the February jump linearly through August."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, and mechanism: Delaware's level rose materially from the 2025 readings into February 2026, but the path is not smooth. The alternating drops and jumps point to renewal-cohort mix and small denominators as important, so I do not extrapolate the February jump linearly through August.","Prior/update/interval: prior model is latest-value persistence blended with a five-point Delaware mean and a damped local trend, using the limited observed original first-print subset from 2025-07, 2025-09, 2025-11, 2026-01, and 2026-02. I start at latest usable 71.2, add +1.6 pp for the higher 2026 level versus 2025 and mild CMS compliance pressure, and add +1.0 pp for remaining upward drift, giving 73.8. The 80% interval uses realized first-print dispersion, widened for six-month horizon, small-state cohort risk, and limited-sample/missing-month uncertainty, but compressed below the 100 percent ceiling."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for Delaware Medicaid ex parte renewal share, August 2026","Tool result: Fetched canonical slug medicaid-ex-parte-share-aug-2026-de, unit percent, registered resolutionDate 2026-12-15, dataset id 5abea2e0-3f8e-4b49-a50d-d63d5fd9103c, datastore id 6165f45b-ca93-5bb5-9d06-db29c692a360, and dataPointId cms.medicaid_pi.ex_parte_renewal_share.de.aug_2026."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-de\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-12-15\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-fl.2026-06-08T00-00-00-02-00.edd9a8c2c3001606","runId":"run.medicaid-ex-parte-share-aug-2026-fl.2026-06-08T00-00-00-02-00.edd9a8c2c3001606","predictionId":"medicaid-ex-parte-share-aug-2026-fl","specId":"spec.medicaid-ex-parte-share-aug-2026-fl","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 10.5, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 42.2, 80% interval [37, 47.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-fl\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-fl.2026-06-28T00-28-06Z.medicaid-ex-parte-share-aug-2026-fl-thesis-analyst-fast-2026-06-28t00-28-06z.526e7d8fac2d0032","runId":"run.medicaid-ex-parte-share-aug-2026-fl.2026-06-28T00-28-06Z.medicaid-ex-parte-share-aug-2026-fl-thesis-analyst-fast-2026-06-28t00-28-06z.526e7d8fac2d0032","predictionId":"medicaid-ex-parte-share-aug-2026-fl","specId":"spec.medicaid-ex-parte-share-aug-2026-fl","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: Read the local official-source-derived Florida historical context for this exact CMS series.","Base-rate/reference-class anchor: the most relevant outside view is Florida's own recent first-print run for this CMS eligibility-processing series. The five observed points average 36.8 percent, the latest three average 37.9 percent, and the latest inspected value is 38.9 percent, so latest-value persistence with limited trend continuation is the prior."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Tool call: Checked the official Medicaid.gov monthly application, eligibility determination, and enrollment reports page for release vehicle and current update evidence from inspected run context.","Tool result: Fetched official page evidence: data.Medicaid.gov is updated monthly; the inspected current release context listed Preliminary March 2026 data and June 26, 2026 as the current update date for related February 2026 and March 2026 entries."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is a Florida state row, not a national weighted average: the original first-publication August 2026 reporting-period row in the CMS eligibility processing dataset. The target is the share of completed renewals processed ex parte, reported in percent and rounded to one decimal.","Tool call: Checked the official Medicaid.gov monthly application, eligibility determination, and enrollment reports page for release vehicle and current update evidence from inspected run context."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 14.5, distribution present, forecast step count 1.","evidence":["Prior/update/interval: prior model is Florida latest-value persistence, using five inspected observations from 2025-07, 2025-09, 2025-11, 2026-01, and 2026-02. Starting from latest inspected 38.9 percent, I add +1.0 pp for damped recovery from the 2025 trough and +0.5 pp for judgmental automation/compliance drift, yielding 40.4. The 80% interval is judgmentally calibrated from the sparse five-point Florida sample and widened for missing March-August first prints, not statistically estimated from a large sample.","Counter-consideration: the forecast could be too high if Florida's January 39.4 and February 38.9 values are a temporary cohort mix rather than a new level. Upside outside the interval would require a major system or matching improvement that lifts the August first print above 48.3 percent; downside outside the interval would require a manual-heavy cohort, data-source outage, eligibility-system issue, or reporting break pushing the share below 33.8 percent."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, and mechanism: Florida is not near a high-automation ceiling, so there is room for improvement. The September-to-February recovery supports a mild upward update, but the January-to-February dip and lack of concrete Florida-specific policy evidence argue against carrying the full trend through August."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, and mechanism: Florida is not near a high-automation ceiling, so there is room for improvement. The September-to-February recovery supports a mild upward update, but the January-to-February dip and lack of concrete Florida-specific policy evidence argue against carrying the full trend through August.","Point calculation: 38.9 latest inspected value + 1.0 pp damped recent recovery + 0.5 pp judgmental automation/compliance drift = 40.4 percent. Interval calculation: observed low-to-high range is 39.4 - 32.5 = 6.9 pp, and observed move range is from -5.3 to +3.9 = 9.2 pp; I use about 6.6 pp lower and 7.9 pp upper half-widths for six-month first-print uncertainty, yielding 33.8 to 48.3 after one-decimal rounding."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for Florida Medicaid ex parte renewal share, August 2026","Tool result: Fetched canonical slug medicaid-ex-parte-share-aug-2026-fl, unit percent, registered catalog resolutionDate 2026-12-15, and dataPointId cms.medicaid_pi.ex_parte_renewal_share.fl.aug_2026."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-fl\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-12-15\ntraceLineCount: 20\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-ga.2026-06-08T00-00-00-02-00.da77e9988a2aa57d","runId":"run.medicaid-ex-parte-share-aug-2026-ga.2026-06-08T00-00-00-02-00.da77e9988a2aa57d","predictionId":"medicaid-ex-parte-share-aug-2026-ga","specId":"spec.medicaid-ex-parte-share-aug-2026-ga","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 10.7, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 83.6, 80% interval [78.2, 88.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-ga\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-ga.2026-06-28T00-33-02Z.medicaid-ex-parte-share-aug-2026-ga-thesis-analyst-fast-2026-06-28t00-33-02z.da77e9988a2aa57d","runId":"run.medicaid-ex-parte-share-aug-2026-ga.2026-06-28T00-33-02Z.medicaid-ex-parte-share-aug-2026-ga-thesis-analyst-fast-2026-06-28t00-33-02z.da77e9988a2aa57d","predictionId":"medicaid-ex-parte-share-aug-2026-ga","specId":"spec.medicaid-ex-parte-share-aug-2026-ga","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: Read the local official-source-derived Georgia historical context for this exact CMS series.","Base-rate/reference class: the most relevant outside view is Georgia's own recent first-print run for this CMS eligibility-processing series. The five observed points average 80.1 percent, the latest three average 81.6 percent, and the latest inspected value is 81.6 percent, so latest-value persistence with modest trend continuation is the prior."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Tool call: Inspected the registered CMS Medicaid PI target and local ledger identity fields for the Georgia August 2026 ex parte renewal-share resolver.","Tool result: Fetched official release context that data.Medicaid.gov is updated monthly; inspected CMS page context listed Preliminary March 2026 data and June 26, 2026 as the current update date for related February 2026 and March 2026 entries."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is a Georgia state row, not a national weighted average: the original first-publication August 2026 reporting-period row in the CMS eligibility processing dataset. The target is the share of completed Medicaid renewals processed ex parte, reported in percent and rounded to one decimal.","Tool call: Checked CMS Medicaid release vehicle context preserved for this data family."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 10.7, distribution present, forecast step count 1.","evidence":["Prior/update/interval: prior model is Georgia latest-value persistence with damped local trend, using five inspected observations from 2025-07, 2025-09, 2025-11, 2026-01, and 2026-02. Starting from latest inspected 81.6 percent, I add +1.4 pp for the 2025-to-early-2026 improvement signal and +0.6 pp for CMS compliance and continued automation drift, yielding 83.6. The 80% interval is calibrated from realized first-print movements and widened for the six-month horizon, renewal-cohort mix, and limited skipped-month sample, giving 78.2 to 88.9.","Counter-consideration: the forecast could be too high if the 2026-01 and 2026-02 values already represent Georgia's practical ceiling or if August has a manual-heavy renewal cohort. Upside outside the interval would require a durable system or data-match improvement pushing the first print above 88.9 percent; downside outside the interval would require a data-source outage, eligibility-system issue, reporting break, or cohort mix pushing the share below 78.2 percent."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, and mechanism: Georgia is already a high ex parte performer, so ceiling effects matter. The July-to-January improvement supports a mild upward update, but the February dip and high starting level argue against extrapolating the full 2025 trend through August.","Review disposition: accepted the optional resolver-clarity suggestion by naming the numerator and denominator concepts in the resolution rule. The 2026-02 point remains labeled latest inspected rather than first-print because the available draft evidence did not prove first-print vintage for that point."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, and mechanism: Georgia is already a high ex parte performer, so ceiling effects matter. The July-to-January improvement supports a mild upward update, but the February dip and high starting level argue against extrapolating the full 2025 trend through August."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for Georgia Medicaid ex parte renewal share, August 2026","Tool result: Fetched canonical slug medicaid-ex-parte-share-aug-2026-ga, unit percent, registered resolutionDate 2026-12-15, dataset id 5abea2e0-3f8e-4b49-a50d-d63d5fd9103c, and dataPointId cms.medicaid_pi.ex_parte_renewal_share.ga.aug_2026."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-ga\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-12-15\ntraceLineCount: 20\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-hi.2026-06-08T00-00-00-02-00.0ddc8bde6bafd838","runId":"run.medicaid-ex-parte-share-aug-2026-hi.2026-06-08T00-00-00-02-00.0ddc8bde6bafd838","predictionId":"medicaid-ex-parte-share-aug-2026-hi","specId":"spec.medicaid-ex-parte-share-aug-2026-hi","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 24.3, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 63.2, 80% interval [51.1, 75.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-hi\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-hi.2026-06-28T00-35-06Z.medicaid-ex-parte-share-aug-2026-hi-thesis-analyst-fast-2026-06-28t00-35-06z.d120effcc5ba62d3","runId":"run.medicaid-ex-parte-share-aug-2026-hi.2026-06-28T00-35-06Z.medicaid-ex-parte-share-aug-2026-hi-thesis-analyst-fast-2026-06-28t00-35-06z.d120effcc5ba62d3","predictionId":"medicaid-ex-parte-share-aug-2026-hi","specId":"spec.medicaid-ex-parte-share-aug-2026-hi","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: Read the local CMS-source-derived Hawaii historical context for this exact eligibility-processing series.","Base-rate/reference class: the closest outside view is Hawaii's own recent CMS eligibility-processing history. The five inspected sparse observations average 80.7 percent, while the latest three average 78.4 percent and the latest value is 70.5 percent, so the prior is latest-value persistence with partial mean reversion rather than a straight extrapolation of the latest drop."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Tool call: Inspected the registered CMS Medicaid PI target and ledger identity fields for the Hawaii August 2026 ex parte renewal-share resolver.","Tool call: Checked same-family CMS release context preserved in local official-source-derived records."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is a Hawaii state row, not a national weighted average: the original first-publication August 2026 reporting-period row in the CMS eligibility processing dataset. The target is the share of completed Medicaid renewals processed ex parte, reported in percent and rounded to one decimal.","Tool call: Checked same-family CMS release context preserved in local official-source-derived records."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 28, distribution present, forecast step count 1.","evidence":["Prior/update/interval: prior model is Hawaii latest-value persistence with partial mean reversion, using five inspected sparse observations from 2025-07, 2025-09, 2025-11, 2026-01, and 2026-02. Starting from latest inspected 70.5 percent, I subtract 3.0 pp for negative short-run momentum, add 0.5 pp for mean reversion toward the 78.4 percent latest-three average, and use 68.0 as the rounded point. The 80% interval uses a 14.0 pp half-width based on realized large first-print moves in this sparse sample, widened for the six-month horizon and cohort mix, giving 54.0 to 82.0.","Historical mean = (91.4 + 76.8 + 85.5 + 79.3 + 70.5) / 5 = 80.7 percent; latest-three mean = (85.5 + 79.3 + 70.5) / 3 = 78.4 percent. Point calculation: 70.5 - 3.0 momentum adjustment + 0.5 mean-reversion adjustment = 68.0 percent. 80% interval calculation: center 68.0 with 14.0 pp half-width, yielding 54.0 to 82.0 after one-decimal-compatible rounding."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Computed recent Hawaii level and momentum from the inspected sample.","Level, momentum, and mechanism: the level is below Hawaii's recent average, and the latest move is negative. But the series has large renewal-cohort swings, including a rebound from 76.8 to 85.5 in late 2025, so I avoid carrying the full February weakness linearly into August."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Level, momentum, and mechanism: the level is below Hawaii's recent average, and the latest move is negative. But the series has large renewal-cohort swings, including a rebound from 76.8 to 85.5 in late 2025, so I avoid carrying the full February weakness linearly into August."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for Hawaii Medicaid ex parte renewal share, August 2026","Tool result: Fetched canonical slug medicaid-ex-parte-share-aug-2026-hi, unit percent, registered resolutionDate 2026-12-15, dataset id 5abea2e0-3f8e-4b49-a50d-d63d5fd9103c, and dataPointId cms.medicaid_pi.ex_parte_renewal_share.hi.aug_2026."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-hi\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-12-15\ntraceLineCount: 19\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-ia.2026-06-08T00-00-00-02-00.6ad85cf065fe7560","runId":"run.medicaid-ex-parte-share-aug-2026-ia.2026-06-08T00-00-00-02-00.6ad85cf065fe7560","predictionId":"medicaid-ex-parte-share-aug-2026-ia","specId":"spec.medicaid-ex-parte-share-aug-2026-ia","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 28, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 78.3, 80% interval [64.3, 92.3]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-ia\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-ia.2026-06-28T00-39-47Z.medicaid-ex-parte-share-aug-2026-ia-thesis-analyst-fast-2026-06-28t00-39-47z.58363cc1a37e8b41","runId":"run.medicaid-ex-parte-share-aug-2026-ia.2026-06-28T00-39-47Z.medicaid-ex-parte-share-aug-2026-ia-thesis-analyst-fast-2026-06-28t00-39-47z.58363cc1a37e8b41","predictionId":"medicaid-ex-parte-share-aug-2026-ia","specId":"spec.medicaid-ex-parte-share-aug-2026-ia","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: Read local official-source-derived Iowa historical context for this CMS series, excluding the existing catalog point and interval from evidentiary use.","Tool call: Checked CMS monthly-release context preserved in local prior official lookups for this data family."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Tool call: Inspected the canonical ledger target for the Iowa August 2026 CMS Medicaid eligibility-processing ex parte renewal-share target.","Tool call: Read local official-source-derived Iowa historical context for this CMS series, excluding the existing catalog point and interval from evidentiary use."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is a single Iowa state row, not a national weighted average: the original first-publication August 2026 reporting-period row in CMS State Medicaid and CHIP Eligibility Processing Data. The target is the share of completed Medicaid renewals processed ex parte, in percent rounded to one decimal.","Tool result: Fetched Iowa original first-print ex parte renewal shares: 2025-07 = 61.8 percent, 2025-09 = 60.8 percent, 2025-11 = 71.2 percent, 2026-01 = 85.3 percent, and 2026-02 = 72.7 percent."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 28, distribution present, forecast step count 1.","evidence":["Tool call: Read local official-source-derived Iowa historical context for this CMS series, excluding the existing catalog point and interval from evidentiary use.","Prior/update/interval: prior model is Iowa latest-value persistence blended with a five-point Iowa mean and a damped local trend, using the limited observed original first-print subset from 2025-07, 2025-09, 2025-11, 2026-01, and 2026-02. I start at latest usable 72.7, add +3.0 pp for persistence of the higher early-2026 level versus the 2025 average, and add a subjective +2.3 pp damped drift for possible continued automation/compliance improvement, giving 78.0. The 80% interval uses realized first-print dispersion, widened for six-month horizon, renewal-cohort risk, and missing-month uncertainty, while keeping the upper tail below 100 percent."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base-rate/reference class: the relevant outside view is Iowa's own recent original-submission first-print run, because the target resolves a single state row. The five inspected values average 70.4 percent, span 60.8 to 85.3 percent, and have a latest usable value of 72.7 percent.","Level, momentum, and mechanism: Iowa moved from around 61 percent in mid-2025 to a much higher January 2026 print before falling to 72.7 percent in February. I treat the January high as partly cohort or reporting composition, but the early-2026 level still suggests Iowa's baseline has shifted above the 2025 low-60s readings."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, and mechanism: Iowa moved from around 61 percent in mid-2025 to a much higher January 2026 print before falling to 72.7 percent in February. I treat the January high as partly cohort or reporting composition, but the early-2026 level still suggests Iowa's baseline has shifted above the 2025 low-60s readings.","Prior/update/interval: prior model is Iowa latest-value persistence blended with a five-point Iowa mean and a damped local trend, using the limited observed original first-print subset from 2025-07, 2025-09, 2025-11, 2026-01, and 2026-02. I start at latest usable 72.7, add +3.0 pp for persistence of the higher early-2026 level versus the 2025 average, and add a subjective +2.3 pp damped drift for possible continued automation/compliance improvement, giving 78.0. The 80% interval uses realized first-print dispersion, widened for six-month horizon, renewal-cohort risk, and missing-month uncertainty, while keeping the upper tail below 100 percent."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for Iowa Medicaid ex parte renewal share, August 2026","Tool result: Fetched canonical slug medicaid-ex-parte-share-aug-2026-ia, unit percent, registered resolutionDate 2026-12-15, dataset id 5abea2e0-3f8e-4b49-a50d-d63d5fd9103c, datastore id 6165f45b-ca93-5bb5-9d06-db29c692a360, and dataPointId cms.medicaid_pi.ex_parte_renewal_share.ia.aug_2026."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-ia\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-12-15\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-id.2026-06-08T00-00-00-02-00.38608f0826f052d7","runId":"run.medicaid-ex-parte-share-aug-2026-id.2026-06-08T00-00-00-02-00.38608f0826f052d7","predictionId":"medicaid-ex-parte-share-aug-2026-id","specId":"spec.medicaid-ex-parte-share-aug-2026-id","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 15, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 98, 80% interval [84, 99]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-id\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-id.2026-06-28T00-41-31Z.medicaid-ex-parte-share-aug-2026-id-thesis-analyst-fast-2026-06-28t00-41-31z.cce545e0c698eaf0","runId":"run.medicaid-ex-parte-share-aug-2026-id.2026-06-28T00-41-31Z.medicaid-ex-parte-share-aug-2026-id-thesis-analyst-fast-2026-06-28t00-41-31z.cce545e0c698eaf0","predictionId":"medicaid-ex-parte-share-aug-2026-id","specId":"spec.medicaid-ex-parte-share-aug-2026-id","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: Read local official-source-derived Idaho historical context for this CMS series.","Base-rate/reference class: the relevant outside view is Idaho's own recent original-submission first-print run, because this resolves a single state row. The five inspected values average 81.8 percent, span 70.9 to 99.6 percent, and have a latest value of 99.6 percent; intervening months were unavailable in the inspected context rather than intentionally excluded."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Tool call: Inspected the canonical ledger target for the Idaho August 2026 CMS Medicaid eligibility-processing ex parte renewal-share target.","Tool call: Checked CMS monthly reports release page for the official release vehicle and latest visible update cadence."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is an Idaho state row, not a national weighted average: the original first-publication August 2026 reporting-period row in CMS State Medicaid and CHIP Eligibility Processing Data. The target is the share of completed Medicaid renewals processed ex parte, in percent rounded to one decimal.","Tool call: Checked CMS monthly reports release page for the official release vehicle and latest visible update cadence."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 21.4, distribution present, forecast step count 1.","evidence":["Prior/update/interval: prior model is latest-value persistence blended with a five-point Idaho mean and a ceiling-aware damped trend, using observed original first-print values from 2025-07, 2025-09, 2025-11, 2026-01, and 2026-02. I start at latest 99.6, subtract 3.4 pp for regression from an extreme near-ceiling print, subtract 2.0 pp for renewal-cohort volatility, and keep a +0.0 pp net policy/system improvement adjustment because the latest jump may be partly durable, giving 94.2. The 80% interval uses realized first-print dispersion: recent range 28.7 pp and mean absolute adjacent step about 12.9 pp, widened over the six-month horizon and made asymmetric by the 100 percent ceiling.","Counter-consideration: upside outside the interval is limited but would occur if Idaho's February near-100 percent processing reflects a stable automated renewal process and August's cohort remains data-match friendly. Downside outside the interval would require the February result to be a one-off, a manual-heavy renewal cohort, a data-source outage, eligibility-system issue, or a reporting break pushing the first print below 78.4 percent."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base-rate/reference class: the relevant outside view is Idaho's own recent original-submission first-print run, because this resolves a single state row. The five inspected values average 81.8 percent, span 70.9 to 99.6 percent, and have a latest value of 99.6 percent; intervening months were unavailable in the inspected context rather than intentionally excluded.","Level, momentum, and mechanism: the latest February 2026 value is almost at the ceiling, which could reflect a real data-match or system improvement, but Idaho's recent history also includes a drop from 83.2 percent to 70.9 percent before the jump to 99.6 percent. I therefore treat the latest value as highly informative but not fully persistent."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, and mechanism: the latest February 2026 value is almost at the ceiling, which could reflect a real data-match or system improvement, but Idaho's recent history also includes a drop from 83.2 percent to 70.9 percent before the jump to 99.6 percent. I therefore treat the latest value as highly informative but not fully persistent.","Counter-consideration: upside outside the interval is limited but would occur if Idaho's February near-100 percent processing reflects a stable automated renewal process and August's cohort remains data-match friendly. Downside outside the interval would require the February result to be a one-off, a manual-heavy renewal cohort, a data-source outage, eligibility-system issue, or a reporting break pushing the first print below 78.4 percent."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for Idaho Medicaid ex parte renewal share, August 2026","Tool result: Fetched canonical slug medicaid-ex-parte-share-aug-2026-id, unit percent, registered resolutionDate 2026-12-15, dataset id 5abea2e0-3f8e-4b49-a50d-d63d5fd9103c, and dataPointId cms.medicaid_pi.ex_parte_renewal_share.id.aug_2026."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-id\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-12-15\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-il.2026-06-08T00-00-00-02-00.1842587c681d3a06","runId":"run.medicaid-ex-parte-share-aug-2026-il.2026-06-08T00-00-00-02-00.1842587c681d3a06","predictionId":"medicaid-ex-parte-share-aug-2026-il","specId":"spec.medicaid-ex-parte-share-aug-2026-il","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 16.6, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 81.7, 80% interval [73.4, 90]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-il\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-il.2026-06-28T00-44-04Z.medicaid-ex-parte-share-aug-2026-il-thesis-analyst-fast-2026-06-28t00-44-04z.1842587c681d3a06","runId":"run.medicaid-ex-parte-share-aug-2026-il.2026-06-28T00-44-04Z.medicaid-ex-parte-share-aug-2026-il-thesis-analyst-fast-2026-06-28t00-44-04z.1842587c681d3a06","predictionId":"medicaid-ex-parte-share-aug-2026-il","specId":"spec.medicaid-ex-parte-share-aug-2026-il","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: Read local official-source-derived Illinois historical context for this CMS ex parte renewal-share series.","Base-rate/reference class: the relevant outside view is Illinois's own recent original-submission first-print run for this CMS state-row metric. The five inspected values average 80.7 percent, span 74.7 to 84.3 percent, and the latest inspected value is 81.0 percent."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Tool call: Inspected the canonical ledger target for the Illinois August 2026 CMS Medicaid eligibility-processing ex parte renewal-share target.","Tool call: Checked CMS monthly reports release context preserved in official-source run artifacts for the Medicaid eligibility-processing data family."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is an Illinois state row, not a national weighted average: the original first-publication August 2026 reporting-period row in CMS State Medicaid and CHIP Eligibility Processing Data. The target is completed Medicaid renewals processed ex parte divided by completed Medicaid renewals, reported as a percent rounded to one decimal.","Tool call: Checked CMS monthly reports release context preserved in official-source run artifacts for the Medicaid eligibility-processing data family."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 16.6, distribution present, forecast step count 1.","evidence":["Prior/update/interval: prior model is latest-value persistence blended with the five-point Illinois mean, with only a small operational-drift adjustment because five observations are too sparse for a meaningful fitted trend. The baseline blend is 70 percent latest value of 81.0 and 30 percent five-point mean of 80.7, giving 80.9; I then add +0.8 pp for mild CMS compliance pressure, systems learning, and the possibility that August's cohort is not as manual-heavy as the low 2025-09 print, giving 81.7. The 80% interval uses realized original first-print dispersion: recent range 9.6 pp and mean absolute adjacent step 4.6 pp, widened to an 8.3 pp half-width over the six-month horizon for cohort mix and reporting noise.","Counter-consideration: upside outside the interval would require a durable Illinois data-match or workflow improvement plus an August cohort suited to automated renewals, pushing the first print above 90.0 percent. Downside outside the interval would require a manual-heavy cohort, data-source outage, eligibility-system issue, or reporting break pushing the share below 73.4 percent."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level and momentum: Illinois is already at a high administrative-processing level but not close enough to 100 percent for ceiling effects to dominate. The July-to-February net movement is only +0.7 percentage point, while the intervening swings show renewal-cohort composition and reporting mix rather than a clean trend.","Mechanism split: durable level depends on data matches and eligibility-system workflow. Mild upward pressure comes from continued CMS compliance focus and operational learning after unwinding, but one-off denominator/numerator mix by renewal cohort can easily move the monthly first print several percentage points."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level and momentum: Illinois is already at a high administrative-processing level but not close enough to 100 percent for ceiling effects to dominate. The July-to-February net movement is only +0.7 percentage point, while the intervening swings show renewal-cohort composition and reporting mix rather than a clean trend.","Mechanism split: durable level depends on data matches and eligibility-system workflow. Mild upward pressure comes from continued CMS compliance focus and operational learning after unwinding, but one-off denominator/numerator mix by renewal cohort can easily move the monthly first print several percentage points."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for Illinois Medicaid ex parte renewal share, August 2026","Tool result: Fetched canonical slug medicaid-ex-parte-share-aug-2026-il, unit percent, registered resolutionDate 2026-12-15, dataset id 5abea2e0-3f8e-4b49-a50d-d63d5fd9103c, and dataPointId cms.medicaid_pi.ex_parte_renewal_share.il.aug_2026."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-il\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-12-15\ntraceLineCount: 19\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-in.2026-06-08T00-00-00-02-00.85d10fbf92c55c06","runId":"run.medicaid-ex-parte-share-aug-2026-in.2026-06-08T00-00-00-02-00.85d10fbf92c55c06","predictionId":"medicaid-ex-parte-share-aug-2026-in","specId":"spec.medicaid-ex-parte-share-aug-2026-in","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 28, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 62.8, 80% interval [48.8, 76.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-in\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-in.2026-06-28T00-46-54Z.medicaid-ex-parte-share-aug-2026-in-thesis-analyst-fast-2026-06-28t00-46-54z.ca08fbec699b7b38","runId":"run.medicaid-ex-parte-share-aug-2026-in.2026-06-28T00-46-54Z.medicaid-ex-parte-share-aug-2026-in-thesis-analyst-fast-2026-06-28t00-46-54z.ca08fbec699b7b38","predictionId":"medicaid-ex-parte-share-aug-2026-in","specId":"spec.medicaid-ex-parte-share-aug-2026-in","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base-rate/reference class: the best outside view is Indiana's own recent post-unwinding CMS ex parte renewal-share history. The inspected official-source-derived sample mean is 64.0 percent, the latest value is 66.7 percent, and the recent range is wide at 47.4 to 71.5 percent, so I anchor on state-level persistence rather than national convergence.","Prior/update/interval: prior model is latest-value persistence blended with the five-point state mean, using inspected official-source-derived observations from 2025-07, 2025-09, 2025-11, 2026-01, and 2026-02. Starting from 66.7, I subtract 1.2 pp for negative latest movement and mean reversion, add 0.2 pp for CMS compliance and automation pressure, and subtract 1.2 pp as a judgmental volatility discount toward the lower sample mean, giving 64.5. The 80% interval uses about 1.5 times the 9.8 pp sample standard deviation, close to the 13.0 pp mean absolute adjacent change plus extra six-month horizon risk, giving asymmetric rounded bounds of 49.5 to 78.5."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Tool call: Checked the canonical ledger target and CMS resolver identity for the Indiana August 2026 ex parte renewal-share target.","Tool call: Opened the official Medicaid.gov monthly reports page for current release vehicle and timing context."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is an Indiana state row, not a national weighted average: the original first-publication August 2026 reporting-period row in the CMS eligibility processing dataset. The target is the share of completed Medicaid renewals processed ex parte, reported in percent and rounded to one decimal.","Tool call: Opened the official Medicaid.gov monthly reports page for current release vehicle and timing context."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 29, distribution present, forecast step count 1.","evidence":["Tool call: Read local official-source-derived Indiana history for this exact CMS ex parte renewal-share series, without using the existing catalog point or interval as evidence.","Level, momentum, and mechanism: Indiana appears to be a mid-performing state with meaningful month-to-month cohort effects. The September 2025 trough argues for a wide interval, while the recovery to 70.9 in January 2026 and 66.7 in February 2026 argues against treating the September low as the new level."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, and mechanism: Indiana appears to be a mid-performing state with meaningful month-to-month cohort effects. The September 2025 trough argues for a wide interval, while the recovery to 70.9 in January 2026 and 66.7 in February 2026 argues against treating the September low as the new level.","Prior/update/interval: prior model is latest-value persistence blended with the five-point state mean, using inspected official-source-derived observations from 2025-07, 2025-09, 2025-11, 2026-01, and 2026-02. Starting from 66.7, I subtract 1.2 pp for negative latest movement and mean reversion, add 0.2 pp for CMS compliance and automation pressure, and subtract 1.2 pp as a judgmental volatility discount toward the lower sample mean, giving 64.5. The 80% interval uses about 1.5 times the 9.8 pp sample standard deviation, close to the 13.0 pp mean absolute adjacent change plus extra six-month horizon risk, giving asymmetric rounded bounds of 49.5 to 78.5."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: prior model is latest-value persistence blended with the five-point state mean, using inspected official-source-derived observations from 2025-07, 2025-09, 2025-11, 2026-01, and 2026-02. Starting from 66.7, I subtract 1.2 pp for negative latest movement and mean reversion, add 0.2 pp for CMS compliance and automation pressure, and subtract 1.2 pp as a judgmental volatility discount toward the lower sample mean, giving 64.5. The 80% interval uses about 1.5 times the 9.8 pp sample standard deviation, close to the 13.0 pp mean absolute adjacent change plus extra six-month horizon risk, giving asymmetric rounded bounds of 49.5 to 78.5.","Resolution-date note: the ledger target uses 2026-12-15 for the August 2026 original-vintage print. The official CMS page verified the monthly data.Medicaid.gov release vehicle and current June 26, 2026 update, but I did not find an official future August 2026 placeholder dated December 15, 2026 in the checked public page; I keep the canonical target date and bind resolution to the first official CMS dataset print."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for Indiana Medicaid ex parte renewal share, August 2026","Tool result: Fetched canonical slug medicaid-ex-parte-share-aug-2026-in, unit percent, registered resolutionDate 2026-12-15, dataset id 5abea2e0-3f8e-4b49-a50d-d63d5fd9103c, and dataPointId cms.medicaid_pi.ex_parte_renewal_share.in.aug_2026."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-in\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2026-12-15\ntraceLineCount: 20\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-ks.2026-06-08T00-00-00-02-00.4ab8258321db0872","runId":"run.medicaid-ex-parte-share-aug-2026-ks.2026-06-08T00-00-00-02-00.4ab8258321db0872","predictionId":"medicaid-ex-parte-share-aug-2026-ks","specId":"spec.medicaid-ex-parte-share-aug-2026-ks","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 14.6, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 56.4, 80% interval [49.1, 63.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-ks\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-ks.2026-07-01T05-19-30Z.medicaid-ex-parte-share-aug-2026-ks-thesis-analyst-fast-2026-07-01t05-19-30z.f4b55f287914ca2a","runId":"run.medicaid-ex-parte-share-aug-2026-ks.2026-07-01T05-19-30Z.medicaid-ex-parte-share-aug-2026-ks-thesis-analyst-fast-2026-07-01t05-19-30z.f4b55f287914ca2a","predictionId":"medicaid-ex-parte-share-aug-2026-ks","specId":"spec.medicaid-ex-parte-share-aug-2026-ks","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: Read the official-source-derived Kansas historical context for this exact CMS series from the public repository catalog and prior public Thesis trace.","Tool call: Computed recent Kansas movement and base-rate statistics from the inspected sample."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Tool call: Checked the CMS monthly Medicaid and CHIP reports page for the official release vehicle and latest public update evidence.","Tool result: Fetched official CMS page evidence: Preliminary March 2026 Applications, Eligibility, and Enrollment Data was listed with Last Updated June 26, 2026; Updated February 2026 and Preliminary February 2026 entries were also listed with Last Updated June 26, 2026; the page states data.Medicaid.gov is updated monthly."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The resolver is Kansas's state row, not a national weighted average: the original first-publication August 2026 reporting-period row in CMS State Medicaid and CHIP Eligibility Processing Data. The target is the share of completed Medicaid renewals processed ex parte, in percent rounded to one decimal.","Tool call: Checked the CMS monthly Medicaid and CHIP reports page for the official release vehicle and latest public update evidence."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 20.4, distribution present, forecast step count 1.","evidence":["Prior/update/interval: prior model is latest-value persistence blended with Kansas's five-point first-print mean and a damped negative local trend, using the observed sample 2025-07, 2025-09, 2025-11, 2026-01, and 2026-02. Starting from latest 58.3, I subtract 1.5 pp for the recent two-print downtrend and 0.4 pp for renewal-cohort volatility, with no additional policy lift beyond persistence, giving 56.4. The 80% interval uses realized Kansas first-print dispersion: an 18.6 pp range and 7.2 pp mean absolute adjacent move, widened over the six-month horizon to asymmetric bounds of 46.8 to 67.2.","Historical mean = (49.7 + 62.3 + 68.3 + 62.9 + 58.3) / 5 = 60.3 percent. Recent adjacent changes were +12.6, +6.0, -5.4, and -4.6 pp. Point calculation: latest 58.3 - 1.5 pp downtrend adjustment - 0.4 pp cohort-volatility adjustment = 56.4. Interval calculation: center 56.4, lower half-width 9.6 pp and upper half-width 10.8 pp from observed Kansas dispersion and remaining-month uncertainty, yielding 46.8 to 67.2 after rounding."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, and mechanism: Kansas improved sharply from July to November 2025, then gave back part of the gain in January and February 2026. I treat the latest decline as informative because ex parte performance is operational and cohort-sensitive, but I do not extrapolate a collapse because the latest level remains above the July 2025 low and CMS compliance pressure favors continued automation."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, and mechanism: Kansas improved sharply from July to November 2025, then gave back part of the gain in January and February 2026. I treat the latest decline as informative because ex parte performance is operational and cohort-sensitive, but I do not extrapolate a collapse because the latest level remains above the July 2025 low and CMS compliance pressure favors continued automation.","Historical mean = (49.7 + 62.3 + 68.3 + 62.9 + 58.3) / 5 = 60.3 percent. Recent adjacent changes were +12.6, +6.0, -5.4, and -4.6 pp. Point calculation: latest 58.3 - 1.5 pp downtrend adjustment - 0.4 pp cohort-volatility adjustment = 56.4. Interval calculation: center 56.4, lower half-width 9.6 pp and upper half-width 10.8 pp from observed Kansas dispersion and remaining-month uncertainty, yielding 46.8 to 67.2 after rounding."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for Kansas Medicaid ex parte renewal share, August 2026","Tool result: Fetched canonical slug medicaid-ex-parte-share-aug-2026-ks, unit percent, resolutionDate 2026-12-15, dataset id 5abea2e0-3f8e-4b49-a50d-d63d5fd9103c, and dataPointId cms.medicaid_pi.ex_parte_renewal_share.ks.aug_2026."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-ks\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-12-15\ntraceLineCount: 20\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-ky.2026-06-08T00-00-00-02-00.4c13b6cb619fac9d","runId":"run.medicaid-ex-parte-share-aug-2026-ky.2026-06-08T00-00-00-02-00.4c13b6cb619fac9d","predictionId":"medicaid-ex-parte-share-aug-2026-ky","specId":"spec.medicaid-ex-parte-share-aug-2026-ky","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 14.4, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 92.2, 80% interval [84.6, 99]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-ky\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-ky.2026-07-01T05-21-15Z.medicaid-ex-parte-share-aug-2026-ky-thesis-analyst-fast-2026-07-01t05-21-15z.997811c5cc2282bf","runId":"run.medicaid-ex-parte-share-aug-2026-ky.2026-07-01T05-21-15Z.medicaid-ex-parte-share-aug-2026-ky-thesis-analyst-fast-2026-07-01t05-21-15z.997811c5cc2282bf","predictionId":"medicaid-ex-parte-share-aug-2026-ky","specId":"spec.medicaid-ex-parte-share-aug-2026-ky","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base-rate/reference-class anchor: the most relevant outside view is Kentucky's own recent original-submission first-print run for this CMS eligibility-processing series. The level is high and stable enough that latest-value persistence near 90 percent is a stronger prior than a national or multi-state average.","Prior/update/interval: prior model is Kentucky latest-value persistence blended with the latest-three mean, using the five inspected original first-print points from 2025-07, 2025-09, 2025-11, 2026-01, and 2026-02. Starting from latest 89.9 percent, I add +1.3 pp for the latest-three mean being 91.6 percent, +0.8 pp for high-level persistence and CMS compliance pressure, and 0.0 pp for the ceiling-constrained trend after the January dip, giving 92.0 after rounding. The 80% interval starts from realized first-print dispersion of 11.0 pp and mean adjacent move of 4.3 pp, widened for missing March-August first prints and skewed downward because upside is capped near 100."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Tool call: Checked the CMS Medicaid.gov monthly reports page for the official release vehicle and current public update pattern.","Tool result: Fetched official CMS monthly page evidence: Preliminary March 2026 Applications, Eligibility, and Enrollment Data was listed; March 2026, February 2026, January 2026, December 2025, November 2025, October 2025, September 2025, August 2025, and July 2025 entries were Last Updated June 26, 2026; the page states data.Medicaid.gov is updated monthly."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is a Kentucky state row, not a national weighted average: the original first-publication August 2026 reporting-period row in CMS State Medicaid and CHIP Eligibility Processing Data. The target is the share of completed Medicaid renewals processed ex parte, reported in percent and rounded to one decimal.","Tool call: Checked the CMS Medicaid.gov monthly reports page for the official release vehicle and current public update pattern."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 15.8, distribution present, forecast step count 1.","evidence":["Tool call: Read public generated official-source-derived Kentucky history for this exact CMS ex parte renewal-share series, excluding the existing catalog point and interval from evidence.","Prior/update/interval: prior model is Kentucky latest-value persistence blended with the latest-three mean, using the five inspected original first-print points from 2025-07, 2025-09, 2025-11, 2026-01, and 2026-02. Starting from latest 89.9 percent, I add +1.3 pp for the latest-three mean being 91.6 percent, +0.8 pp for high-level persistence and CMS compliance pressure, and 0.0 pp for the ceiling-constrained trend after the January dip, giving 92.0 after rounding. The 80% interval starts from realized first-print dispersion of 11.0 pp and mean adjacent move of 4.3 pp, widened for missing March-August first prints and skewed downward because upside is capped near 100."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, and mechanism: Kentucky has already reached a high-ex-parte regime, with 2025-11 at 95.3 percent and February 2026 at 89.9 percent. Momentum is mildly positive from July 2025 to February 2026, but the January 2026 pullback shows the path is cohort-sensitive rather than a smooth trend to 100 percent.","Prior/update/interval: prior model is Kentucky latest-value persistence blended with the latest-three mean, using the five inspected original first-print points from 2025-07, 2025-09, 2025-11, 2026-01, and 2026-02. Starting from latest 89.9 percent, I add +1.3 pp for the latest-three mean being 91.6 percent, +0.8 pp for high-level persistence and CMS compliance pressure, and 0.0 pp for the ceiling-constrained trend after the January dip, giving 92.0 after rounding. The 80% interval starts from realized first-print dispersion of 11.0 pp and mean adjacent move of 4.3 pp, widened for missing March-August first prints and skewed downward because upside is capped near 100."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, and mechanism: Kentucky has already reached a high-ex-parte regime, with 2025-11 at 95.3 percent and February 2026 at 89.9 percent. Momentum is mildly positive from July 2025 to February 2026, but the January 2026 pullback shows the path is cohort-sensitive rather than a smooth trend to 100 percent."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for Kentucky Medicaid ex parte renewal share, August 2026","Tool result: Fetched canonical slug medicaid-ex-parte-share-aug-2026-ky, unit percent, resolutionDate 2026-12-15, dataset id 5abea2e0-3f8e-4b49-a50d-d63d5fd9103c, datastore id 6165f45b-ca93-5bb5-9d06-db29c692a360, and dataPointId cms.medicaid_pi.ex_parte_renewal_share.ky.aug_2026."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-ky\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-12-15\ntraceLineCount: 19\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-la.2026-06-08T00-00-00-02-00.ac9485376da74a28","runId":"run.medicaid-ex-parte-share-aug-2026-la.2026-06-08T00-00-00-02-00.ac9485376da74a28","predictionId":"medicaid-ex-parte-share-aug-2026-la","specId":"spec.medicaid-ex-parte-share-aug-2026-la","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 28, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 66.7, 80% interval [52.7, 80.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-la\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-la.2026-07-01T05-23-05Z.medicaid-ex-parte-share-aug-2026-la-thesis-analyst-fast-2026-07-01t05-23-05z.47311b3d7435f4e3","runId":"run.medicaid-ex-parte-share-aug-2026-la.2026-07-01T05-23-05Z.medicaid-ex-parte-share-aug-2026-la-thesis-analyst-fast-2026-07-01t05-23-05z.47311b3d7435f4e3","predictionId":"medicaid-ex-parte-share-aug-2026-la","specId":"spec.medicaid-ex-parte-share-aug-2026-la","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: Read local public-repository, official-source-derived Louisiana historical context for this exact CMS series; existing catalog point and interval were ignored as forecast evidence.","Tool result: Fetched shell network result code 6 with 0 downloaded bytes, so direct API confirmation was blocked in this sandbox; the 5 Louisiana historical shares above come from local public official-source-derived repository artifacts."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Tool call: Opened the official Medicaid.gov monthly Medicaid and CHIP application, eligibility determination, and enrollment reports page for release vehicle and current-update evidence.","Tool result: Fetched official page evidence: Beginning with the October 2018 report, monthly enrollment data are available only on data.Medicaid.gov; the page says data.Medicaid.gov is updated monthly; Preliminary February 2026 Applications, Eligibility, and Enrollment Data was Last Updated May 29, 2026; Updated January 2026 and Preliminary January 2026 entries were also Last Updated May 29, 2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is a Louisiana state row, not a national weighted average: the original first-publication August 2026 reporting-period row in the CMS eligibility processing dataset. The target is the share of completed Medicaid renewals processed ex parte, reported in percent and rounded to one decimal.","Tool call: Opened the official Medicaid.gov monthly Medicaid and CHIP application, eligibility determination, and enrollment reports page for release vehicle and current-update evidence."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 28.3, distribution present, forecast step count 1.","evidence":["Tool call: Inspected the canonical ledger identity fields for the Louisiana August 2026 CMS Medicaid eligibility-processing ex parte renewal-share target, without using catalog point estimates or intervals as evidence.","Tool call: Read local public-repository, official-source-derived Louisiana historical context for this exact CMS series; existing catalog point and interval were ignored as forecast evidence."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base-rate/reference class: the most relevant outside view is Louisiana's own recent original-submission CMS eligibility-processing run because this resolves a single state row. The five inspected values average 69.7 percent, span 65.5 to 75.1 percent, and the latest inspected point is 69.8 percent.","Level, momentum, and mechanism: Louisiana is not near the 100 percent ceiling, so both improvement and deterioration remain plausible. The January spike to 75.1 followed by February at 69.8 looks more like renewal-cohort or processing volatility than a clean trend break; data-match coverage and eligibility-system operations remain the key mechanism."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: prior model is Louisiana latest-value persistence blended with a five-point state mean and damped local trend, using observed values from 2025-07, 2025-09, 2025-11, 2026-01, and 2026-02. Starting from latest 69.8, I subtract 1.4 pp for weak July-to-February drift and the January-to-February pullback, subtract 0.6 pp for August renewal-cohort/manual-processing risk, and subtract 0.4 pp because the recent mean does not confirm January's high as durable, yielding 67.4. The 80% interval starts from realized first-print dispersion, with 9.6 pp recent range and 5.3 pp mean absolute adjacent move, then widens over the six-month horizon to about 14 pp each side.","Historical mean = (71.9 + 65.5 + 66.1 + 75.1 + 69.8) / 5 = 69.7 percent. Observed adjacent changes were -6.4, +0.6, +9.0, and -5.3 pp, with mean absolute change 5.3 pp. Point calculation: 69.8 latest inspected value - 1.4 pp damped drift/pullback - 0.6 pp cohort risk - 0.4 pp mean-reversion adjustment = 67.4 percent. Interval calculation: center 67.4, lower half-width 14.2 pp and upper half-width 14.1 pp, yielding 53.2 to 81.5 after one-decimal rounding."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for Louisiana Medicaid ex parte renewal share, August 2026","Tool call: Inspected the canonical ledger identity fields for the Louisiana August 2026 CMS Medicaid eligibility-processing ex parte renewal-share target, without using catalog point estimates or intervals as evidence."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-la\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-12-15\ntraceLineCount: 20\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-ma.2026-06-08T00-00-00-02-00.bad95d3660250151","runId":"run.medicaid-ex-parte-share-aug-2026-ma.2026-06-08T00-00-00-02-00.bad95d3660250151","predictionId":"medicaid-ex-parte-share-aug-2026-ma","specId":"spec.medicaid-ex-parte-share-aug-2026-ma","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 27.8, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 77.4, 80% interval [63.5, 91.3]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-ma\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-ma.2026-07-01T05-25-13Z.medicaid-ex-parte-share-aug-2026-ma-thesis-analyst-fast-2026-07-01t05-25-13z.f34a2bf73a1bccd2","runId":"run.medicaid-ex-parte-share-aug-2026-ma.2026-07-01T05-25-13Z.medicaid-ex-parte-share-aug-2026-ma-thesis-analyst-fast-2026-07-01t05-25-13z.f34a2bf73a1bccd2","predictionId":"medicaid-ex-parte-share-aug-2026-ma","specId":"spec.medicaid-ex-parte-share-aug-2026-ma","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Tool call: Read local public-repository, official-source-derived Massachusetts historical context for this exact CMS series; existing catalog point and interval were ignored as forecast evidence.","Base-rate/reference class: the most relevant outside view is Massachusetts's own recent original-submission CMS eligibility-processing history. The five inspected values average 80.4 percent, the latest three average 81.6 percent, and the latest inspected value is 77.8 percent, so the prior is latest-value persistence with partial mean reversion rather than continuation of the January high."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 7 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Tool call: Opened the official Medicaid.gov monthly Medicaid and CHIP application, eligibility determination, and enrollment reports page for release vehicle and dated current-update evidence.","Tool result: Fetched official page evidence: monthly enrollment data are available only on data.Medicaid.gov beginning with the October 2018 report; data.Medicaid.gov is updated monthly; Preliminary February 2026 Applications, Eligibility, and Enrollment Data was Last Updated May 29, 2026; Updated January 2026 and Preliminary January 2026 entries were also Last Updated May 29, 2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is a Massachusetts state row, not a national total or weighted average: the original first-publication August 2026 reporting-period row in the CMS eligibility processing dataset. The target is the percent of completed Medicaid renewals processed ex parte, rounded to one decimal.","Tool call: Opened the official Medicaid.gov monthly Medicaid and CHIP application, eligibility determination, and enrollment reports page for release vehicle and dated current-update evidence."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 21.9, distribution present, forecast step count 1.","evidence":["Tool call: Inspected the canonical ledger identity fields for the Massachusetts August 2026 CMS Medicaid eligibility-processing ex parte renewal-share target, without using catalog point estimates or intervals as evidence.","Tool call: Read local public-repository, official-source-derived Massachusetts historical context for this exact CMS series; existing catalog point and interval were ignored as forecast evidence."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, and mechanism: Massachusetts appears to operate around a high but not ceiling-level ex parte share. The January 2026 value of 84.6 followed by February at 77.8 looks like cohort or processing volatility, while data-match capacity and CMS compliance pressure support staying near the high-70s to low-80s.","Prior/update/interval: prior model is Massachusetts latest-value persistence blended with a five-point state mean, using observed values from 2025-07, 2025-09, 2025-11, 2026-01, and 2026-02. Starting from latest 77.8, I add +1.1 pp for mean reversion toward the 80.4 percent sample average and +0.3 pp for continued automation/compliance pressure, yielding 79.2. The 80% interval uses realized first-print dispersion, with a 6.8 pp recent range and 3.8 pp mean absolute adjacent move, widened over the six-month horizon and renewal-cohort uncertainty to about -10.7/+11.2 pp."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, and mechanism: Massachusetts appears to operate around a high but not ceiling-level ex parte share. The January 2026 value of 84.6 followed by February at 77.8 looks like cohort or processing volatility, while data-match capacity and CMS compliance pressure support staying near the high-70s to low-80s.","Prior/update/interval: prior model is Massachusetts latest-value persistence blended with a five-point state mean, using observed values from 2025-07, 2025-09, 2025-11, 2026-01, and 2026-02. Starting from latest 77.8, I add +1.1 pp for mean reversion toward the 80.4 percent sample average and +0.3 pp for continued automation/compliance pressure, yielding 79.2. The 80% interval uses realized first-print dispersion, with a 6.8 pp recent range and 3.8 pp mean absolute adjacent move, widened over the six-month horizon and renewal-cohort uncertainty to about -10.7/+11.2 pp."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for Massachusetts Medicaid ex parte renewal share, August 2026","Tool call: Inspected the canonical ledger identity fields for the Massachusetts August 2026 CMS Medicaid eligibility-processing ex parte renewal-share target, without using catalog point estimates or intervals as evidence."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-ma\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-12-15\ntraceLineCount: 24\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-md.2026-06-08T00-00-00-02-00.cdbce40723e6e8cd","runId":"run.medicaid-ex-parte-share-aug-2026-md.2026-06-08T00-00-00-02-00.cdbce40723e6e8cd","predictionId":"medicaid-ex-parte-share-aug-2026-md","specId":"spec.medicaid-ex-parte-share-aug-2026-md","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 14.7, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 76, 80% interval [68.7, 83.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-md\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-me.2026-06-08T00-00-00-02-00.82d99841c106223a","runId":"run.medicaid-ex-parte-share-aug-2026-me.2026-06-08T00-00-00-02-00.82d99841c106223a","predictionId":"medicaid-ex-parte-share-aug-2026-me","specId":"spec.medicaid-ex-parte-share-aug-2026-me","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 7.4, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 98, 80% interval [91.6, 99]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-me\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-mi.2026-06-08T00-00-00-02-00.86c97d90ea15b729","runId":"run.medicaid-ex-parte-share-aug-2026-mi.2026-06-08T00-00-00-02-00.86c97d90ea15b729","predictionId":"medicaid-ex-parte-share-aug-2026-mi","specId":"spec.medicaid-ex-parte-share-aug-2026-mi","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 12.6, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 80.9, 80% interval [74.6, 87.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-mi\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-mn.2026-06-08T00-00-00-02-00.2c1a3843458d0531","runId":"run.medicaid-ex-parte-share-aug-2026-mn.2026-06-08T00-00-00-02-00.2c1a3843458d0531","predictionId":"medicaid-ex-parte-share-aug-2026-mn","specId":"spec.medicaid-ex-parte-share-aug-2026-mn","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 8.8, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 86.5, 80% interval [82.1, 90.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-mn\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-mo.2026-06-08T00-00-00-02-00.7722492791610330","runId":"run.medicaid-ex-parte-share-aug-2026-mo.2026-06-08T00-00-00-02-00.7722492791610330","predictionId":"medicaid-ex-parte-share-aug-2026-mo","specId":"spec.medicaid-ex-parte-share-aug-2026-mo","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 12.6, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 92.2, 80% interval [85.9, 98.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-mo\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-ms.2026-06-08T00-00-00-02-00.8545a17f067908f7","runId":"run.medicaid-ex-parte-share-aug-2026-ms.2026-06-08T00-00-00-02-00.8545a17f067908f7","predictionId":"medicaid-ex-parte-share-aug-2026-ms","specId":"spec.medicaid-ex-parte-share-aug-2026-ms","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 25.7, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 60.5, 80% interval [47.7, 73.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-ms\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-mt.2026-06-08T00-00-00-02-00.7ed79b4e74a2cf07","runId":"run.medicaid-ex-parte-share-aug-2026-mt.2026-06-08T00-00-00-02-00.7ed79b4e74a2cf07","predictionId":"medicaid-ex-parte-share-aug-2026-mt","specId":"spec.medicaid-ex-parte-share-aug-2026-mt","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 10.2, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 84.6, 80% interval [79.5, 89.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-mt\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-nc.2026-06-08T00-00-00-02-00.e310015579a96dc9","runId":"run.medicaid-ex-parte-share-aug-2026-nc.2026-06-08T00-00-00-02-00.e310015579a96dc9","predictionId":"medicaid-ex-parte-share-aug-2026-nc","specId":"spec.medicaid-ex-parte-share-aug-2026-nc","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3.5, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 98, 80% interval [95.5, 99]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-nc\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-nd.2026-06-08T00-00-00-02-00.437c6bae975aaf9a","runId":"run.medicaid-ex-parte-share-aug-2026-nd.2026-06-08T00-00-00-02-00.437c6bae975aaf9a","predictionId":"medicaid-ex-parte-share-aug-2026-nd","specId":"spec.medicaid-ex-parte-share-aug-2026-nd","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 17, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 77, 80% interval [68.5, 85.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-nd\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-ne.2026-06-08T00-00-00-02-00.38608f0826f052d7","runId":"run.medicaid-ex-parte-share-aug-2026-ne.2026-06-08T00-00-00-02-00.38608f0826f052d7","predictionId":"medicaid-ex-parte-share-aug-2026-ne","specId":"spec.medicaid-ex-parte-share-aug-2026-ne","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 15, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 98, 80% interval [84, 99]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-ne\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-nh.2026-06-08T00-00-00-02-00.94fb6260a1a406e9","runId":"run.medicaid-ex-parte-share-aug-2026-nh.2026-06-08T00-00-00-02-00.94fb6260a1a406e9","predictionId":"medicaid-ex-parte-share-aug-2026-nh","specId":"spec.medicaid-ex-parte-share-aug-2026-nh","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 28, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 67.6, 80% interval [53.6, 81.6]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-nh\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-nj.2026-06-08T00-00-00-02-00.7d1de571749412e7","runId":"run.medicaid-ex-parte-share-aug-2026-nj.2026-06-08T00-00-00-02-00.7d1de571749412e7","predictionId":"medicaid-ex-parte-share-aug-2026-nj","specId":"spec.medicaid-ex-parte-share-aug-2026-nj","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 28, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 78.4, 80% interval [64.4, 92.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-nj\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-nm.2026-06-08T00-00-00-02-00.827dfba4bdae68bf","runId":"run.medicaid-ex-parte-share-aug-2026-nm.2026-06-08T00-00-00-02-00.827dfba4bdae68bf","predictionId":"medicaid-ex-parte-share-aug-2026-nm","specId":"spec.medicaid-ex-parte-share-aug-2026-nm","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 28, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 66.4, 80% interval [52.4, 80.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-nm\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-nv.2026-06-08T00-00-00-02-00.b439b004b7a103c5","runId":"run.medicaid-ex-parte-share-aug-2026-nv.2026-06-08T00-00-00-02-00.b439b004b7a103c5","predictionId":"medicaid-ex-parte-share-aug-2026-nv","specId":"spec.medicaid-ex-parte-share-aug-2026-nv","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 16.9, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 96.1, 80% interval [82.1, 99]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-nv\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-ny.2026-06-08T00-00-00-02-00.a909744d10fe667c","runId":"run.medicaid-ex-parte-share-aug-2026-ny.2026-06-08T00-00-00-02-00.a909744d10fe667c","predictionId":"medicaid-ex-parte-share-aug-2026-ny","specId":"spec.medicaid-ex-parte-share-aug-2026-ny","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 28, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 26.2, 80% interval [12.2, 40.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-ny\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-oh.2026-06-08T00-00-00-02-00.bc0662db15a7cb68","runId":"run.medicaid-ex-parte-share-aug-2026-oh.2026-06-08T00-00-00-02-00.bc0662db15a7cb68","predictionId":"medicaid-ex-parte-share-aug-2026-oh","specId":"spec.medicaid-ex-parte-share-aug-2026-oh","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 28, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 69.6, 80% interval [55.6, 83.6]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-oh\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-ok.2026-06-08T00-00-00-02-00.ffdf97e34f52137b","runId":"run.medicaid-ex-parte-share-aug-2026-ok.2026-06-08T00-00-00-02-00.ffdf97e34f52137b","predictionId":"medicaid-ex-parte-share-aug-2026-ok","specId":"spec.medicaid-ex-parte-share-aug-2026-ok","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 16.4, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 82.2, 80% interval [74, 90.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-ok\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-or.2026-06-08T00-00-00-02-00.7c93c4278c9cd29b","runId":"run.medicaid-ex-parte-share-aug-2026-or.2026-06-08T00-00-00-02-00.7c93c4278c9cd29b","predictionId":"medicaid-ex-parte-share-aug-2026-or","specId":"spec.medicaid-ex-parte-share-aug-2026-or","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 12.8, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 81.3, 80% interval [74.9, 87.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-or\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-pa.2026-06-08T00-00-00-02-00.4ccaee1090322322","runId":"run.medicaid-ex-parte-share-aug-2026-pa.2026-06-08T00-00-00-02-00.4ccaee1090322322","predictionId":"medicaid-ex-parte-share-aug-2026-pa","specId":"spec.medicaid-ex-parte-share-aug-2026-pa","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 27.1, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 43.8, 80% interval [30.3, 57.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-pa\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-ri.2026-06-08T00-00-00-02-00.179b11fa9ab46ce6","runId":"run.medicaid-ex-parte-share-aug-2026-ri.2026-06-08T00-00-00-02-00.179b11fa9ab46ce6","predictionId":"medicaid-ex-parte-share-aug-2026-ri","specId":"spec.medicaid-ex-parte-share-aug-2026-ri","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 14.1, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 92.4, 80% interval [84.9, 99]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-ri\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-sc.2026-06-08T00-00-00-02-00.083a3120fd8e4f92","runId":"run.medicaid-ex-parte-share-aug-2026-sc.2026-06-08T00-00-00-02-00.083a3120fd8e4f92","predictionId":"medicaid-ex-parte-share-aug-2026-sc","specId":"spec.medicaid-ex-parte-share-aug-2026-sc","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 14.7, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 89.2, 80% interval [81.8, 96.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-sc\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-sd.2026-06-08T00-00-00-02-00.caea8c3702f96e9e","runId":"run.medicaid-ex-parte-share-aug-2026-sd.2026-06-08T00-00-00-02-00.caea8c3702f96e9e","predictionId":"medicaid-ex-parte-share-aug-2026-sd","specId":"spec.medicaid-ex-parte-share-aug-2026-sd","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 22.5, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 75.3, 80% interval [64.1, 86.6]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-sd\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-tn.2026-06-08T00-00-00-02-00.fcbf09325d5a6eaa","runId":"run.medicaid-ex-parte-share-aug-2026-tn.2026-06-08T00-00-00-02-00.fcbf09325d5a6eaa","predictionId":"medicaid-ex-parte-share-aug-2026-tn","specId":"spec.medicaid-ex-parte-share-aug-2026-tn","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 15.5, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 69, 80% interval [61.2, 76.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-tn\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-tx.2026-06-08T00-00-00-02-00.ab2f248e8795f71c","runId":"run.medicaid-ex-parte-share-aug-2026-tx.2026-06-08T00-00-00-02-00.ab2f248e8795f71c","predictionId":"medicaid-ex-parte-share-aug-2026-tx","specId":"spec.medicaid-ex-parte-share-aug-2026-tx","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6.9, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 13.5, 80% interval [10.1, 17]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-tx\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-ut.2026-06-08T00-00-00-02-00.6f072835f8407c8e","runId":"run.medicaid-ex-parte-share-aug-2026-ut.2026-06-08T00-00-00-02-00.6f072835f8407c8e","predictionId":"medicaid-ex-parte-share-aug-2026-ut","specId":"spec.medicaid-ex-parte-share-aug-2026-ut","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 20.8, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 72.1, 80% interval [61.7, 82.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-ut\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-va.2026-06-08T00-00-00-02-00.ba444f2de448da59","runId":"run.medicaid-ex-parte-share-aug-2026-va.2026-06-08T00-00-00-02-00.ba444f2de448da59","predictionId":"medicaid-ex-parte-share-aug-2026-va","specId":"spec.medicaid-ex-parte-share-aug-2026-va","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 28, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 60, 80% interval [46, 74]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-va\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-vt.2026-06-08T00-00-00-02-00.bfd2dd3d13e9d9fa","runId":"run.medicaid-ex-parte-share-aug-2026-vt.2026-06-08T00-00-00-02-00.bfd2dd3d13e9d9fa","predictionId":"medicaid-ex-parte-share-aug-2026-vt","specId":"spec.medicaid-ex-parte-share-aug-2026-vt","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 22.7, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 88.8, 80% interval [76.3, 99]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-vt\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-wa.2026-06-08T00-00-00-02-00.deb791ca23cabb59","runId":"run.medicaid-ex-parte-share-aug-2026-wa.2026-06-08T00-00-00-02-00.deb791ca23cabb59","predictionId":"medicaid-ex-parte-share-aug-2026-wa","specId":"spec.medicaid-ex-parte-share-aug-2026-wa","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5.3, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 93.9, 80% interval [91.2, 96.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-wa\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-wi.2026-06-08T00-00-00-02-00.55d88d1c90fa1cf0","runId":"run.medicaid-ex-parte-share-aug-2026-wi.2026-06-08T00-00-00-02-00.55d88d1c90fa1cf0","predictionId":"medicaid-ex-parte-share-aug-2026-wi","specId":"spec.medicaid-ex-parte-share-aug-2026-wi","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 16.8, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 59.4, 80% interval [51, 67.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-wi\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-wv.2026-06-08T00-00-00-02-00.67b01881d239ebcd","runId":"run.medicaid-ex-parte-share-aug-2026-wv.2026-06-08T00-00-00-02-00.67b01881d239ebcd","predictionId":"medicaid-ex-parte-share-aug-2026-wv","specId":"spec.medicaid-ex-parte-share-aug-2026-wv","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 13.2, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 81.9, 80% interval [75.3, 88.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-wv\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-ex-parte-share-aug-2026-wy.2026-06-08T00-00-00-02-00.151d9ab5e8dbcef5","runId":"run.medicaid-ex-parte-share-aug-2026-wy.2026-06-08T00-00-00-02-00.151d9ab5e8dbcef5","predictionId":"medicaid-ex-parte-share-aug-2026-wy","specId":"spec.medicaid-ex-parte-share-aug-2026-wy","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Ex parte share measures how much of the renewal burden the state carries instead of the beneficiary. It trends with data-matching infrastructure, which improves in vendor-release steps rather than smoothly."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 28, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 77.7, 80% interval [63.7, 91.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-ex-parte-share-aug-2026-wy\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-ak.2026-06-08T00-00-00-02-00.054100992fac6147","runId":"run.medicaid-procedural-share-aug-2026-ak.2026-06-08T00-00-00-02-00.054100992fac6147","predictionId":"medicaid-procedural-share-aug-2026-ak","specId":"spec.medicaid-procedural-share-aug-2026-ak","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 28, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 84.1, 80% interval [70.1, 98.1]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-ak\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-al.2026-06-08T00-00-00-02-00.3a219e5ab800219c","runId":"run.medicaid-procedural-share-aug-2026-al.2026-06-08T00-00-00-02-00.3a219e5ab800219c","predictionId":"medicaid-procedural-share-aug-2026-al","specId":"spec.medicaid-procedural-share-aug-2026-al","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 9.7, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 23.4, 80% interval [18.6, 28.3]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-al\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-ar.2026-06-08T00-00-00-02-00.69934c613a23f3c9","runId":"run.medicaid-procedural-share-aug-2026-ar.2026-06-08T00-00-00-02-00.69934c613a23f3c9","predictionId":"medicaid-procedural-share-aug-2026-ar","specId":"spec.medicaid-procedural-share-aug-2026-ar","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 16, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 77, 80% interval [69, 85]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-ar\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-az.2026-06-08T00-00-00-02-00.df1761a22a900494","runId":"run.medicaid-procedural-share-aug-2026-az.2026-06-08T00-00-00-02-00.df1761a22a900494","predictionId":"medicaid-procedural-share-aug-2026-az","specId":"spec.medicaid-procedural-share-aug-2026-az","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 25.5, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 81.9, 80% interval [69.2, 94.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-az\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-co.2026-06-08T00-00-00-02-00.10f374d7a12f5855","runId":"run.medicaid-procedural-share-aug-2026-co.2026-06-08T00-00-00-02-00.10f374d7a12f5855","predictionId":"medicaid-procedural-share-aug-2026-co","specId":"spec.medicaid-procedural-share-aug-2026-co","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 28, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 68.9, 80% interval [54.9, 82.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-co\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-ct.2026-06-08T00-00-00-02-00.59513bbde59aa959","runId":"run.medicaid-procedural-share-aug-2026-ct.2026-06-08T00-00-00-02-00.59513bbde59aa959","predictionId":"medicaid-procedural-share-aug-2026-ct","specId":"spec.medicaid-procedural-share-aug-2026-ct","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 28, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 43.9, 80% interval [29.9, 57.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-ct\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-dc.2026-06-08T00-00-00-02-00.5d2719ff4a307f7b","runId":"run.medicaid-procedural-share-aug-2026-dc.2026-06-08T00-00-00-02-00.5d2719ff4a307f7b","predictionId":"medicaid-procedural-share-aug-2026-dc","specId":"spec.medicaid-procedural-share-aug-2026-dc","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6.1, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 98, 80% interval [92.9, 99]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-dc\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-de.2026-06-08T00-00-00-02-00.55e416860bac6301","runId":"run.medicaid-procedural-share-aug-2026-de.2026-06-08T00-00-00-02-00.55e416860bac6301","predictionId":"medicaid-procedural-share-aug-2026-de","specId":"spec.medicaid-procedural-share-aug-2026-de","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 22.8, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 75, 80% interval [63.6, 86.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-de\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-fl.2026-06-08T00-00-00-02-00.72f44df8e88e68d0","runId":"run.medicaid-procedural-share-aug-2026-fl.2026-06-08T00-00-00-02-00.72f44df8e88e68d0","predictionId":"medicaid-procedural-share-aug-2026-fl","specId":"spec.medicaid-procedural-share-aug-2026-fl","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 28, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 62.2, 80% interval [48.2, 76.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-fl\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-ga.2026-06-08T00-00-00-02-00.8073022e82c2d4f0","runId":"run.medicaid-procedural-share-aug-2026-ga.2026-06-08T00-00-00-02-00.8073022e82c2d4f0","predictionId":"medicaid-procedural-share-aug-2026-ga","specId":"spec.medicaid-procedural-share-aug-2026-ga","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 13.5, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 51, 80% interval [44.3, 57.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-ga\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-hi.2026-06-08T00-00-00-02-00.19829e784c631c27","runId":"run.medicaid-procedural-share-aug-2026-hi.2026-06-08T00-00-00-02-00.19829e784c631c27","predictionId":"medicaid-procedural-share-aug-2026-hi","specId":"spec.medicaid-procedural-share-aug-2026-hi","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 13.8, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 81, 80% interval [74.1, 87.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-hi\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-ia.2026-06-08T00-00-00-02-00.9e745706be41e377","runId":"run.medicaid-procedural-share-aug-2026-ia.2026-06-08T00-00-00-02-00.9e745706be41e377","predictionId":"medicaid-procedural-share-aug-2026-ia","specId":"spec.medicaid-procedural-share-aug-2026-ia","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 21, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 72.8, 80% interval [62.3, 83.3]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-ia\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-id.2026-06-08T00-00-00-02-00.c4c6d20745480ef6","runId":"run.medicaid-procedural-share-aug-2026-id.2026-06-08T00-00-00-02-00.c4c6d20745480ef6","predictionId":"medicaid-procedural-share-aug-2026-id","specId":"spec.medicaid-procedural-share-aug-2026-id","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 15, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 2, 80% interval [1, 16]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-id\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-il.2026-06-08T00-00-00-02-00.efb4711094657bd9","runId":"run.medicaid-procedural-share-aug-2026-il.2026-06-08T00-00-00-02-00.efb4711094657bd9","predictionId":"medicaid-procedural-share-aug-2026-il","specId":"spec.medicaid-procedural-share-aug-2026-il","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 14.9, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 83.8, 80% interval [76.4, 91.3]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-il\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-in.2026-06-08T00-00-00-02-00.a34722ef7170dd1c","runId":"run.medicaid-procedural-share-aug-2026-in.2026-06-08T00-00-00-02-00.a34722ef7170dd1c","predictionId":"medicaid-procedural-share-aug-2026-in","specId":"spec.medicaid-procedural-share-aug-2026-in","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6.2, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 98, 80% interval [92.8, 99]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-in\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-ks.2026-06-08T00-00-00-02-00.af64c3a76a0abd32","runId":"run.medicaid-procedural-share-aug-2026-ks.2026-06-08T00-00-00-02-00.af64c3a76a0abd32","predictionId":"medicaid-procedural-share-aug-2026-ks","specId":"spec.medicaid-procedural-share-aug-2026-ks","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 24.6, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 39.4, 80% interval [27.1, 51.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-ks\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-ky.2026-06-08T00-00-00-02-00.8e9525f0266c54c0","runId":"run.medicaid-procedural-share-aug-2026-ky.2026-06-08T00-00-00-02-00.8e9525f0266c54c0","predictionId":"medicaid-procedural-share-aug-2026-ky","specId":"spec.medicaid-procedural-share-aug-2026-ky","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 28, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 74.2, 80% interval [60.2, 88.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-ky\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-la.2026-06-08T00-00-00-02-00.347753b075a416d6","runId":"run.medicaid-procedural-share-aug-2026-la.2026-06-08T00-00-00-02-00.347753b075a416d6","predictionId":"medicaid-procedural-share-aug-2026-la","specId":"spec.medicaid-procedural-share-aug-2026-la","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 15.2, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 97.8, 80% interval [83.8, 99]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-la\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-ma.2026-06-08T00-00-00-02-00.61e8c478f282f1b2","runId":"run.medicaid-procedural-share-aug-2026-ma.2026-06-08T00-00-00-02-00.61e8c478f282f1b2","predictionId":"medicaid-procedural-share-aug-2026-ma","specId":"spec.medicaid-procedural-share-aug-2026-ma","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 28, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 49.3, 80% interval [35.3, 63.3]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-ma\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-md.2026-06-08T00-00-00-02-00.72106cb4bea85b2d","runId":"run.medicaid-procedural-share-aug-2026-md.2026-06-08T00-00-00-02-00.72106cb4bea85b2d","predictionId":"medicaid-procedural-share-aug-2026-md","specId":"spec.medicaid-procedural-share-aug-2026-md","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 11.6, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 89.3, 80% interval [83.5, 95.1]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-md\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-me.2026-06-08T00-00-00-02-00.7c3751955ee724aa","runId":"run.medicaid-procedural-share-aug-2026-me.2026-06-08T00-00-00-02-00.7c3751955ee724aa","predictionId":"medicaid-procedural-share-aug-2026-me","specId":"spec.medicaid-procedural-share-aug-2026-me","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 21.7, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 91.3, 80% interval [77.3, 99]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-me\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-mi.2026-06-08T00-00-00-02-00.6793610372771bb1","runId":"run.medicaid-procedural-share-aug-2026-mi.2026-06-08T00-00-00-02-00.6793610372771bb1","predictionId":"medicaid-procedural-share-aug-2026-mi","specId":"spec.medicaid-procedural-share-aug-2026-mi","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 18.2, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 92.2, 80% interval [80.8, 99]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-mi\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-mn.2026-06-08T00-00-00-02-00.31044e501961d129","runId":"run.medicaid-procedural-share-aug-2026-mn.2026-06-08T00-00-00-02-00.31044e501961d129","predictionId":"medicaid-procedural-share-aug-2026-mn","specId":"spec.medicaid-procedural-share-aug-2026-mn","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 17.1, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 87.1, 80% interval [78.5, 95.6]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-mn\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-mo.2026-06-08T00-00-00-02-00.12b0409fc90ebb13","runId":"run.medicaid-procedural-share-aug-2026-mo.2026-06-08T00-00-00-02-00.12b0409fc90ebb13","predictionId":"medicaid-procedural-share-aug-2026-mo","specId":"spec.medicaid-procedural-share-aug-2026-mo","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 8.7, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 94.1, 80% interval [89.8, 98.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-mo\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-ms.2026-06-08T00-00-00-02-00.6839ef63ee068db3","runId":"run.medicaid-procedural-share-aug-2026-ms.2026-06-08T00-00-00-02-00.6839ef63ee068db3","predictionId":"medicaid-procedural-share-aug-2026-ms","specId":"spec.medicaid-procedural-share-aug-2026-ms","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 10.6, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 82.4, 80% interval [77.1, 87.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-ms\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-mt.2026-06-08T00-00-00-02-00.e66421609fd14af6","runId":"run.medicaid-procedural-share-aug-2026-mt.2026-06-08T00-00-00-02-00.e66421609fd14af6","predictionId":"medicaid-procedural-share-aug-2026-mt","specId":"spec.medicaid-procedural-share-aug-2026-mt","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 27.8, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 77, 80% interval [63.1, 90.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-mt\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-nc.2026-06-08T00-00-00-02-00.9ce2d8a81bd2aa5f","runId":"run.medicaid-procedural-share-aug-2026-nc.2026-06-08T00-00-00-02-00.9ce2d8a81bd2aa5f","predictionId":"medicaid-procedural-share-aug-2026-nc","specId":"spec.medicaid-procedural-share-aug-2026-nc","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 9.6, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 59.6, 80% interval [54.8, 64.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-nc\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-nd.2026-06-08T00-00-00-02-00.144d1e06a5b58977","runId":"run.medicaid-procedural-share-aug-2026-nd.2026-06-08T00-00-00-02-00.144d1e06a5b58977","predictionId":"medicaid-procedural-share-aug-2026-nd","specId":"spec.medicaid-procedural-share-aug-2026-nd","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 22.2, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 85.4, 80% interval [74.3, 96.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-nd\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-ne.2026-06-08T00-00-00-02-00.a22cc6bc8e049684","runId":"run.medicaid-procedural-share-aug-2026-ne.2026-06-08T00-00-00-02-00.a22cc6bc8e049684","predictionId":"medicaid-procedural-share-aug-2026-ne","specId":"spec.medicaid-procedural-share-aug-2026-ne","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 13.2, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 37.5, 80% interval [30.9, 44.1]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-ne\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-nh.2026-06-08T00-00-00-02-00.50df8fc46e971140","runId":"run.medicaid-procedural-share-aug-2026-nh.2026-06-08T00-00-00-02-00.50df8fc46e971140","predictionId":"medicaid-procedural-share-aug-2026-nh","specId":"spec.medicaid-procedural-share-aug-2026-nh","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 13.9, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 88.9, 80% interval [82, 95.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-nh\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-nj.2026-06-08T00-00-00-02-00.2216a77f57b7c05a","runId":"run.medicaid-procedural-share-aug-2026-nj.2026-06-08T00-00-00-02-00.2216a77f57b7c05a","predictionId":"medicaid-procedural-share-aug-2026-nj","specId":"spec.medicaid-procedural-share-aug-2026-nj","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 23.8, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 89.2, 80% interval [75.2, 99]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-nj\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-nm.2026-06-08T00-00-00-02-00.531e1dd2624565f1","runId":"run.medicaid-procedural-share-aug-2026-nm.2026-06-08T00-00-00-02-00.531e1dd2624565f1","predictionId":"medicaid-procedural-share-aug-2026-nm","specId":"spec.medicaid-procedural-share-aug-2026-nm","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 10.1, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 89.6, 80% interval [84.6, 94.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-nm\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-nv.2026-06-08T00-00-00-02-00.f9efd46a97ec8887","runId":"run.medicaid-procedural-share-aug-2026-nv.2026-06-08T00-00-00-02-00.f9efd46a97ec8887","predictionId":"medicaid-procedural-share-aug-2026-nv","specId":"spec.medicaid-procedural-share-aug-2026-nv","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 21.4, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 78.7, 80% interval [68, 89.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-nv\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-ny.2026-06-08T00-00-00-02-00.364c7812879c1db3","runId":"run.medicaid-procedural-share-aug-2026-ny.2026-06-08T00-00-00-02-00.364c7812879c1db3","predictionId":"medicaid-procedural-share-aug-2026-ny","specId":"spec.medicaid-procedural-share-aug-2026-ny","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 19.9, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 66.8, 80% interval [56.8, 76.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-ny\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-oh.2026-06-08T00-00-00-02-00.6a857c52cd363ac5","runId":"run.medicaid-procedural-share-aug-2026-oh.2026-06-08T00-00-00-02-00.6a857c52cd363ac5","predictionId":"medicaid-procedural-share-aug-2026-oh","specId":"spec.medicaid-procedural-share-aug-2026-oh","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 11, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 98, 80% interval [88, 99]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-oh\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-ok.2026-06-08T00-00-00-02-00.a8d3fda8cdee23ed","runId":"run.medicaid-procedural-share-aug-2026-ok.2026-06-08T00-00-00-02-00.a8d3fda8cdee23ed","predictionId":"medicaid-procedural-share-aug-2026-ok","specId":"spec.medicaid-procedural-share-aug-2026-ok","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 19.1, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 92.5, 80% interval [79.9, 99]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-ok\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-or.2026-06-08T00-00-00-02-00.9fa78ec82c180466","runId":"run.medicaid-procedural-share-aug-2026-or.2026-06-08T00-00-00-02-00.9fa78ec82c180466","predictionId":"medicaid-procedural-share-aug-2026-or","specId":"spec.medicaid-procedural-share-aug-2026-or","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 20.9, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 65, 80% interval [54.6, 75.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-or\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-pa.2026-06-08T00-00-00-02-00.6f682dde22be4ebb","runId":"run.medicaid-procedural-share-aug-2026-pa.2026-06-08T00-00-00-02-00.6f682dde22be4ebb","predictionId":"medicaid-procedural-share-aug-2026-pa","specId":"spec.medicaid-procedural-share-aug-2026-pa","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 21.8, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 40, 80% interval [29.1, 50.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-pa\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-ri.2026-06-08T00-00-00-02-00.0fcac8d950ed6970","runId":"run.medicaid-procedural-share-aug-2026-ri.2026-06-08T00-00-00-02-00.0fcac8d950ed6970","predictionId":"medicaid-procedural-share-aug-2026-ri","specId":"spec.medicaid-procedural-share-aug-2026-ri","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 28, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 77.6, 80% interval [63.6, 91.6]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-ri\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-sc.2026-06-08T00-00-00-02-00.56a231fa56ddf542","runId":"run.medicaid-procedural-share-aug-2026-sc.2026-06-08T00-00-00-02-00.56a231fa56ddf542","predictionId":"medicaid-procedural-share-aug-2026-sc","specId":"spec.medicaid-procedural-share-aug-2026-sc","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 20.5, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 22.4, 80% interval [12.1, 32.6]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-sc\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-sd.2026-06-08T00-00-00-02-00.339f13e964182f62","runId":"run.medicaid-procedural-share-aug-2026-sd.2026-06-08T00-00-00-02-00.339f13e964182f62","predictionId":"medicaid-procedural-share-aug-2026-sd","specId":"spec.medicaid-procedural-share-aug-2026-sd","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 19.2, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 85.7, 80% interval [76.1, 95.3]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-sd\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-tn.2026-06-08T00-00-00-02-00.8efbf0e333ed5a49","runId":"run.medicaid-procedural-share-aug-2026-tn.2026-06-08T00-00-00-02-00.8efbf0e333ed5a49","predictionId":"medicaid-procedural-share-aug-2026-tn","specId":"spec.medicaid-procedural-share-aug-2026-tn","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 18.6, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 65.9, 80% interval [56.6, 75.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-tn\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-tx.2026-06-08T00-00-00-02-00.ddd36b3a678897fd","runId":"run.medicaid-procedural-share-aug-2026-tx.2026-06-08T00-00-00-02-00.ddd36b3a678897fd","predictionId":"medicaid-procedural-share-aug-2026-tx","specId":"spec.medicaid-procedural-share-aug-2026-tx","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 28, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 72.1, 80% interval [58.1, 86.1]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-tx\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-ut.2026-06-08T00-00-00-02-00.36536857f74707ef","runId":"run.medicaid-procedural-share-aug-2026-ut.2026-06-08T00-00-00-02-00.36536857f74707ef","predictionId":"medicaid-procedural-share-aug-2026-ut","specId":"spec.medicaid-procedural-share-aug-2026-ut","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 8.5, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 91.3, 80% interval [87, 95.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-ut\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-va.2026-06-08T00-00-00-02-00.27f65c155656969a","runId":"run.medicaid-procedural-share-aug-2026-va.2026-06-08T00-00-00-02-00.27f65c155656969a","predictionId":"medicaid-procedural-share-aug-2026-va","specId":"spec.medicaid-procedural-share-aug-2026-va","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 25.5, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 87.5, 80% interval [73.5, 99]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-va\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-vt.2026-06-08T00-00-00-02-00.41a9de5ac947f8f0","runId":"run.medicaid-procedural-share-aug-2026-vt.2026-06-08T00-00-00-02-00.41a9de5ac947f8f0","predictionId":"medicaid-procedural-share-aug-2026-vt","specId":"spec.medicaid-procedural-share-aug-2026-vt","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 12.3, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 93.3, 80% interval [86.7, 99]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-vt\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-wa.2026-06-08T00-00-00-02-00.a6c0d778d11c5867","runId":"run.medicaid-procedural-share-aug-2026-wa.2026-06-08T00-00-00-02-00.a6c0d778d11c5867","predictionId":"medicaid-procedural-share-aug-2026-wa","specId":"spec.medicaid-procedural-share-aug-2026-wa","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 10.3, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 85.5, 80% interval [80.4, 90.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-wa\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-wi.2026-06-08T00-00-00-02-00.9118ddd3ef925dc0","runId":"run.medicaid-procedural-share-aug-2026-wi.2026-06-08T00-00-00-02-00.9118ddd3ef925dc0","predictionId":"medicaid-procedural-share-aug-2026-wi","specId":"spec.medicaid-procedural-share-aug-2026-wi","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 20.2, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 60.2, 80% interval [50.1, 70.3]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-wi\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-wv.2026-06-08T00-00-00-02-00.2fdbb9a0b2c6ab0a","runId":"run.medicaid-procedural-share-aug-2026-wv.2026-06-08T00-00-00-02-00.2fdbb9a0b2c6ab0a","predictionId":"medicaid-procedural-share-aug-2026-wv","specId":"spec.medicaid-procedural-share-aug-2026-wv","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 11.8, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 83.1, 80% interval [77.2, 89]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-wv\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-procedural-share-aug-2026-wy.2026-06-08T00-00-00-02-00.fff855116cb9c2dd","runId":"run.medicaid-procedural-share-aug-2026-wy.2026-06-08T00-00-00-02-00.fff855116cb9c2dd","predictionId":"medicaid-procedural-share-aug-2026-wy","specId":"spec.medicaid-procedural-share-aug-2026-wy","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 25.7, distribution present, forecast step count 1.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest.","Forecast: point 77.5, 80% interval [64.7, 90.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Half-weight trend continuation with volatility-scaled uncertainty; renewal cohorts differ month to month, so the interval is wider than the point trend alone would suggest."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-procedural-share-aug-2026-wy\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-cost-share-threshold-states-fy2025.2026-06-08T00-00-00-02-00.376b2ea1dbda6122","runId":"run.snap-cost-share-threshold-states-fy2025.2026-06-08T00-00-00-02-00.376b2ea1dbda6122","predictionId":"snap-cost-share-threshold-states-fy2025","specId":"spec.snap-cost-share-threshold-states-fy2025","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: fns.lookup({ series: \"jurisdictions_at_or_above_6pct\", years: [\"fy2023\", \"fy2024\"] })","Modal outcome is 41-43 jurisdictions at or above 6 percent. The lower tail requires broad, fast corrective-action wins; the upper tail covers caseload churn pushing borderline states back above the line."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 17, distribution present, forecast step count 1.","evidence":["Modal outcome is 41-43 jurisdictions at or above 6 percent. The lower tail requires broad, fast corrective-action wins; the upper tail covers caseload churn pushing borderline states back above the line.","Forecast: point 79.2, 80% interval [69.8, 86.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast","Forecast: point 79.2, 80% interval [69.8, 86.8]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-cost-share-threshold-states-fy2025\nrunLabel: Headline\nresolutionDate: 2026-09-30\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-cost-share-in-effect.2026-06-08T00-00-00-02-00.25426038f56ada19","runId":"run.snap-error-rate-fy2026-cost-share-in-effect.2026-06-08T00-00-00-02-00.25426038f56ada19","predictionId":"snap-error-rate-fy2026-cost-share-in-effect","specId":"spec.snap-error-rate-fy2026-cost-share-in-effect","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 3 historical point(s) and implicit outside-view language.","evidence":["Unconditional FY 2025 forecast: 10.2. A binding match incentive historically accelerates corrective action (South Carolina cut 22.6 to 9.3 in one year under far weaker pressure); conditional on the provision surviving, an additional ~0.8pp decline is the modal path."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["This cell conditions on a policy state, not on data availability: the SNAP cost-share provisions staying law through mid-2027. It isolates the incentive effect the threshold cell can only gesture at — FY 2026 is the first full fiscal year states operate knowing their error rates drive a 5-15 percent benefit match, and FY 2026 rates feed the first match calculations. The conditioning event is machine-checkable against the federal bill tracker, and once the provision is encoded, against the rules corpus.","Tool call: ledger.lookup({ source_record_id: \"fns.snap.total_payment_error_rate.us.fy2024.official_release\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["This cell conditions on a policy state, not on data availability: the SNAP cost-share provisions staying law through mid-2027. It isolates the incentive effect the threshold cell can only gesture at — FY 2026 is the first full fiscal year states operate knowing their error rates drive a 5-15 percent benefit match, and FY 2026 rates feed the first match calculations. The conditioning event is machine-checkable against the federal bill tracker, and once the provision is encoded, against the rules corpus.","Tool call: ledger.lookup({ source_record_id: \"fns.snap.total_payment_error_rate.us.fy2024.official_release\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.5, distribution present, forecast step count 1.","evidence":["The lower tail is broad corrective-action wins plus favorable QC arbitration; the upper tail is implementation friction and caseload churn offsetting the incentive. If the provision is repealed or delayed, the cell never resolves — that is what makes it a clean reading of the policy's effect.","Forecast: point 9.4, 80% interval [8.2, 10.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Unconditional FY 2025 forecast: 10.2. A binding match incentive historically accelerates corrective action (South Carolina cut 22.6 to 9.3 in one year under far weaker pressure); conditional on the provision surviving, an additional ~0.8pp decline is the modal path."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The lower tail is broad corrective-action wins plus favorable QC arbitration; the upper tail is implementation friction and caseload churn offsetting the incentive. If the provision is repealed or delayed, the cell never resolves — that is what makes it a clean reading of the policy's effect."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Unconditional FY 2025 forecast: 10.2. A binding match incentive historically accelerates corrective action (South Carolina cut 22.6 to 9.3 in one year under far weaker pressure); conditional on the provision surviving, an additional ~0.8pp decline is the modal path.","Forecast"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-cost-share-in-effect\nrunLabel: Headline\nresolutionDate: 2027-06-30\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-cost-share-repealed.2026-06-08T00-00-00-02-00.63d316d8387f5e14","runId":"run.snap-error-rate-fy2026-cost-share-repealed.2026-06-08T00-00-00-02-00.63d316d8387f5e14","predictionId":"snap-error-rate-fy2026-cost-share-repealed","specId":"spec.snap-error-rate-fy2026-cost-share-repealed","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.22,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ source_record_id: \"fns.snap.total_payment_error_rate.us.fy2024.official_release\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["This is the mirror of the cost-share-in-effect cell: same outcome, opposite policy state. Exactly one arm resolves. The 0.9-point gap between the two point estimates is the institution's product in miniature — a falsifiable, dated forecast of what a policy choice does to a delivery outcome, published before the choice is made.","Tool call: ledger.lookup({ source_record_id: \"fns.snap.total_payment_error_rate.us.fy2024.official_release\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.7, distribution present, forecast step count 1.","evidence":["Under repeal, the secular improvement trend (11.68 to 10.93 to ~10.2e) continues but loses the match-driven acceleration; states that already funded corrective action carry some momentum through FY 2026. Wider interval reflects the policy turbulence that any repeal scenario implies.","Forecast: point 10.3, 80% interval [9, 11.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Under repeal, the secular improvement trend (11.68 to 10.93 to ~10.2e) continues but loses the match-driven acceleration; states that already funded corrective action carry some momentum through FY 2026. Wider interval reflects the policy turbulence that any repeal scenario implies."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Under repeal, the secular improvement trend (11.68 to 10.93 to ~10.2e) continues but loses the match-driven acceleration; states that already funded corrective action carry some momentum through FY 2026. Wider interval reflects the policy turbulence that any repeal scenario implies."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["This is the mirror of the cost-share-in-effect cell: same outcome, opposite policy state. Exactly one arm resolves. The 0.9-point gap between the two point estimates is the institution's product in miniature — a falsifiable, dated forecast of what a policy choice does to a delivery outcome, published before the choice is made.","Under repeal, the secular improvement trend (11.68 to 10.93 to ~10.2e) continues but loses the match-driven acceleration; states that already funded corrective action carry some momentum through FY 2026. Wider interval reflects the policy turbulence that any repeal scenario implies."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-cost-share-repealed\nrunLabel: Headline\nresolutionDate: 2027-06-30\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-call-wait-mar-2027-work-req-deadline-holds.2026-06-12T18-52-35Z.fda471c7c708d046","runId":"run.medicaid-call-wait-mar-2027-work-req-deadline-holds.2026-06-12T18-52-35Z.fda471c7c708d046","predictionId":"medicaid-call-wait-mar-2027-work-req-deadline-holds","specId":"spec.medicaid-call-wait-mar-2027-work-req-deadline-holds","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.54,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Minutes on hold is the time tax at its most direct. I rebuild this forecast from the primary CMS series rather than asserting it: the volume-weighted national average Medicaid call-center wait already tripled from 7.3 minutes in May 2025 to a 25.4-minute peak in January 2026 (11.9M calls), settling at 24.0 in February 2026 — the latest period CMS has published. March 2027 is the first full quarter after the December 31, 2026 community-engagement compliance deadline, so the question is how much an implementation pulse adds on top of an already-stressed baseline, net of staffing response.","Tool result: Unwinding precedent (Apr 2023–Jun 2024): call volume rose from a 7.1M/month April-2023 baseline to 10.9M in August 2023 (+3.7M, >150%) and peaked near 11.0M in January 2024. National average wait peaked at 'over 13 minutes'; state peaks ranged 1–72 minutes (14 states >30 min). Abandonment peaked at 17.7% nationally. 94.3M renewals over 14 months, 31.8% requiring a returned form; 15.1% procedurally disenrolled for not completing renewal."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Minutes on hold is the time tax at its most direct. I rebuild this forecast from the primary CMS series rather than asserting it: the volume-weighted national average Medicaid call-center wait already tripled from 7.3 minutes in May 2025 to a 25.4-minute peak in January 2026 (11.9M calls), settling at 24.0 in February 2026 — the latest period CMS has published. March 2027 is the first full quarter after the December 31, 2026 community-engagement compliance deadline, so the question is how much an implementation pulse adds on top of an already-stressed baseline, net of staffing response.","Tool result: CBO: 18.5M people subject to the requirement each year. Verification at application and at renewal every 6 months (states may verify more frequently); look-back of 1–3 consecutive months. Effective January 1, 2027; compliance deadline December 31, 2026. CMS interim final rule issued June 3, 2026 (80 hrs/month), projecting a 2.3M enrollment reduction in FY2027 rising to 3.1–3.3M later."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Minutes on hold is the time tax at its most direct. I rebuild this forecast from the primary CMS series rather than asserting it: the volume-weighted national average Medicaid call-center wait already tripled from 7.3 minutes in May 2025 to a 25.4-minute peak in January 2026 (11.9M calls), settling at 24.0 in February 2026 — the latest period CMS has published. March 2027 is the first full quarter after the December 31, 2026 community-engagement compliance deadline, so the question is how much an implementation pulse adds on top of an already-stressed baseline, net of staffing response.","Tool result: Computed from the datastore API (10,710 rows; latest period = 202602). Volume-weighted national wait by month: 2025-05 7.26 (6.76M calls); 2025-09 14.99 (8.48M); 2025-12 16.42 (8.28M); 2026-01 25.37 (11.94M); 2026-02 24.01 (9.96M). Volume-weighted abandonment peaked with wait at 20.4% in 2026-01. My reproduction matches the published series (7.3/15.0/16.4/24.0) to one decimal, confirming the resolution method."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 17, distribution present, forecast step count 1.","evidence":["calls→wait fit + offset. I fit the 18-month volume-weighted CMS series three ways: linear wait = −12.08 + 3.03·V(M) (corr 0.82); quadratic 7.06 − 1.37·V + 0.246·V² (R² 0.69); and an M/M/1-flavored queue wait = 18.53·ρ/(1−ρ) with capacity 20.5M/mo (R² 0.69). They agree within ~1 min at 10–12M and diverge above 13M where the convex fits bend up (queueing saturation). A Monte Carlo over the parameter ranges (triangular extra-calls mode 3.6M; staffing offset U(−6,0) anchored to the unwinding catch-up from a 13-min peak) gives central volume ~14.3M → mean-of-fits ~34 min before offset, with an 80% wait interval of [26, 43]. Staffing offset central −3 min pulls the point to ~33.","Counter-consideration — what breaks this each way. Downward: the rollout is pre-announced (unlike the chaotic unwinding), states have run stressed call centers since 2025, and the IFR pushes data-matching/ex-parte verification that could deflect calls — a strong staffing/automation response could hold March near the low 20s. Also, if early-2027 implementation is partial (good-faith state extensions, phased cohorts), the pulse spreads thin. Upward: the queue fit warns that past ~14–15M calls the wait curve is explosively convex — a heavier pulse plus thin staffing could blow past 43 minutes, and Arkansas's 33% awareness gap argues calls-per-touch could exceed my central. The interval is right-skewed for exactly this reason."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Δcalls decomposition for March 2027 (HOLDS): extra calls ≈ (subject pop) × (share with an establishment touchpoint hitting March) × (incremental calls per touched person). Subject = 18.5M (CBO). March-touch share = 0.10–0.22 (Jan–Mar rollout, March is one of ~three pulse months); calls per touched person = 0.8–2.0 (anchored above the unwinding's 1.8 per action-required event because the policy is novel and 33% are unaware). Central: 18.5 × 0.15 × 1.3 ≈ 3.6M extra calls in March — deliberately matched to the unwinding's +3.9M peak increment, the right magnitude for a nationwide eligibility shock. Range 1.5M (low) to ~6M (severe). Added to a March renewal baseline of 9.5–11.5M (anchored to Jan-26 11.9M / Feb-26 10.0M) gives a HOLDS call volume of ~11–17M, centered ~14M."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["calls→wait fit + offset. I fit the 18-month volume-weighted CMS series three ways: linear wait = −12.08 + 3.03·V(M) (corr 0.82); quadratic 7.06 − 1.37·V + 0.246·V² (R² 0.69); and an M/M/1-flavored queue wait = 18.53·ρ/(1−ρ) with capacity 20.5M/mo (R² 0.69). They agree within ~1 min at 10–12M and diverge above 13M where the convex fits bend up (queueing saturation). A Monte Carlo over the parameter ranges (triangular extra-calls mode 3.6M; staffing offset U(−6,0) anchored to the unwinding catch-up from a 13-min peak) gives central volume ~14.3M → mean-of-fits ~34 min before offset, with an 80% wait interval of [26, 43]. Staffing offset central −3 min pulls the point to ~33."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Minutes on hold is the time tax at its most direct. I rebuild this forecast from the primary CMS series rather than asserting it: the volume-weighted national average Medicaid call-center wait already tripled from 7.3 minutes in May 2025 to a 25.4-minute peak in January 2026 (11.9M calls), settling at 24.0 in February 2026 — the latest period CMS has published. March 2027 is the first full quarter after the December 31, 2026 community-engagement compliance deadline, so the question is how much an implementation pulse adds on top of an already-stressed baseline, net of staffing response.","Tool result: At the unwinding peak ~3.9M incremental calls/month landed on top of the 7.1M baseline against ~2.1M/month action-required (form) renewals → ~1.8 incremental calls per action-required touchpoint (~0.58 per renewal of any type). This is the reference-class ratio I anchor the work-requirement decomposition to."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-call-wait-mar-2027-work-req-deadline-holds\nrunLabel: Headline\nresolutionDate: 2027-07-31\ntraceLineCount: 19\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-call-wait-mar-2027-work-req-deadline-delayed.2026-06-12T18-52-35Z.7297dee169cc2a61","runId":"run.medicaid-call-wait-mar-2027-work-req-deadline-delayed.2026-06-12T18-52-35Z.7297dee169cc2a61","predictionId":"medicaid-call-wait-mar-2027-work-req-deadline-delayed","specId":"spec.medicaid-call-wait-mar-2027-work-req-deadline-delayed","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Same outcome, opposite policy state, same model with the work-requirement pulse switched off. If a statute or a nationwide stay delays the community-engagement deadline before April 2027, the implementation wave never lands in Q1; volume reverts toward the renewal-system baseline and staffing catches up. Hold times do not return to the 7-minute world of spring 2025 — renewal volumes and prior churn persist — but the implementation premium does not get added.","Tool call: macpac.lookup({ brief: \"State-Reported Medicaid Unwinding Data\", fields: [\"baseline_volume\", \"post_surge_level\"] })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Δcalls ≈ 0 by construction in this arm — the work-requirement decomposition (the +3.6M central pulse from the holds arm) is set to zero. The only additions to the renewal baseline are residual churn calls (~0–0.8M/month) from coverage lost during the 2025–26 surge. March-2027 volume is therefore the baseline drift alone: a triangular 8.5–10.5M with mode 9.5M, anchored to the 2025 in-band months (6.3–9.6M) plus modest upward drift from a larger post-surge caseload.","Counter-consideration — what breaks this each way. Upward: a delay that arrives late or messily (a Q1 court stay after partial state rollout, or a statutory delay enacted in February) could leave a half-started implementation generating confusion calls anyway, plus the 2025–26 churn keeps re-application volume elevated — the upper tail could touch the low 20s. Downward: if the delay is clean and early and staffing fully catches up, March could revert into the low teens like spring 2025. The interval is much narrower than the holds arm because there is no queueing-saturation tail when volume stays under ~11M."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Modal path ~15 minutes: elevated above the spring-2025 floor by persistent renewal and churn volume, but well below the holds arm because the implementation pulse never lands. Exactly one arm of this pair resolves. The ~18-minute gap to the holds arm, at roughly 10 million calls a month, is on the order of 1.8 million person-hours of waiting per month — the time-tax-denominated forecast of this single policy state."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6, distribution present, forecast step count 1.","evidence":["calls→wait fit + offset. Applying the same three-way fit (linear −12.08 + 3.03·V; quadratic; M/M/1-flavored queue, all R²≈0.69, agreeing to ~1 min in this 8.5–10.5M range that sits inside the calibration window): mean-of-fits at 9.5M ≈ 16 min; at 8.5M ≈ 13; at 10.5M ≈ 20. A Monte Carlo with the −3 min central staffing offset (range −6 to 0, anchored to the unwinding catch-up) yields a point of ~15 minutes and an 80% interval of [12, 18] — tight, because this arm sits in the well-sampled, near-linear part of the curve rather than the convex tail.","Counter-consideration — what breaks this each way. Upward: a delay that arrives late or messily (a Q1 court stay after partial state rollout, or a statutory delay enacted in February) could leave a half-started implementation generating confusion calls anyway, plus the 2025–26 churn keeps re-application volume elevated — the upper tail could touch the low 20s. Downward: if the delay is clean and early and staffing fully catches up, March could revert into the low teens like spring 2025. The interval is much narrower than the holds arm because there is no queueing-saturation tail when volume stays under ~11M."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Reference class — the unwinding recession, quantified. The cleanest analogue for a 'shock deferred / volumes normalize' path is the back half of the unwinding: after the January 2024 peak (~11M calls, national wait 'over 13 minutes'), volume fell ~26% to 8.1M by June 2024 and most states' waits eased. Without an implementation pulse, March 2027 looks like that recession state — a renewal baseline around 9–10M calls, not the 12–14M of the holds arm. Arkansas's confusion channel (33% unaware) is muted here because no new requirement is being enforced, though some residual confusion calls from 2025–26 coverage churn persist.","calls→wait fit + offset. Applying the same three-way fit (linear −12.08 + 3.03·V; quadratic; M/M/1-flavored queue, all R²≈0.69, agreeing to ~1 min in this 8.5–10.5M range that sits inside the calibration window): mean-of-fits at 9.5M ≈ 16 min; at 8.5M ≈ 13; at 10.5M ≈ 20. A Monte Carlo with the −3 min central staffing offset (range −6 to 0, anchored to the unwinding catch-up) yields a point of ~15 minutes and an 80% interval of [12, 18] — tight, because this arm sits in the well-sampled, near-linear part of the curve rather than the convex tail."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Same outcome, opposite policy state, same model with the work-requirement pulse switched off. If a statute or a nationwide stay delays the community-engagement deadline before April 2027, the implementation wave never lands in Q1; volume reverts toward the renewal-system baseline and staffing catches up. Hold times do not return to the 7-minute world of spring 2025 — renewal volumes and prior churn persist — but the implementation premium does not get added.","calls→wait fit + offset. Applying the same three-way fit (linear −12.08 + 3.03·V; quadratic; M/M/1-flavored queue, all R²≈0.69, agreeing to ~1 min in this 8.5–10.5M range that sits inside the calibration window): mean-of-fits at 9.5M ≈ 16 min; at 8.5M ≈ 13; at 10.5M ≈ 20. A Monte Carlo with the −3 min central staffing offset (range −6 to 0, anchored to the unwinding catch-up) yields a point of ~15 minutes and an 80% interval of [12, 18] — tight, because this arm sits in the well-sampled, near-linear part of the curve rather than the convex tail."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["calls→wait fit + offset. Applying the same three-way fit (linear −12.08 + 3.03·V; quadratic; M/M/1-flavored queue, all R²≈0.69, agreeing to ~1 min in this 8.5–10.5M range that sits inside the calibration window): mean-of-fits at 9.5M ≈ 16 min; at 8.5M ≈ 13; at 10.5M ≈ 20. A Monte Carlo with the −3 min central staffing offset (range −6 to 0, anchored to the unwinding catch-up) yields a point of ~15 minutes and an 80% interval of [12, 18] — tight, because this arm sits in the well-sampled, near-linear part of the curve rather than the convex tail.","Counter-consideration — what breaks this each way. Upward: a delay that arrives late or messily (a Q1 court stay after partial state rollout, or a statutory delay enacted in February) could leave a half-started implementation generating confusion calls anyway, plus the 2025–26 churn keeps re-application volume elevated — the upper tail could touch the low 20s. Downward: if the delay is clean and early and staffing fully catches up, March could revert into the low teens like spring 2025. The interval is much narrower than the holds arm because there is no queueing-saturation tail when volume stays under ~11M."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-call-wait-mar-2027-work-req-deadline-delayed\nrunLabel: Headline\nresolutionDate: 2027-07-31\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-work-req-deadline-in-effect-2027q1.2026-06-12T18-52-35Z.36222c51ba0ec5ed","runId":"run.medicaid-work-req-deadline-in-effect-2027q1.2026-06-12T18-52-35Z.36222c51ba0ec5ed","predictionId":"medicaid-work-req-deadline-in-effect-2027q1","specId":"spec.medicaid-work-req-deadline-in-effect-2027q1","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.51,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 3 historical point(s) and explicit outside-view language.","evidence":["P(fail) = 0.06 + 0.05 − 0.003 = 0.107 → P(hold) = 0.893 ≈ 89%. Propagating the parameter ranges gives P(hold) ∈ [82%, 93%]; I widen the lower bound slightly to 80% for model risk (unmodeled late-2026 implementation politics, e.g. a chaotic rollout shifting congressional will). 80% interval [80, 94]. This is up from the prior 85% specifically because Trump v. CASA — decided after the earlier estimate's framing — removed most of the nationwide-stay mass, and the on-schedule June 2026 IFR is fresh evidence of implementation intent.","Point 89%, reflecting a high statutory-survival base rate, a post-CASA collapse of the nationwide-stay leg, an on-schedule implementing rule, and a state-extension safety valve that bleeds off pressure for a national delay. Together with the conditional pair this completes the mixture: the unconditional March-2027 wait forecast is the probability-weighted blend of the two arms (≈ 0.89 × 33 + 0.11 × 15 ≈ 31 minutes)."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log absent.","evidence":["Tool result: Supreme Court held 6-3 in Trump v. CASA (June 27, 2025) that federal courts lack authority to issue universal/nationwide injunctions under the Judiciary Act of 1789. This post-dates the reconciliation law and collapses the most direct path to a nationwide stay of the statutory deadline; residual nationwide-effect relief would require APA vacatur of the implementing rule (which does not by itself move the statutory deadline) or a certified (b)(2) class action.","Tool result: KFF tracker (June 2026): NO active suit seeks to block or delay the federal statutory deadline (Dec 31 2026 / Jan 1 2027). Georgia is the only state with a work-requirement waiver (expiring 2026-12-31); states are not advancing new 1115 waivers. National Health Law Program records show recent work-requirement cases being dismissed. Commentators expect challenges to specific IFR provisions (medically frail definition, SUD stable-recovery exclusion, look-back period), not to the deadline itself."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Tool result: CMS published the interim final rule 'Community Engagement Requirement for Certain Individuals' on June 3, 2026: 80 hrs/month, compliance beginning January 1, 2027, binding regulation, projecting 2.3M enrollment reduction in FY2027. The administration issuing the rule on schedule signals intent to implement, not delay — evidence against the statutory-delay leg.","Reference class — federal health-program compliance deadlines slipping. The outside view: signature reconciliation provisions rarely get statutorily delayed inside their first implementation quarter (the enacting majority would have to reverse itself). The closest precedents cut against a delay meeting THIS bar: the ACA employer mandate was delayed administratively (2013), not by statute and not via a court order; the Medicaid unwinding timeline shifted through CMS guidance and state-specific extensions, not a nationwide statutory delay or stay; and the 2018–19 work-requirement litigation produced waiver vacaturs (Gresham/Arkansas), which is a different legal posture than staying a statute. Each analogue shows pressure relieved through administrative/state channels — exactly the channels this cell's resolution rule excludes from 'failure'."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 14, distribution present, forecast step count 1.","evidence":["P(fail) = 0.06 + 0.05 − 0.003 = 0.107 → P(hold) = 0.893 ≈ 89%. Propagating the parameter ranges gives P(hold) ∈ [82%, 93%]; I widen the lower bound slightly to 80% for model risk (unmodeled late-2026 implementation politics, e.g. a chaotic rollout shifting congressional will). 80% interval [80, 94]. This is up from the prior 85% specifically because Trump v. CASA — decided after the earlier estimate's framing — removed most of the nationwide-stay mass, and the on-schedule June 2026 IFR is fresh evidence of implementation intent.","Counter-consideration — what would move this down. A genuinely chaotic implementation in late 2026 (mass erroneous disenrollments, the kind of confusion Arkansas saw with 33% unaware) could flip congressional politics toward a bipartisan delay, or prompt a court to certify a nationwide class and grant class-wide relief that effectively suspends the deadline. Either path is live but each is a minority branch on a three-month horizon. The interval's 80% floor encodes that risk; the cell would update fast if a delay bill gained a floor vote or a class were certified."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: The law lets the HHS Secretary grant states 'good faith effort' exemptions that expire no later than December 31, 2028. Crucially, the resolution rule treats Secretary-granted STATE extensions as NOT triggering failure — only a nationwide statutory delay or nationwide court stay counts. This safety valve makes a sweeping NATIONAL delay less likely, because political pressure can be vented state-by-state without moving the federal deadline.","Reference class — federal health-program compliance deadlines slipping. The outside view: signature reconciliation provisions rarely get statutorily delayed inside their first implementation quarter (the enacting majority would have to reverse itself). The closest precedents cut against a delay meeting THIS bar: the ACA employer mandate was delayed administratively (2013), not by statute and not via a court order; the Medicaid unwinding timeline shifted through CMS guidance and state-specific extensions, not a nationwide statutory delay or stay; and the 2018–19 work-requirement litigation produced waiver vacaturs (Gresham/Arkansas), which is a different legal posture than staying a statute. Each analogue shows pressure relieved through administrative/state channels — exactly the channels this cell's resolution rule excludes from 'failure'."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["P(fail) = 0.06 + 0.05 − 0.003 = 0.107 → P(hold) = 0.893 ≈ 89%. Propagating the parameter ranges gives P(hold) ∈ [82%, 93%]; I widen the lower bound slightly to 80% for model risk (unmodeled late-2026 implementation politics, e.g. a chaotic rollout shifting congressional will). 80% interval [80, 94]. This is up from the prior 85% specifically because Trump v. CASA — decided after the earlier estimate's framing — removed most of the nationwide-stay mass, and the on-schedule June 2026 IFR is fresh evidence of implementation intent.","Counter-consideration — what would move this down. A genuinely chaotic implementation in late 2026 (mass erroneous disenrollments, the kind of confusion Arkansas saw with 33% unaware) could flip congressional politics toward a bipartisan delay, or prompt a court to certify a nationwide class and grant class-wide relief that effectively suspends the deadline. Either path is live but each is a minority branch on a three-month horizon. The interval's 80% floor encodes that risk; the cell would update fast if a delay bill gained a floor vote or a class were certified."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["P(fail) = 0.06 + 0.05 − 0.003 = 0.107 → P(hold) = 0.893 ≈ 89%. Propagating the parameter ranges gives P(hold) ∈ [82%, 93%]; I widen the lower bound slightly to 80% for model risk (unmodeled late-2026 implementation politics, e.g. a chaotic rollout shifting congressional will). 80% interval [80, 94]. This is up from the prior 85% specifically because Trump v. CASA — decided after the earlier estimate's framing — removed most of the nationwide-stay mass, and the on-schedule June 2026 IFR is fresh evidence of implementation intent.","Counter-consideration — what would move this down. A genuinely chaotic implementation in late 2026 (mass erroneous disenrollments, the kind of confusion Arkansas saw with 33% unaware) could flip congressional politics toward a bipartisan delay, or prompt a court to certify a nationwide class and grant class-wide relief that effectively suspends the deadline. Either path is live but each is a minority branch on a three-month horizon. The interval's 80% floor encodes that risk; the cell would update fast if a delay bill gained a floor vote or a class were certified."]}],"flags":["no_ledger_target"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-work-req-deadline-in-effect-2027q1\nrunLabel: Headline\nresolutionDate: 2027-03-31\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: resolution clarity (2/4). Flags: no_ledger_target."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-call-wait-mar-2027.2026-06-08T00-00-00-02-00.fcb8aee0d6461d90","runId":"run.medicaid-call-wait-mar-2027.2026-06-08T00-00-00-02-00.fcb8aee0d6461d90","predictionId":"medicaid-call-wait-mar-2027","specId":"spec.medicaid-call-wait-mar-2027","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.03,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["E[wait] = 0.85 x 31 + 0.15 x 20 = 29.4 minutes. Interval from the simulated mixture of the two arm distributions: [19.7, 38.4] at 80% — wider and left-skewed versus the holds arm alone, because the delay scenario drags the lower tail."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Resolves regardless of what policy does — and when it does, the mixture, the arms, and the probability cell all get scored together: one outcome, four calibration receipts."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 18.7, distribution present, forecast step count 1.","evidence":["E[wait] = 0.85 x 31 + 0.15 x 20 = 29.4 minutes. Interval from the simulated mixture of the two arm distributions: [19.7, 38.4] at 80% — wider and left-skewed versus the holds arm alone, because the delay scenario drags the lower tail.","Forecast: point 29.4, 80% interval [19.7, 38.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["E[wait] = 0.85 x 31 + 0.15 x 20 = 29.4 minutes. Interval from the simulated mixture of the two arm distributions: [19.7, 38.4] at 80% — wider and left-skewed versus the holds arm alone, because the delay scenario drags the lower tail."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["E[wait] = 0.85 x 31 + 0.15 x 20 = 29.4 minutes. Interval from the simulated mixture of the two arm distributions: [19.7, 38.4] at 80% — wider and left-skewed versus the holds arm alone, because the delay scenario drags the lower tail."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["This unconditional forecast is derived, not independently estimated: it is the probability-weighted blend of the two conditional arms, with the weight coming from the policy-state probability cell. The decomposition is the institution's product — anyone can audit which belief (the policy odds or the conditional outcomes) drives the headline number.","E[wait] = 0.85 x 31 + 0.15 x 20 = 29.4 minutes. Interval from the simulated mixture of the two arm distributions: [19.7, 38.4] at 80% — wider and left-skewed versus the holds arm alone, because the delay scenario drags the lower tail."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-call-wait-mar-2027\nrunLabel: Headline\nresolutionDate: 2027-07-31\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.ca-procedural-share-given-high-ex-parte-aug-2026.2026-06-08T00-00-00-02-00.c98cca4f74a75b1e","runId":"run.ca-procedural-share-given-high-ex-parte-aug-2026.2026-06-08T00-00-00-02-00.c98cca4f74a75b1e","predictionId":"ca-procedural-share-given-high-ex-parte-aug-2026","specId":"spec.ca-procedural-share-given-high-ex-parte-aug-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.89,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 3 historical point(s) and explicit outside-view language.","evidence":["February 2026 baseline: ex parte 76.3, procedural 92.7. Conditioning on ex parte at or above 80 shifts the procedural distribution up roughly 1.5pp relative to the unconditional forecast of 93.0."]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 1 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5, distribution present, forecast step count 1.","evidence":["Under the conditioning event the compositional effect dominates: the interval sits above the unconditional cell, with the lower tail covering successful notice reforms that decouple the two series.","Forecast: point 94.5, 80% interval [91.5, 96.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["February 2026 baseline: ex parte 76.3, procedural 92.7. Conditioning on ex parte at or above 80 shifts the procedural distribution up roughly 1.5pp relative to the unconditional forecast of 93.0."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["This cell isolates the compositional hypothesis behind the unconditional California churn forecast: if ex parte automation reaches 80 percent of completed renewals, the people who still get disenrolled should be even more concentrated in paperwork cases.","February 2026 baseline: ex parte 76.3, procedural 92.7. Conditioning on ex parte at or above 80 shifts the procedural distribution up roughly 1.5pp relative to the unconditional forecast of 93.0."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: ca-procedural-share-given-high-ex-parte-aug-2026\nrunLabel: Headline\nresolutionDate: 2026-12-15\ntraceLineCount: 8\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: source grounding (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-payment-error-rate-fy2026.2026-06-25T03-51-27Z.e784dbf32fb74e9c","runId":"run.snap-payment-error-rate-fy2026.2026-06-25T03-51-27Z.e784dbf32fb74e9c","predictionId":"snap-payment-error-rate-fy2026","specId":"spec.snap-payment-error-rate-fy2026","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.us.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 10.62. Update weight is 0.15 x own FY2024-FY2025 change -0.31 = -0.05; point rounds to 10.6."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.1, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 10.6, 80% interval [9.6, 11.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.us.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.us.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-payment-error-rate-fy2026\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-ak.2026-06-25T03-51-27Z.2e96f52e01da2db2","runId":"run.snap-error-rate-fy2026-ak.2026-06-25T03-51-27Z.2e96f52e01da2db2","predictionId":"snap-error-rate-fy2026-ak","specId":"spec.snap-error-rate-fy2026-ak","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ak.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 23.15. Shrunk trend = 25% own delta -1.51 + 75% panel median 0.12; update weight 0.15 gives -0.04; point rounds to 23.1."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 23.1, 80% interval [21.1, 25.1]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ak.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ak.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-ak\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-al.2026-06-25T03-51-27Z.36d2843a15e5ffde","runId":"run.snap-error-rate-fy2026-al.2026-06-25T03-51-27Z.36d2843a15e5ffde","predictionId":"snap-error-rate-fy2026-al","specId":"spec.snap-error-rate-fy2026-al","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.al.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 9.52. Shrunk trend = 25% own delta 1.2 + 75% panel median 0.12; update weight 0.15 gives 0.06; point rounds to 9.6."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 9.6, 80% interval [7.6, 11.6]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.al.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.al.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-al\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-ar.2026-06-25T03-51-27Z.6cbd383b56d534f2","runId":"run.snap-error-rate-fy2026-ar.2026-06-25T03-51-27Z.6cbd383b56d534f2","predictionId":"snap-error-rate-fy2026-ar","specId":"spec.snap-error-rate-fy2026-ar","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ar.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 8.81. Shrunk trend = 25% own delta -0.75 + 75% panel median 0.12; update weight 0.15 gives -0.01; point rounds to 8.8."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 8.8, 80% interval [6.8, 10.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ar.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ar.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-ar\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-az.2026-06-25T03-51-27Z.38f4eb7b033a4214","runId":"run.snap-error-rate-fy2026-az.2026-06-25T03-51-27Z.38f4eb7b033a4214","predictionId":"snap-error-rate-fy2026-az","specId":"spec.snap-error-rate-fy2026-az","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.az.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 10.8. Shrunk trend = 25% own delta 1.96 + 75% panel median 0.12; update weight 0.15 gives 0.09; point rounds to 10.9."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 10.9, 80% interval [8.9, 12.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.az.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.az.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-az\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-ca.2026-06-25T03-51-27Z.38f4eb7b033a4214","runId":"run.snap-error-rate-fy2026-ca.2026-06-25T03-51-27Z.38f4eb7b033a4214","predictionId":"snap-error-rate-fy2026-ca","specId":"spec.snap-error-rate-fy2026-ca","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ca.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 10.93. Shrunk trend = 25% own delta -0.05 + 75% panel median 0.12; update weight 0.15 gives 0.01; point rounds to 10.9."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 10.9, 80% interval [8.9, 12.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ca.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ca.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-ca\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-co.2026-06-25T03-51-27Z.b9e2702ccb213ce8","runId":"run.snap-error-rate-fy2026-co.2026-06-25T03-51-27Z.b9e2702ccb213ce8","predictionId":"snap-error-rate-fy2026-co","specId":"spec.snap-error-rate-fy2026-co","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.co.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 10.09. Shrunk trend = 25% own delta 0.12 + 75% panel median 0.12; update weight 0.15 gives 0.02; point rounds to 10.1."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 10.1, 80% interval [8.1, 12.1]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.co.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.co.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-co\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-ct.2026-06-25T03-51-27Z.d1ee04c8dd812211","runId":"run.snap-error-rate-fy2026-ct.2026-06-25T03-51-27Z.d1ee04c8dd812211","predictionId":"snap-error-rate-fy2026-ct","specId":"spec.snap-error-rate-fy2026-ct","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ct.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 9.08. Shrunk trend = 25% own delta -1.17 + 75% panel median 0.12; update weight 0.15 gives -0.03; point rounds to 9."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 9, 80% interval [7, 11]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ct.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ct.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-ct\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-dc.2026-06-25T03-51-27Z.97500dfe9b1993fe","runId":"run.snap-error-rate-fy2026-dc.2026-06-25T03-51-27Z.97500dfe9b1993fe","predictionId":"snap-error-rate-fy2026-dc","specId":"spec.snap-error-rate-fy2026-dc","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.dc.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 18.66. Shrunk trend = 25% own delta 1.28 + 75% panel median 0.12; update weight 0.15 gives 0.06; point rounds to 18.7."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 18.7, 80% interval [16.7, 20.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.dc.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.dc.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-dc\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-de.2026-06-25T03-51-27Z.3eecf6af597a0abf","runId":"run.snap-error-rate-fy2026-de.2026-06-25T03-51-27Z.3eecf6af597a0abf","predictionId":"snap-error-rate-fy2026-de","specId":"spec.snap-error-rate-fy2026-de","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.de.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 16. Shrunk trend = 25% own delta 3.63 + 75% panel median 0.12; update weight 0.15 gives 0.15; point rounds to 16.1."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.5, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 16.1, 80% interval [13.8, 18.3]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.de.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.de.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-de\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-fl.2026-06-25T03-51-27Z.f3ec5dd9952016d5","runId":"run.snap-error-rate-fy2026-fl.2026-06-25T03-51-27Z.f3ec5dd9952016d5","predictionId":"snap-error-rate-fy2026-fl","specId":"spec.snap-error-rate-fy2026-fl","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.fl.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 12.97. Shrunk trend = 25% own delta -2.16 + 75% panel median 0.12; update weight 0.15 gives -0.07; point rounds to 12.9."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.1, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 12.9, 80% interval [10.8, 14.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.fl.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.fl.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-fl\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-ga.2026-06-25T03-51-27Z.d95567445ec7ea26","runId":"run.snap-error-rate-fy2026-ga.2026-06-25T03-51-27Z.d95567445ec7ea26","predictionId":"snap-error-rate-fy2026-ga","specId":"spec.snap-error-rate-fy2026-ga","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ga.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 15.21. Shrunk trend = 25% own delta -0.44 + 75% panel median 0.12; update weight 0.15 gives 0; point rounds to 15.2."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 15.2, 80% interval [13.2, 17.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ga.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ga.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-ga\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-gu.2026-06-25T03-51-27Z.09aed5acf86809e7","runId":"run.snap-error-rate-fy2026-gu.2026-06-25T03-51-27Z.09aed5acf86809e7","predictionId":"snap-error-rate-fy2026-gu","specId":"spec.snap-error-rate-fy2026-gu","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.gu.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 11.7. Shrunk trend = 25% own delta 1.98 + 75% panel median 0.12; update weight 0.15 gives 0.09; point rounds to 11.8."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 11.8, 80% interval [9.8, 13.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.gu.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.gu.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-gu\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-hi.2026-06-25T03-51-27Z.4cf2bbe9b2cf6377","runId":"run.snap-error-rate-fy2026-hi.2026-06-25T03-51-27Z.4cf2bbe9b2cf6377","predictionId":"snap-error-rate-fy2026-hi","specId":"spec.snap-error-rate-fy2026-hi","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.hi.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 10.92. Shrunk trend = 25% own delta 4.24 + 75% panel median 0.12; update weight 0.15 gives 0.17; point rounds to 11.1."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.7, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 11.1, 80% interval [8.7, 13.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.hi.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.hi.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-hi\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-ia.2026-06-25T03-51-27Z.b8f9ff34cc85e179","runId":"run.snap-error-rate-fy2026-ia.2026-06-25T03-51-27Z.b8f9ff34cc85e179","predictionId":"snap-error-rate-fy2026-ia","specId":"spec.snap-error-rate-fy2026-ia","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ia.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 5.34. Shrunk trend = 25% own delta -0.8 + 75% panel median 0.12; update weight 0.15 gives -0.02; point rounds to 5.3."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 5.3, 80% interval [3.3, 7.3]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ia.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ia.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-ia\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-id.2026-06-25T03-51-27Z.8f9b193a44fa13ad","runId":"run.snap-error-rate-fy2026-id.2026-06-25T03-51-27Z.8f9b193a44fa13ad","predictionId":"snap-error-rate-fy2026-id","specId":"spec.snap-error-rate-fy2026-id","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.id.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 3.85. Shrunk trend = 25% own delta 0.26 + 75% panel median 0.12; update weight 0.15 gives 0.02; point rounds to 3.9."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 3.9, 80% interval [1.9, 5.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.id.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.id.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-id\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-il.2026-06-25T03-51-27Z.d741760f65530bae","runId":"run.snap-error-rate-fy2026-il.2026-06-25T03-51-27Z.d741760f65530bae","predictionId":"snap-error-rate-fy2026-il","specId":"spec.snap-error-rate-fy2026-il","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.il.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 14.67. Shrunk trend = 25% own delta 3.11 + 75% panel median 0.12; update weight 0.15 gives 0.13; point rounds to 14.8."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.3, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 14.8, 80% interval [12.6, 16.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.il.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.il.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-il\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-in.2026-06-25T03-51-27Z.f74b06da5e030c4b","runId":"run.snap-error-rate-fy2026-in.2026-06-25T03-51-27Z.f74b06da5e030c4b","predictionId":"snap-error-rate-fy2026-in","specId":"spec.snap-error-rate-fy2026-in","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.in.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 9.77. Shrunk trend = 25% own delta 0.25 + 75% panel median 0.12; update weight 0.15 gives 0.02; point rounds to 9.8."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 9.8, 80% interval [7.8, 11.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.in.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.in.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-in\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-ks.2026-06-25T03-51-27Z.e0b769aa1ffb0a61","runId":"run.snap-error-rate-fy2026-ks.2026-06-25T03-51-27Z.e0b769aa1ffb0a61","predictionId":"snap-error-rate-fy2026-ks","specId":"spec.snap-error-rate-fy2026-ks","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ks.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 9.44. Shrunk trend = 25% own delta -0.54 + 75% panel median 0.12; update weight 0.15 gives -0.01; point rounds to 9.4."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 9.4, 80% interval [7.4, 11.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ks.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ks.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-ks\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-ky.2026-06-25T03-51-27Z.f9ef2b1e6c9c807e","runId":"run.snap-error-rate-fy2026-ky.2026-06-25T03-51-27Z.f9ef2b1e6c9c807e","predictionId":"snap-error-rate-fy2026-ky","specId":"spec.snap-error-rate-fy2026-ky","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ky.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 4.7. Shrunk trend = 25% own delta -4.41 + 75% panel median 0.12; update weight 0.15 gives -0.15; point rounds to 4.5."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.7, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 4.5, 80% interval [2.1, 6.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ky.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ky.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-ky\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-la.2026-06-25T03-51-27Z.062abd028994c96e","runId":"run.snap-error-rate-fy2026-la.2026-06-25T03-51-27Z.062abd028994c96e","predictionId":"snap-error-rate-fy2026-la","specId":"spec.snap-error-rate-fy2026-la","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.la.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 8.14. Shrunk trend = 25% own delta 1.52 + 75% panel median 0.12; update weight 0.15 gives 0.07; point rounds to 8.2."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.1, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 8.2, 80% interval [6.1, 10.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.la.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.la.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-la\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-ma.2026-06-25T03-51-27Z.d274a61904bc202a","runId":"run.snap-error-rate-fy2026-ma.2026-06-25T03-51-27Z.d274a61904bc202a","predictionId":"snap-error-rate-fy2026-ma","specId":"spec.snap-error-rate-fy2026-ma","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ma.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 12.49. Shrunk trend = 25% own delta -1.61 + 75% panel median 0.12; update weight 0.15 gives -0.05; point rounds to 12.4."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 12.4, 80% interval [10.4, 14.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ma.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ma.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-ma\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-md.2026-06-25T03-51-27Z.70dc9d82b1f40c7b","runId":"run.snap-error-rate-fy2026-md.2026-06-25T03-51-27Z.70dc9d82b1f40c7b","predictionId":"snap-error-rate-fy2026-md","specId":"spec.snap-error-rate-fy2026-md","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.md.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 13.08. Shrunk trend = 25% own delta -0.56 + 75% panel median 0.12; update weight 0.15 gives -0.01; point rounds to 13.1."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 13.1, 80% interval [11.1, 15.1]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.md.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.md.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-md\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-me.2026-06-25T03-51-27Z.143dcfa5039fbe05","runId":"run.snap-error-rate-fy2026-me.2026-06-25T03-51-27Z.143dcfa5039fbe05","predictionId":"snap-error-rate-fy2026-me","specId":"spec.snap-error-rate-fy2026-me","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.me.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 10.81. Shrunk trend = 25% own delta 0.55 + 75% panel median 0.12; update weight 0.15 gives 0.03; point rounds to 10.8."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 10.8, 80% interval [8.8, 12.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.me.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.me.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-me\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-mi.2026-06-25T03-51-27Z.3c03d3a5557ac198","runId":"run.snap-error-rate-fy2026-mi.2026-06-25T03-51-27Z.3c03d3a5557ac198","predictionId":"snap-error-rate-fy2026-mi","specId":"spec.snap-error-rate-fy2026-mi","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.mi.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 9.89. Shrunk trend = 25% own delta 0.36 + 75% panel median 0.12; update weight 0.15 gives 0.03; point rounds to 9.9."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 9.9, 80% interval [7.9, 11.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.mi.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.mi.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-mi\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-mn.2026-06-25T03-51-27Z.a07c13e4e60fc814","runId":"run.snap-error-rate-fy2026-mn.2026-06-25T03-51-27Z.a07c13e4e60fc814","predictionId":"snap-error-rate-fy2026-mn","specId":"spec.snap-error-rate-fy2026-mn","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.mn.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 12.58. Shrunk trend = 25% own delta 3.6 + 75% panel median 0.12; update weight 0.15 gives 0.15; point rounds to 12.7."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.5, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 12.7, 80% interval [10.4, 14.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.mn.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.mn.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-mn\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-mo.2026-06-25T03-51-27Z.2e343bac4d360023","runId":"run.snap-error-rate-fy2026-mo.2026-06-25T03-51-27Z.2e343bac4d360023","predictionId":"snap-error-rate-fy2026-mo","specId":"spec.snap-error-rate-fy2026-mo","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.mo.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 8.67. Shrunk trend = 25% own delta -0.75 + 75% panel median 0.12; update weight 0.15 gives -0.01; point rounds to 8.7."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 8.7, 80% interval [6.7, 10.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.mo.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.mo.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-mo\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-ms.2026-06-25T03-51-27Z.ec1864dfb4468565","runId":"run.snap-error-rate-fy2026-ms.2026-06-25T03-51-27Z.ec1864dfb4468565","predictionId":"snap-error-rate-fy2026-ms","specId":"spec.snap-error-rate-fy2026-ms","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ms.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 9.51. Shrunk trend = 25% own delta -1.18 + 75% panel median 0.12; update weight 0.15 gives -0.03; point rounds to 9.5."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 9.5, 80% interval [7.5, 11.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ms.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ms.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-ms\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-mt.2026-06-25T03-51-27Z.91ea5f682e56724c","runId":"run.snap-error-rate-fy2026-mt.2026-06-25T03-51-27Z.91ea5f682e56724c","predictionId":"snap-error-rate-fy2026-mt","specId":"spec.snap-error-rate-fy2026-mt","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.mt.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 8.86. Shrunk trend = 25% own delta -0.03 + 75% panel median 0.12; update weight 0.15 gives 0.01; point rounds to 8.9."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 8.9, 80% interval [6.9, 10.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.mt.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.mt.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-mt\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-nc.2026-06-25T03-51-27Z.22ac54f4da9fa20a","runId":"run.snap-error-rate-fy2026-nc.2026-06-25T03-51-27Z.22ac54f4da9fa20a","predictionId":"snap-error-rate-fy2026-nc","specId":"spec.snap-error-rate-fy2026-nc","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.nc.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 7.36. Shrunk trend = 25% own delta -2.85 + 75% panel median 0.12; update weight 0.15 gives -0.09; point rounds to 7.3."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.3, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 7.3, 80% interval [5.1, 9.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.nc.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.nc.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-nc\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-nd.2026-06-25T03-51-27Z.caf6670e7f07f9e9","runId":"run.snap-error-rate-fy2026-nd.2026-06-25T03-51-27Z.caf6670e7f07f9e9","predictionId":"snap-error-rate-fy2026-nd","specId":"spec.snap-error-rate-fy2026-nd","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.nd.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 9.89. Shrunk trend = 25% own delta 1.98 + 75% panel median 0.12; update weight 0.15 gives 0.09; point rounds to 10."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 10, 80% interval [8, 12]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.nd.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.nd.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-nd\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-ne.2026-06-25T03-51-27Z.ac97772d83c2b5fe","runId":"run.snap-error-rate-fy2026-ne.2026-06-25T03-51-27Z.ac97772d83c2b5fe","predictionId":"snap-error-rate-fy2026-ne","specId":"spec.snap-error-rate-fy2026-ne","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ne.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 5.9. Shrunk trend = 25% own delta 0.4 + 75% panel median 0.12; update weight 0.15 gives 0.03; point rounds to 5.9."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 5.9, 80% interval [3.9, 7.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ne.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ne.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-ne\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-nh.2026-06-25T03-51-27Z.91ea5f682e56724c","runId":"run.snap-error-rate-fy2026-nh.2026-06-25T03-51-27Z.91ea5f682e56724c","predictionId":"snap-error-rate-fy2026-nh","specId":"spec.snap-error-rate-fy2026-nh","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.nh.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 8.85. Shrunk trend = 25% own delta 1.28 + 75% panel median 0.12; update weight 0.15 gives 0.06; point rounds to 8.9."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 8.9, 80% interval [6.9, 10.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.nh.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.nh.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-nh\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-nj.2026-06-25T03-51-27Z.b2cfbb4e4ae7a481","runId":"run.snap-error-rate-fy2026-nj.2026-06-25T03-51-27Z.b2cfbb4e4ae7a481","predictionId":"snap-error-rate-fy2026-nj","specId":"spec.snap-error-rate-fy2026-nj","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.nj.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 6.86. Shrunk trend = 25% own delta -7.47 + 75% panel median 0.12; update weight 0.15 gives -0.27; point rounds to 6.6."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5.7, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 6.6, 80% interval [3.7, 9.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.nj.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.nj.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-nj\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-nm.2026-06-25T03-51-27Z.950824310c212d6c","runId":"run.snap-error-rate-fy2026-nm.2026-06-25T03-51-27Z.950824310c212d6c","predictionId":"snap-error-rate-fy2026-nm","specId":"spec.snap-error-rate-fy2026-nm","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.nm.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 16.81. Shrunk trend = 25% own delta 2.2 + 75% panel median 0.12; update weight 0.15 gives 0.1; point rounds to 16.9."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.1, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 16.9, 80% interval [14.8, 18.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.nm.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.nm.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-nm\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-nv.2026-06-25T03-51-27Z.0fc429cb0ac8a84a","runId":"run.snap-error-rate-fy2026-nv.2026-06-25T03-51-27Z.0fc429cb0ac8a84a","predictionId":"snap-error-rate-fy2026-nv","specId":"spec.snap-error-rate-fy2026-nv","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.nv.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 6.22. Shrunk trend = 25% own delta 0.28 + 75% panel median 0.12; update weight 0.15 gives 0.02; point rounds to 6.2."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 6.2, 80% interval [4.2, 8.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.nv.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.nv.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-nv\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-ny.2026-06-25T03-51-27Z.1448fa47b1a7c7a7","runId":"run.snap-error-rate-fy2026-ny.2026-06-25T03-51-27Z.1448fa47b1a7c7a7","predictionId":"snap-error-rate-fy2026-ny","specId":"spec.snap-error-rate-fy2026-ny","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ny.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 13.18. Shrunk trend = 25% own delta -0.91 + 75% panel median 0.12; update weight 0.15 gives -0.02; point rounds to 13.2."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.1, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 13.2, 80% interval [11.1, 15.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ny.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ny.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-ny\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-oh.2026-06-25T03-51-27Z.083b7954cfdc5eb9","runId":"run.snap-error-rate-fy2026-oh.2026-06-25T03-51-27Z.083b7954cfdc5eb9","predictionId":"snap-error-rate-fy2026-oh","specId":"spec.snap-error-rate-fy2026-oh","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.oh.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 6.76. Shrunk trend = 25% own delta -2.25 + 75% panel median 0.12; update weight 0.15 gives -0.07; point rounds to 6.7."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.1, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 6.7, 80% interval [4.6, 8.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.oh.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.oh.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-oh\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-ok.2026-06-25T03-51-27Z.e2385cf303b76202","runId":"run.snap-error-rate-fy2026-ok.2026-06-25T03-51-27Z.e2385cf303b76202","predictionId":"snap-error-rate-fy2026-ok","specId":"spec.snap-error-rate-fy2026-ok","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ok.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 11.04. Shrunk trend = 25% own delta 0.17 + 75% panel median 0.12; update weight 0.15 gives 0.02; point rounds to 11.1."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 11.1, 80% interval [9.1, 13.1]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ok.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ok.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-ok\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-or.2026-06-25T03-51-27Z.00d65eb97ca7db47","runId":"run.snap-error-rate-fy2026-or.2026-06-25T03-51-27Z.00d65eb97ca7db47","predictionId":"snap-error-rate-fy2026-or","specId":"spec.snap-error-rate-fy2026-or","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.or.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 14.14. Shrunk trend = 25% own delta 0.08 + 75% panel median 0.12; update weight 0.15 gives 0.02; point rounds to 14.2."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.1, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 14.2, 80% interval [12.1, 16.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.or.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.or.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-or\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-pa.2026-06-25T03-51-27Z.d495296f1984ff8f","runId":"run.snap-error-rate-fy2026-pa.2026-06-25T03-51-27Z.d495296f1984ff8f","predictionId":"snap-error-rate-fy2026-pa","specId":"spec.snap-error-rate-fy2026-pa","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.pa.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 9.21. Shrunk trend = 25% own delta -1.55 + 75% panel median 0.12; update weight 0.15 gives -0.04; point rounds to 9.2."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 9.2, 80% interval [7.2, 11.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.pa.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.pa.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-pa\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-ri.2026-06-25T03-51-27Z.d274a61904bc202a","runId":"run.snap-error-rate-fy2026-ri.2026-06-25T03-51-27Z.d274a61904bc202a","predictionId":"snap-error-rate-fy2026-ri","specId":"spec.snap-error-rate-fy2026-ri","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ri.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 12.42. Shrunk trend = 25% own delta 0.13 + 75% panel median 0.12; update weight 0.15 gives 0.02; point rounds to 12.4."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 12.4, 80% interval [10.4, 14.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ri.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ri.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-ri\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-sc.2026-06-25T03-51-27Z.6cbd383b56d534f2","runId":"run.snap-error-rate-fy2026-sc.2026-06-25T03-51-27Z.6cbd383b56d534f2","predictionId":"snap-error-rate-fy2026-sc","specId":"spec.snap-error-rate-fy2026-sc","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.sc.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 8.8. Shrunk trend = 25% own delta -0.45 + 75% panel median 0.12; update weight 0.15 gives 0; point rounds to 8.8."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 8.8, 80% interval [6.8, 10.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.sc.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.sc.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-sc\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-sd.2026-06-25T03-51-27Z.6782e6d3c18ae40a","runId":"run.snap-error-rate-fy2026-sd.2026-06-25T03-51-27Z.6782e6d3c18ae40a","predictionId":"snap-error-rate-fy2026-sd","specId":"spec.snap-error-rate-fy2026-sd","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.sd.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 2.47. Shrunk trend = 25% own delta -0.81 + 75% panel median 0.12; update weight 0.15 gives -0.02; point rounds to 2.5."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 2.5, 80% interval [0.5, 4.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.sd.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.sd.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-sd\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-tn.2026-06-25T03-51-27Z.ec1864dfb4468565","runId":"run.snap-error-rate-fy2026-tn.2026-06-25T03-51-27Z.ec1864dfb4468565","predictionId":"snap-error-rate-fy2026-tn","specId":"spec.snap-error-rate-fy2026-tn","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.tn.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 9.44. Shrunk trend = 25% own delta -0.03 + 75% panel median 0.12; update weight 0.15 gives 0.01; point rounds to 9.5."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 9.5, 80% interval [7.5, 11.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.tn.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.tn.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-tn\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-tx.2026-06-25T03-51-27Z.e0b769aa1ffb0a61","runId":"run.snap-error-rate-fy2026-tx.2026-06-25T03-51-27Z.e0b769aa1ffb0a61","predictionId":"snap-error-rate-fy2026-tx","specId":"spec.snap-error-rate-fy2026-tx","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.tx.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 9.34. Shrunk trend = 25% own delta 1.02 + 75% panel median 0.12; update weight 0.15 gives 0.05; point rounds to 9.4."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 9.4, 80% interval [7.4, 11.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.tx.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.tx.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-tx\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-ut.2026-06-25T03-51-27Z.a05d945aa865170a","runId":"run.snap-error-rate-fy2026-ut.2026-06-25T03-51-27Z.a05d945aa865170a","predictionId":"snap-error-rate-fy2026-ut","specId":"spec.snap-error-rate-fy2026-ut","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ut.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 5.54. Shrunk trend = 25% own delta -0.2 + 75% panel median 0.12; update weight 0.15 gives 0.01; point rounds to 5.5."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 5.5, 80% interval [3.5, 7.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ut.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.ut.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-ut\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-va.2026-06-25T03-51-27Z.d274a61904bc202a","runId":"run.snap-error-rate-fy2026-va.2026-06-25T03-51-27Z.d274a61904bc202a","predictionId":"snap-error-rate-fy2026-va","specId":"spec.snap-error-rate-fy2026-va","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.va.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 12.32. Shrunk trend = 25% own delta 0.82 + 75% panel median 0.12; update weight 0.15 gives 0.04; point rounds to 12.4."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 12.4, 80% interval [10.4, 14.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.va.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.va.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-va\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-vi.2026-06-25T03-51-27Z.1a32297b45a701b0","runId":"run.snap-error-rate-fy2026-vi.2026-06-25T03-51-27Z.1a32297b45a701b0","predictionId":"snap-error-rate-fy2026-vi","specId":"spec.snap-error-rate-fy2026-vi","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.vi.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 5.36. Shrunk trend = 25% own delta 1.82 + 75% panel median 0.12; update weight 0.15 gives 0.08; point rounds to 5.4."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 5.4, 80% interval [3.4, 7.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.vi.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.vi.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-vi\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-vt.2026-06-25T03-51-27Z.1a32297b45a701b0","runId":"run.snap-error-rate-fy2026-vt.2026-06-25T03-51-27Z.1a32297b45a701b0","predictionId":"snap-error-rate-fy2026-vt","specId":"spec.snap-error-rate-fy2026-vt","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.vt.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 5.38. Shrunk trend = 25% own delta 0.25 + 75% panel median 0.12; update weight 0.15 gives 0.02; point rounds to 5.4."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 5.4, 80% interval [3.4, 7.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.vt.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.vt.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-vt\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-wa.2026-06-25T03-51-27Z.b8dcd569ed773af7","runId":"run.snap-error-rate-fy2026-wa.2026-06-25T03-51-27Z.b8dcd569ed773af7","predictionId":"snap-error-rate-fy2026-wa","specId":"spec.snap-error-rate-fy2026-wa","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.wa.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 6.98. Shrunk trend = 25% own delta 0.92 + 75% panel median 0.12; update weight 0.15 gives 0.05; point rounds to 7."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 7, 80% interval [5, 9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.wa.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.wa.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-wa\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-wi.2026-06-25T03-51-27Z.7f0935c226c6271f","runId":"run.snap-error-rate-fy2026-wi.2026-06-25T03-51-27Z.7f0935c226c6271f","predictionId":"snap-error-rate-fy2026-wi","specId":"spec.snap-error-rate-fy2026-wi","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.wi.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 5.72. Shrunk trend = 25% own delta 1.25 + 75% panel median 0.12; update weight 0.15 gives 0.06; point rounds to 5.8."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 5.8, 80% interval [3.8, 7.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.wi.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.wi.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-wi\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-wv.2026-06-25T03-51-27Z.20f6ce774898bed7","runId":"run.snap-error-rate-fy2026-wv.2026-06-25T03-51-27Z.20f6ce774898bed7","predictionId":"snap-error-rate-fy2026-wv","specId":"spec.snap-error-rate-fy2026-wv","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.wv.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 6.69. Shrunk trend = 25% own delta -2.74 + 75% panel median 0.12; update weight 0.15 gives -0.09; point rounds to 6.6."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4.3, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 6.6, 80% interval [4.4, 8.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.wv.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.wv.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-wv\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-error-rate-fy2026-wy.2026-06-25T03-51-27Z.8f9b193a44fa13ad","runId":"run.snap-error-rate-fy2026-wy.2026-06-25T03-51-27Z.8f9b193a44fa13ad","predictionId":"snap-error-rate-fy2026-wy","specId":"spec.snap-error-rate-fy2026-wy","runLabel":"Brier base-rate prior","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate prior","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.wy.fy2025\" })","Tool result: { jurisdictions: 53, median_delta: 0.12, p10_delta: -2.05, p90_delta: 1.98 }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Prior = FY2025 first print 3.96. Shrunk trend = 25% own delta -1.16 + 75% panel median 0.12; update weight 0.15 gives -0.03; point rounds to 3.9."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 4, distribution present, forecast step count 1.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments.","Forecast: point 3.9, 80% interval [1.9, 5.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: broad corrective-action gains or favorable QC arbitration. Upside risk: caseload churn, sampling volatility, or state implementation problems offset expected accuracy investments."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.wy.fy2025\" })","Tool call: catalog.lookup({ dataPointId: \"fns.snap.total_payment_error_rate.wy.fy2025\", history: \"FY 2024\" })"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-error-rate-fy2026-wy\nrunLabel: Brier base-rate prior\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-overpayment-error-rate-fy2026.2026-06-25T03-51-27Z.1751ff9fc6bbb83d","runId":"run.snap-overpayment-error-rate-fy2026.2026-06-25T03-51-27Z.1751ff9fc6bbb83d","predictionId":"snap-overpayment-error-rate-fy2026","specId":"spec.snap-overpayment-error-rate-fy2026","runLabel":"SNAP component error-rate model","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate = FY2025 first print 9.28. The damped trend uses 35% of the FY2024-FY2025 log change from 9.26 to 9.28; point rounds to 9.3 with an 80% interval [8, 10.8]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.overpayment_payment_error_rate.us.fy2024.official_release\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.overpayment_payment_error_rate.us.fy2024.official_release\" })","Tool call: fns.lookup({ release: \"FY 2025 SNAP QC PER\", series: \"overpayment_payment_error_rate_us\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.8, distribution present, forecast step count 1.","evidence":["Base rate = FY2025 first print 9.28. The damped trend uses 35% of the FY2024-FY2025 log change from 9.26 to 9.28; point rounds to 9.3 with an 80% interval [8, 10.8].","Downside risk: corrective-action gains or QC arbitration lower the component below the interval. Upside risk: state implementation problems, caseload churn, or sampling noise push it above the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["This is deliberately a model-backed component forecast, not a free-form agent estimate. The model is damped because the component split can move mechanically with QC rules, arbitration, and state reporting practices."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: corrective-action gains or QC arbitration lower the component below the interval. Upside risk: state implementation problems, caseload churn, or sampling noise push it above the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.overpayment_payment_error_rate.us.fy2024.official_release\" })","This is deliberately a model-backed component forecast, not a free-form agent estimate. The model is damped because the component split can move mechanically with QC rules, arbitration, and state reporting practices."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-overpayment-error-rate-fy2026\nrunLabel: SNAP component error-rate model\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.snap-underpayment-error-rate-fy2026.2026-06-25T03-51-27Z.fa36b902c513023a","runId":"run.snap-underpayment-error-rate-fy2026.2026-06-25T03-51-27Z.fa36b902c513023a","predictionId":"snap-underpayment-error-rate-fy2026","specId":"spec.snap-underpayment-error-rate-fy2026","runLabel":"SNAP component error-rate model","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 2 historical point(s) and explicit outside-view language.","evidence":["Base rate = FY2025 first print 1.33. The damped trend uses 35% of the FY2024-FY2025 log change from 1.67 to 1.33; point rounds to 1.2 with an 80% interval [1, 1.6]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.underpayment_payment_error_rate.us.fy2024.official_release\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.underpayment_payment_error_rate.us.fy2024.official_release\" })","Tool call: fns.lookup({ release: \"FY 2025 SNAP QC PER\", series: \"underpayment_payment_error_rate_us\" })"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.6, distribution present, forecast step count 1.","evidence":["Base rate = FY2025 first print 1.33. The damped trend uses 35% of the FY2024-FY2025 log change from 1.67 to 1.33; point rounds to 1.2 with an 80% interval [1, 1.6].","Downside risk: corrective-action gains or QC arbitration lower the component below the interval. Upside risk: state implementation problems, caseload churn, or sampling noise push it above the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["This is deliberately a model-backed component forecast, not a free-form agent estimate. The model is damped because the component split can move mechanically with QC rules, arbitration, and state reporting practices."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Downside risk: corrective-action gains or QC arbitration lower the component below the interval. Upside risk: state implementation problems, caseload churn, or sampling noise push it above the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: ledger.lookup({ dataPointId: \"fns.snap.underpayment_payment_error_rate.us.fy2024.official_release\" })","This is deliberately a model-backed component forecast, not a free-form agent estimate. The model is damped because the component split can move mechanically with QC rules, arbitration, and state reporting practices."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: snap-underpayment-error-rate-fy2026\nrunLabel: SNAP component error-rate model\nresolutionDate: 2027-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.industrial-production-mom-may-2026.2026-06-12T18-32-08Z.a568db54594929de","runId":"run.industrial-production-mom-may-2026.2026-06-12T18-32-08Z.a568db54594929de","predictionId":"industrial-production-mom-may-2026","specId":"spec.industrial-production-mom-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 7 historical point(s) and implicit outside-view language.","evidence":["Industrial production has a low average drift (~+0.1%/mo) and a strong recent tendency to alternate sign. With April printing +0.68%, the base case for May is flat-to-slightly-positive.","Tool result: {\"n\":24,\"mean\":0.094,\"median\":-0.008,\"std_samp\":0.506,\"min\":-0.91,\"max\":1.04,\"last3_mean\":0.336}"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["What lands it outside [-0.5%, +0.7%]: a large motor-vehicle assembly swing, a weather-driven utilities spike/drop, a mining/energy output shock, or a sudden manufacturing contraction (below -0.5%). A second consecutive strong manufacturing month could push above +0.7%."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: WebFetch federalreserve.gov/feeds/g17.html -> 2026 G.17 release schedule","Tool result: {\"2026_g17_dates\":[\"Jan 16\",\"Feb 18\",\"Mar 16\",\"Apr 16\",\"May 15\",\"Jun 15\",\"Jul 17\",\"Aug 18\",\"Sep 18\",\"Oct 16\",\"Nov 17\",\"Dec 16\"],\"may_2026_data_release\":\"2026-06-15\",\"time\":\"09:15 ET\"}"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.2, distribution present, forecast step count 1.","evidence":["Point: trailing-24 mean (+0.09%) rounded to +0.1%, nudged down slightly for the post-strong-month alternation pattern. 80% CI from realized vol: half-width = 1.28*0.51 = 0.65pp -> rounded to 0.6pp. Interval = 0.1 +/- 0.6 = [-0.5%, +0.7%].","Forecast: point 0.1, 80% interval [-0.5, 0.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Point: trailing-24 mean (+0.09%) rounded to +0.1%, nudged down slightly for the post-strong-month alternation pattern. 80% CI from realized vol: half-width = 1.28*0.51 = 0.65pp -> rounded to 0.6pp. Interval = 0.1 +/- 0.6 = [-0.5%, +0.7%].","Forecast: point 0.1, 80% interval [-0.5, 0.7]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: industrial-production-mom-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-15\ntraceLineCount: 12\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.housing-starts-may-2026.2026-06-12T18-32-08Z.b92c171158419259","runId":"run.housing-starts-may-2026.2026-06-12T18-32-08Z.b92c171158419259","predictionId":"housing-starts-may-2026","specId":"spec.housing-starts-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.16,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 8 historical point(s) and implicit outside-view language.","evidence":["Tool result: {\"thousands_saar\":{\"2025-12\":1378,\"2026-01\":1385,\"2026-02\":1346,\"2026-03\":1507,\"2026-04\":1465},\"trailing_12mo_mean\":1365,\"trailing_12mo_median\":1362}"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["US housing starts, May 2026 (SAAR, millions)","Tool call: WebFetch census.gov/economic-indicators/calendar-listview.html -> June 2026"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool result: {\"report\":\"New Residential Construction (Building Permits, Housing Starts, Completions)\",\"reference_month\":\"May 2026\",\"release_date\":\"2026-06-16\",\"time\":\"08:30 ET\"}"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.34, distribution present, forecast step count 1.","evidence":["Point: anchor between the 12-mo mean (1365k) and last print (1465k), weighted toward mean-reversion -> 1400k = 1.40M. 80% CI from MoM-change vol: half-width = 1.28*96.6k = 124k; widened to 170k for the preliminary-estimate sampling error. Interval = 1400 +/- 170 = [1230k, 1570k] = [1.23M, 1.57M].","Forecast: point 1.4, 80% interval [1.23, 1.57]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Housing starts is one of the noisiest monthly indicators. The point estimate leans toward the 12-month mean (~1.365M) given that the last two months printed above trend, with a wide CI reflecting realized month-to-month volatility.","Point: anchor between the 12-mo mean (1365k) and last print (1465k), weighted toward mean-reversion -> 1400k = 1.40M. 80% CI from MoM-change vol: half-width = 1.28*96.6k = 124k; widened to 170k for the preliminary-estimate sampling error. Interval = 1400 +/- 170 = [1230k, 1570k] = [1.23M, 1.57M]."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: housing-starts-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-16\ntraceLineCount: 12\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.housing-starts-may-2026.2026-06-15T10-15-00-04-00.housing-starts-control-no-packs.bec076135a40112e","runId":"run.housing-starts-may-2026.2026-06-15T10-15-00-04-00.housing-starts-control-no-packs.bec076135a40112e","predictionId":"housing-starts-may-2026","specId":"spec.housing-starts-may-2026","runLabel":"Scout-2 - no packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 8 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 0 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.44, distribution present, forecast step count 1.","evidence":["Forecast: point 1.35, 80% interval [1.17, 1.61]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 1.35, 80% interval [1.17, 1.61]"]}],"flags":["weak_counterarguments","no_typed_tool_call"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: housing-starts-may-2026\nrunLabel: Scout-2 - no packs\nresolutionDate: 2026-06-16\ntraceLineCount: 3\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments, no_typed_tool_call."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.housing-starts-may-2026.2026-06-15T10-20-00-04-00.housing-starts-activity-packs.72cf69090dcb4d79","runId":"run.housing-starts-may-2026.2026-06-15T10-20-00-04-00.housing-starts-activity-packs.72cf69090dcb4d79","predictionId":"housing-starts-may-2026","specId":"spec.housing-starts-may-2026","runLabel":"Brier-1 - housing packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.19,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 8 historical point(s) and implicit outside-view language.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"housing-activity-nowcast@0.1.0\", \"release-vintage-calibration@0.1.0\"], target: \"us.census.housing_starts.total_saar.2026-05\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"housing-activity-nowcast@0.1.0\", \"release-vintage-calibration@0.1.0\"], target: \"us.census.housing_starts.total_saar.2026-05\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"housing-activity-nowcast@0.1.0\", \"release-vintage-calibration@0.1.0\"], target: \"us.census.housing_starts.total_saar.2026-05\" })","Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"permits_bridge\", \"mortgage_rate_context\", \"preliminary_release_error\"] }"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.36, distribution present, forecast step count 1.","evidence":["The housing pack keeps the high recent-starts signal alive because permits and builder context do not require a full snap-back to the twelve-month mean, while multifamily timing keeps the lower tail open.","Forecast: point 1.45, 80% interval [1.26, 1.62]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The housing pack keeps the high recent-starts signal alive because permits and builder context do not require a full snap-back to the twelve-month mean, while multifamily timing keeps the lower tail open."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 1.45, 80% interval [1.26, 1.62]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: housing-starts-may-2026\nrunLabel: Brier-1 - housing packs\nresolutionDate: 2026-06-16\ntraceLineCount: 5\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.uk-cpih-yoy-may-2026.2026-06-12T18-51-12Z.d72e5a2873cad832","runId":"run.uk-cpih-yoy-may-2026.2026-06-12T18-51-12Z.d72e5a2873cad832","predictionId":"uk-cpih-yoy-may-2026","specId":"spec.uk-cpih-yoy-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.19,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 8 historical point(s) and implicit outside-view language.","evidence":["Realized month-over-month change in the CPIH annual rate over the last 5 transitions = [+0.1, -0.4, 0.0, +0.2, -0.4]; mean = -0.10pp, population stdev = 0.25pp, mean absolute move = 0.22pp. The two -0.4 moves were identifiable base effects (Jan, Apr); the underlying drift excluding those is roughly flat.","Two forces roughly offset for May: (a) energy/'war' pressure flagged by the BoE pushes up; (b) the April level already absorbed the worst base effect and core CPIH is decelerating. Net expectation: roughly flat at the April 3.0 level, modest upside skew. Point estimate 3.0%."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["Tool call: Fetched ONS Consumer price inflation, April 2026 bulletin.","Tool result: Fetched ONS Consumer price inflation, April 2026 bulletin. CPIH 12-month rate by month: Nov-25 3.5, Dec-25 3.6, Jan-26 3.2, Feb-26 3.2, Mar-26 3.4, Apr-26 3.0. April 2026 CPIH monthly change +0.8%; core CPIH 2.8%."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: Confirmed release calendar from the same bulletin: April 2026 data released 20 May 2026; the next release (May 2026 reference month) is scheduled for 17 June 2026.","Tool result: Confirmed release calendar from the same bulletin: April 2026 data released 20 May 2026; the next release (May 2026 reference month) is scheduled for 17 June 2026. This is the resolution date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.6, distribution present, forecast step count 1.","evidence":["Reference class: month-to-month moves in the UK CPIH annual rate. Over the last six months no single-month move exceeded 0.4pp in magnitude. An 80% interval is therefore roughly last value +/- 1.28*0.25 ~ +/- 0.32pp. Centering on 3.0 (the April level) gives an 80% band near [2.7, 3.3].","Outside the [2.7, 3.3] interval if: a sharper energy pass-through (Brent spiking on the conflict) lifts CPIH to ~3.4-3.6 (upside tail), or a surprise services/core downside drags it to ~2.5-2.6 (downside tail). Regulated-utility and rents profiles in May could also surprise; the realized stdev understates tail risk during an active oil shock, so the true tails are slightly fatter than the Gaussian band implies."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Two forces roughly offset for May: (a) energy/'war' pressure flagged by the BoE pushes up; (b) the April level already absorbed the worst base effect and core CPIH is decelerating. Net expectation: roughly flat at the April 3.0 level, modest upside skew. Point estimate 3.0%."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Two forces roughly offset for May: (a) energy/'war' pressure flagged by the BoE pushes up; (b) the April level already absorbed the worst base effect and core CPIH is decelerating. Net expectation: roughly flat at the April 3.0 level, modest upside skew. Point estimate 3.0%.","Outside the [2.7, 3.3] interval if: a sharper energy pass-through (Brent spiking on the conflict) lifts CPIH to ~3.4-3.6 (upside tail), or a surprise services/core downside drags it to ~2.5-2.6 (downside tail). Regulated-utility and rents profiles in May could also surprise; the realized stdev understates tail risk during an active oil shock, so the true tails are slightly fatter than the Gaussian band implies."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Reference class: month-to-month moves in the UK CPIH annual rate. Over the last six months no single-month move exceeded 0.4pp in magnitude. An 80% interval is therefore roughly last value +/- 1.28*0.25 ~ +/- 0.32pp. Centering on 3.0 (the April level) gives an 80% band near [2.7, 3.3].","Two forces roughly offset for May: (a) energy/'war' pressure flagged by the BoE pushes up; (b) the April level already absorbed the worst base effect and core CPIH is decelerating. Net expectation: roughly flat at the April 3.0 level, modest upside skew. Point estimate 3.0%."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: uk-cpih-yoy-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-17\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.fomc-rate-upper-june-2026.2026-06-12T18-32-08Z.3429ac31a9eb0034","runId":"run.fomc-rate-upper-june-2026.2026-06-12T18-32-08Z.3429ac31a9eb0034","predictionId":"fomc-rate-upper-june-2026","specId":"spec.fomc-rate-upper-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.95,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 8 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.25, distribution present, forecast step count 1.","evidence":["Point = modal outcome = 3.75% (P=0.971 >> 0.8, so the 80% HDI is the single value 3.75%). To reflect the only realistic tail honestly, ciLow is set to the cut scenario 3.50% (P=0.029) and ciHigh=3.75%; the interval is one-sided-down because a hike has ~0 probability. Expected value = 0.971*3.75 + 0.029*3.50 = 3.743%, rounding to the modal 3.75%.","Forecast: point 3.75, 80% interval [3.5, 3.75]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Point = modal outcome = 3.75% (P=0.971 >> 0.8, so the 80% HDI is the single value 3.75%). To reflect the only realistic tail honestly, ciLow is set to the cut scenario 3.50% (P=0.029) and ciHigh=3.75%; the interval is one-sided-down because a hike has ~0 probability. Expected value = 0.971*3.75 + 0.029*3.50 = 3.743%, rounding to the modal 3.75%."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The FOMC sets a target RANGE; the resolvable number is its upper limit. The current range is 3.50-3.75% (upper bound 3.75%). The forecast is essentially a hold-vs-cut probability question, dominated by the Fed's recent on-hold stance and market-implied odds.","Point = modal outcome = 3.75% (P=0.971 >> 0.8, so the 80% HDI is the single value 3.75%). To reflect the only realistic tail honestly, ciLow is set to the cut scenario 3.50% (P=0.029) and ciHigh=3.75%; the interval is one-sided-down because a hike has ~0 probability. Expected value = 0.971*3.75 + 0.029*3.50 = 3.743%, rounding to the modal 3.75%."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: fomc-rate-upper-june-2026\nrunLabel: Headline\nresolutionDate: 2026-06-17\ntraceLineCount: 12\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.boe-bank-rate-june-2026.2026-06-12T18-51-12Z.b33aff3526b668a2","runId":"run.boe-bank-rate-june-2026.2026-06-12T18-51-12Z.b33aff3526b668a2","predictionId":"boe-bank-rate-june-2026","specId":"spec.boe-bank-rate-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.51,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 2 historical point(s) and explicit outside-view language.","evidence":["Tool call: Captured the prior two outcomes verbatim from the same source: 'Bank Rate maintained at 3.75% - March 2026' (19 March) and 'Bank Rate maintained at 3.75% - April 2026' (30 April).","Tool result: Captured the prior two outcomes verbatim from the same source: 'Bank Rate maintained at 3.75% - March 2026' (19 March) and 'Bank Rate maintained at 3.75% - April 2026' (30 April). Two consecutive holds at 3.75%."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["Tool result: Captured the prior two outcomes verbatim from the same source: 'Bank Rate maintained at 3.75% - March 2026' (19 March) and 'Bank Rate maintained at 3.75% - April 2026' (30 April). Two consecutive holds at 3.75%."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Tool call: Fetched bankofengland.co.uk 'Interest rates and Bank Rate: our latest decision': 'Current Bank Rate 3.75%', 'Next due: 18 June 2026', 'interest rate held at 3.75%', published 30 April 2026.","Tool result: Fetched bankofengland.co.uk 'Interest rates and Bank Rate: our latest decision': 'Current Bank Rate 3.75%', 'Next due: 18 June 2026', 'interest rate held at 3.75%', published 30 April 2026. Page last updated 26 May 2026."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.25, distribution present, forecast step count 1.","evidence":["Decompose the outcome distribution: P(hold 3.75) ~ 0.93, P(hike to 4.00) ~ 0.06, P(cut to 3.50) ~ 0.01. Expected value 3.75 + 0.06*0.25 - 0.01*0.25 ~ 3.7625, which rounds to the modal 3.75. The 80% interval contains only the modal value at its low end; the high end 4.00 captures the hawkish tail within the upper 20% mass envelope.","Lands outside a point-3.75 expectation only if the energy shock plus a hot May CPI (released 17 June, the day before) pushes a majority to hike to 4.00% — the realistic upside tail and the reason ciHigh is 4.00 rather than 3.75. A cut to 3.50 is essentially ruled out by the Bank's own 'higher later this year' language."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Decompose the outcome distribution: P(hold 3.75) ~ 0.93, P(hike to 4.00) ~ 0.06, P(cut to 3.50) ~ 0.01. Expected value 3.75 + 0.06*0.25 - 0.01*0.25 ~ 3.7625, which rounds to the modal 3.75. The 80% interval contains only the modal value at its low end; the high end 4.00 captures the hawkish tail within the upper 20% mass envelope."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Reference class: G7 central banks with inflation above target and explicitly rising. The base rate for a hold (no cut) is very high in such regimes; cuts essentially never occur while a central bank is publicly forecasting further inflation increases. Among hold-vs-hike, recent BoE meetings resolved to hold.","Decompose the outcome distribution: P(hold 3.75) ~ 0.93, P(hike to 4.00) ~ 0.06, P(cut to 3.50) ~ 0.01. Expected value 3.75 + 0.06*0.25 - 0.01*0.25 ~ 3.7625, which rounds to the modal 3.75. The 80% interval contains only the modal value at its low end; the high end 4.00 captures the hawkish tail within the upper 20% mass envelope."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: boe-bank-rate-june-2026\nrunLabel: Headline\nresolutionDate: 2026-06-18\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.boe-bank-rate-june-2026.2026-06-16T12-28-37Z.boe-bank-rate-june-2026-thesis-analyst-fast-2026-06-16t12-28-37z.7ec2dedec56040d2","runId":"run.boe-bank-rate-june-2026.2026-06-16T12-28-37Z.boe-bank-rate-june-2026-thesis-analyst-fast-2026-06-16t12-28-37z.7ec2dedec56040d2","predictionId":"boe-bank-rate-june-2026","specId":"spec.boe-bank-rate-june-2026","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.32,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 2 historical point(s) and implicit outside-view language.","evidence":["Base-rate/reference-class step: the last three MPC meetings all held at 3.75%, and the most recent vote distribution shifted from February cut dissents to March unanimous hold to April one hike dissent, so the modal reference case for the next meeting is another hold at 3.75%."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 7 source-context item(s), activity log present.","evidence":["The resolver is the first official Bank of England June 2026 MPC Monetary Policy Summary page. Because Bank Rate is a policy decision level, the target is the rate after the announcement, not a later revised statistical series.","Tool call: Opened recent official MPC summaries for February, March, and April 2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is the first official Bank of England June 2026 MPC Monetary Policy Summary page. Because Bank Rate is a policy decision level, the target is the rate after the announcement, not a later revised statistical series.","Tool result: Fetched Current Bank Rate 3.75%, latest decision held at 3.75%, published 30 April 2026, inflation 3.3%, and next due 18 June 2026."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.5, distribution present, forecast step count 1.","evidence":["Counter-consideration: upside inflation and energy-price risks make a 4.00% hike plausible, while weak activity and a loosening labour market keep a 3.50% cut in the broader 80% set; both alternatives are less likely than a hold two days before the scheduled release.","Use the BoE's usual 0.25 percentage-point policy grid. Point estimate is the modal hold, 3.75. For an 80% interval, include the adjacent cut and hike outcomes around the modal decision: ciLow = 3.50, point = 3.75, ciHigh = 4.00."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The resolver is the first official Bank of England June 2026 MPC Monetary Policy Summary page. Because Bank Rate is a policy decision level, the target is the rate after the announcement, not a later revised statistical series."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base-rate/reference-class step: the last three MPC meetings all held at 3.75%, and the most recent vote distribution shifted from February cut dissents to March unanimous hold to April one hike dissent, so the modal reference case for the next meeting is another hold at 3.75%.","Counter-consideration: upside inflation and energy-price risks make a 4.00% hike plausible, while weak activity and a loosening labour market keep a 3.50% cut in the broader 80% set; both alternatives are less likely than a hold two days before the scheduled release."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for the 18 June 2026 Bank of England Bank Rate decision","Use the BoE's usual 0.25 percentage-point policy grid. Point estimate is the modal hold, 3.75. For an 80% interval, include the adjacent cut and hike outcomes around the modal decision: ciLow = 3.50, point = 3.75, ciHigh = 4.00."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: boe-bank-rate-june-2026\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-06-18\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.initial-claims-week-2026-06-13.2026-06-12T18-32-08Z.a820c5baf6c88911","runId":"run.initial-claims-week-2026-06-13.2026-06-12T18-32-08Z.a820c5baf6c88911","predictionId":"initial-claims-week-2026-06-13","specId":"spec.initial-claims-week-2026-06-13","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.19,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 7 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["Tool call: GET fredgraph.csv?id=ICSA (initial claims SA, persons); /1000"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: DOL UI Weekly Claims cadence: Thursdays 08:30 ET, ~5-day lag; latest print (wk 2026-06-06) released Thu 2026-06-11","Tool result: {\"week_ending\":\"2026-06-13\",\"release_date\":\"2026-06-18\",\"time\":\"08:30 ET\",\"basis\":\"deterministic Thursday cadence confirmed by ICSA vintage\"}"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 40, distribution present, forecast step count 1.","evidence":["Point: weight latest print 229k (0.4) and trailing-8 mean 211.5k (0.6) -> ~218.5, then add a small upward nudge for the apparent drift -> 222k. 80% CI from WoW vol: half-width = 1.28*10.9 = 14k, widened to 20k for two-week-ahead uncertainty and seasonal-factor noise. Interval = 222 +/- 20 = [202k, 242k].","Forecast: point 222, 80% interval [202, 242]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Initial claims behave as a noisy near-random walk around a slowly moving mean. The recent mean is ~212k but the last two weeks ticked up to 225k/229k. The forecast splits the difference: a partial mean-reversion off the 229k high toward the low-220s.","Point: weight latest print 229k (0.4) and trailing-8 mean 211.5k (0.6) -> ~218.5, then add a small upward nudge for the apparent drift -> 222k. 80% CI from WoW vol: half-width = 1.28*10.9 = 14k, widened to 20k for two-week-ahead uncertainty and seasonal-factor noise. Interval = 222 +/- 20 = [202k, 242k]."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Initial claims behave as a noisy near-random walk around a slowly moving mean. The recent mean is ~212k but the last two weeks ticked up to 225k/229k. The forecast splits the difference: a partial mean-reversion off the 229k high toward the low-220s.","Point: weight latest print 229k (0.4) and trailing-8 mean 211.5k (0.6) -> ~218.5, then add a small upward nudge for the apparent drift -> 222k. 80% CI from WoW vol: half-width = 1.28*10.9 = 14k, widened to 20k for two-week-ahead uncertainty and seasonal-factor noise. Interval = 222 +/- 20 = [202k, 242k]."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: initial-claims-week-2026-06-13\nrunLabel: Headline\nresolutionDate: 2026-06-18\ntraceLineCount: 12\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.initial-claims-week-2026-06-13.2026-06-15T10-25-00-04-00.claims-0613-control-no-packs.0a0d1b821f8f61e0","runId":"run.initial-claims-week-2026-06-13.2026-06-15T10-25-00-04-00.claims-0613-control-no-packs.0a0d1b821f8f61e0","predictionId":"initial-claims-week-2026-06-13","specId":"spec.initial-claims-week-2026-06-13","runLabel":"Scout-2 - no packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 7 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 0 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 47, distribution present, forecast step count 1.","evidence":["The control partially fades the latest 229k print toward the trailing mean and uses a symmetric weekly-noise interval.","Forecast: point 219, 80% interval [197, 244]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The control partially fades the latest 229k print toward the trailing mean and uses a symmetric weekly-noise interval.","Forecast: point 219, 80% interval [197, 244]"]}],"flags":["weak_counterarguments","no_typed_tool_call"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: initial-claims-week-2026-06-13\nrunLabel: Scout-2 - no packs\nresolutionDate: 2026-06-18\ntraceLineCount: 3\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments, no_typed_tool_call."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.initial-claims-week-2026-06-13.2026-06-15T10-30-00-04-00.claims-0613-labor-packs.a15e2e6770fc1f46","runId":"run.initial-claims-week-2026-06-13.2026-06-15T10-30-00-04-00.claims-0613-labor-packs.a15e2e6770fc1f46","predictionId":"initial-claims-week-2026-06-13","specId":"spec.initial-claims-week-2026-06-13","runLabel":"Brier-1 - claims packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.32,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 7 historical point(s) and implicit outside-view language.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"labor-market-momentum@0.1.0\", \"release-vintage-calibration@0.1.0\"], target: \"us.dol.initial_claims.sa.week_2026-06-13\" })","Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"weekly_claims_base_rate\", \"payroll_openings_cross_check\", \"advance_release_error\"] }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["The pack run respects the latest upshift in weekly claims but does not turn it into a recession signal because payrolls and openings remain consistent with a tight labor market."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"labor-market-momentum@0.1.0\", \"release-vintage-calibration@0.1.0\"], target: \"us.dol.initial_claims.sa.week_2026-06-13\" })","Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"weekly_claims_base_rate\", \"payroll_openings_cross_check\", \"advance_release_error\"] }"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 36, distribution present, forecast step count 1.","evidence":["Forecast: point 225, 80% interval [207, 243]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"labor-market-momentum@0.1.0\", \"release-vintage-calibration@0.1.0\"], target: \"us.dol.initial_claims.sa.week_2026-06-13\" })","The pack run respects the latest upshift in weekly claims but does not turn it into a recession signal because payrolls and openings remain consistent with a tight labor market."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The pack run respects the latest upshift in weekly claims but does not turn it into a recession signal because payrolls and openings remain consistent with a tight labor market."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 225, 80% interval [207, 243]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: initial-claims-week-2026-06-13\nrunLabel: Brier-1 - claims packs\nresolutionDate: 2026-06-18\ntraceLineCount: 5\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.initial-claims-week-2026-06-13.2026-06-16T12-33-22Z.initial-claims-week-2026-06-13-thesis-analyst-fast-2026-06-16t12-33-22z.0db04f1eb4a0e87b","runId":"run.initial-claims-week-2026-06-13.2026-06-16T12-33-22Z.initial-claims-week-2026-06-13-thesis-analyst-fast-2026-06-16t12-33-22z.0db04f1eb4a0e87b","predictionId":"initial-claims-week-2026-06-13","specId":"spec.initial-claims-week-2026-06-13","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.54,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 7 historical point(s) and explicit outside-view language.","evidence":["Tool result: For week ending June 6, 2026, seasonally adjusted initial claims were 229000, up 4000 from the prior unrevised 225000; the four-week moving average was 219000, up 4250.","Tool call: Read the DOL release table for recent and prior-year claims context."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The resolver is the first official DOL ETA Unemployment Insurance Weekly Claims advance seasonally adjusted initial claims figure for the week-ending date June 13, 2026, not any later revised history.","Tool result: Official schedule says the UI Weekly Claims News Release is published each week on Thursday morning at 8:30 AM EST, lists 1 exception date in 2026, Wednesday November 25, 2026, and the page was updated June 11, 2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is the first official DOL ETA Unemployment Insurance Weekly Claims advance seasonally adjusted initial claims figure for the week-ending date June 13, 2026, not any later revised history.","Tool result: Official schedule says the UI Weekly Claims News Release is published each week on Thursday morning at 8:30 AM EST, lists 1 exception date in 2026, Wednesday November 25, 2026, and the page was updated June 11, 2026."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 34, distribution present, forecast step count 1.","evidence":["Blend latest level 229000, prior week 225000, and four-week average 219000 with more weight on persistence: 0.40*229000 + 0.35*225000 + 0.25*219000 = 225100, rounded to the nearest 1000 gives 225000. Set an 80% interval of roughly +/-16000 around the rounded point, giving 209000 to 243000.","Forecast: point 225, 80% interval [209, 243]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Counter-consideration: the latest unadjusted claims rose sharply by 39713 to 228276, and seasonal adjustment expected a large increase of 35595, so a second high print is plausible; however, the SA series often mean-reverts after jumps and the latest 229000 is already above the 219000 four-week average."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for DOL initial claims, week ending June 13, 2026","Blend latest level 229000, prior week 225000, and four-week average 219000 with more weight on persistence: 0.40*229000 + 0.35*225000 + 0.25*219000 = 225100, rounded to the nearest 1000 gives 225000. Set an 80% interval of roughly +/-16000 around the rounded point, giving 209000 to 243000."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: initial-claims-week-2026-06-13\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-06-18\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.japan-core-cpi-yoy-may-2026.2026-06-12T18-51-12Z.595f976a4c022ffe","runId":"run.japan-core-cpi-yoy-may-2026.2026-06-12T18-51-12Z.595f976a4c022ffe","predictionId":"japan-core-cpi-yoy-may-2026","specId":"spec.japan-core-cpi-yoy-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 3 historical point(s) and explicit outside-view language.","evidence":["Tool result: Fetched the Statistics Bureau release schedule (raw table, last updated 23 Jan 2026). Pairs of dates map to (national for prior month, Tokyo for current month): ... May 22 / May 29, June 19 / June 26, July 24 / July 31. The national May 2026 CPI publishes 19 June 2026 (the national April release was 22 May). This is the resolution date.","Direct realized signal is limited (Mar 1.8 -> Apr 1.4, a -0.4pp move driven by the subsidy step). Japan core is normally smooth (typical monthly YoY moves +/-0.1-0.2pp); the -0.4 was a one-off policy/base shift. Absent another subsidy step, a flat-to-slightly-lower May near 1.3-1.5 is most likely. I set the 80% half-width at ~0.4pp to reflect policy-driven jump risk rather than the tiny ordinary-noise stdev."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: Fetched the Statistics Bureau release schedule (raw table, last updated 23 Jan 2026).","Tool result: Fetched the Statistics Bureau release schedule (raw table, last updated 23 Jan 2026). Pairs of dates map to (national for prior month, Tokyo for current month): ... May 22 / May 29, June 19 / June 26, July 24 / July 31. The national May 2026 CPI publishes 19 June 2026 (the national April release was 22 May). This is the resolution date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.8, distribution present, forecast step count 1.","evidence":["Direct realized signal is limited (Mar 1.8 -> Apr 1.4, a -0.4pp move driven by the subsidy step). Japan core is normally smooth (typical monthly YoY moves +/-0.1-0.2pp); the -0.4 was a one-off policy/base shift. Absent another subsidy step, a flat-to-slightly-lower May near 1.3-1.5 is most likely. I set the 80% half-width at ~0.4pp to reflect policy-driven jump risk rather than the tiny ordinary-noise stdev.","Reference class: Japan core CPI monthly YoY changes are among the lowest-variance in the G7 in calm periods (mostly within +/-0.2pp), but subsidy on/off events produce occasional 0.3-0.5pp jumps. Conditioning on an active-subsidy regime, the modal move is small; the tails are driven by subsidy policy changes."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Captured the policy driver from the release commentary: government fuel subsidies are offsetting oil-price pressure from the Iran conflict, which is why core fell to 1.4% despite higher crude.","Tool result: Captured the policy driver from the release commentary: government fuel subsidies are offsetting oil-price pressure from the Iran conflict, which is why core fell to 1.4% despite higher crude. Core-core 1.9% (softest since July 2024) confirms easing underlying momentum."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool call: Captured the policy driver from the release commentary: government fuel subsidies are offsetting oil-price pressure from the Iran conflict, which is why core fell to 1.4% despite higher crude.","Tool result: Captured the policy driver from the release commentary: government fuel subsidies are offsetting oil-price pressure from the Iran conflict, which is why core fell to 1.4% despite higher crude. Core-core 1.9% (softest since July 2024) confirms easing underlying momentum."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["With subsidies still in place and core-core softening, core most likely holds near the April 1.4% level or drifts marginally lower. Point estimate 1.4%.","Lands outside [1.0, 1.8] if: subsidies are scaled back or expire and oil passes through, lifting core toward ~1.9-2.0 (upside tail), or an expanded subsidy / sharp energy drop pulls it below ~1.0 (downside tail). Food (rice) and services pass-through could also surprise to the upside. Because the dominant variable is discretionary subsidy policy, the distribution is bimodal-leaning rather than smooth; the interval captures the central mass but a policy shift could exit it."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: japan-core-cpi-yoy-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-19\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.japan-core-cpi-yoy-may-2026.2026-06-17T01-52-06Z.japan-core-cpi-yoy-may-2026-thesis-analyst-fast-2026-06-17t01-52-06z.ed6fe838e1b99ea4","runId":"run.japan-core-cpi-yoy-may-2026.2026-06-17T01-52-06Z.japan-core-cpi-yoy-may-2026-thesis-analyst-fast-2026-06-17t01-52-06z.ed6fe838e1b99ea4","predictionId":"japan-core-cpi-yoy-may-2026","specId":"spec.japan-core-cpi-yoy-may-2026","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.19,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 3 historical point(s) and implicit outside-view language.","evidence":["Tool result: The CPI index page shows latest monthly results and links to e-Stat; the monthly report page identifies 2020-Base monthly report table access, including table family 1-1 for Japan subgroup indexes.","Tool call: Checked e-Stat monthly report listings and database view for recent release metadata and latest available history."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Tool result: The official schedule lists Japan survey month May with date of release June 19, 2026; the page last update is 23 January 2026.","Tool call: Checked the Statistics Bureau CPI index and monthly report pages for the official table source and e-Stat linkage."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is the Statistics Bureau of Japan/e-Stat first print for the national CPI subgroup 'all items less fresh food' for May 2026, reported as the year-over-year percent change rounded to one decimal.","Tool call: Checked the Statistics Bureau of Japan CPI release schedule page for the May 2026 Japan CPI release date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1, distribution present, forecast step count 1.","evidence":["Anchor at the latest national readings: average of 2026-02 to 2026-04 is (2.9 + 3.0 + 3.1) / 3 = 3.0. The Tokyo May preliminary at 2.8 suggests slight downside versus April, but national core tends to be less volatile, so I keep the point at 3.0 and set an 80% interval of 2.5 to 3.5.","Forecast: point 3, 80% interval [2.5, 3.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Anchor at the latest national readings: average of 2026-02 to 2026-04 is (2.9 + 3.0 + 3.1) / 3 = 3.0. The Tokyo May preliminary at 2.8 suggests slight downside versus April, but national core tends to be less volatile, so I keep the point at 3.0 and set an 80% interval of 2.5 to 3.5."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast Japan May 2026 core CPI excluding fresh food","Tool call: Read recent CPI values used as the numeric forecasting base from the official CPI/e-Stat context."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: japan-core-cpi-yoy-may-2026\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-06-19\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-cpi-yoy-may-2026.2026-06-12T18-51-12Z.4cda521fe1402678","runId":"run.canada-cpi-yoy-may-2026.2026-06-12T18-51-12Z.4cda521fe1402678","predictionId":"canada-cpi-yoy-may-2026","specId":"spec.canada-cpi-yoy-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.22,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 6 historical point(s) and implicit outside-view language.","evidence":["Tool call: Fetched The Daily, February 2026 (260316): all-items +1.8% YoY following +2.3% in January, with the slowdown attributed to the GST/HST tax-break base effect ending February 2025.","Tool result: Fetched The Daily, February 2026 (260316): all-items +1.8% YoY following +2.3% in January, with the slowdown attributed to the GST/HST tax-break base effect ending February 2025. Also confirmed via the 2026-2027 release-dates document that the May 2026 CPI publishes 22 June 2026 and uses updated basket weights effective 15 June."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["Tool call: Queried StatCan WDS API (getDataFromVectorsAndLatestNPeriods, vector 41690973, all-items CPI index NSA).","Tool result: Queried StatCan WDS API (getDataFromVectorsAndLatestNPeriods, vector 41690973, all-items CPI index NSA). Computed 12-month changes: Nov-25 2.2, Dec-25 2.4, Jan-26 2.3, Feb-26 1.8, Mar-26 2.4, Apr-26 2.8. Index levels Apr-25 163.4, Mar-26 167.4, Apr-26 168.0."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool result: Fetched The Daily, February 2026 (260316): all-items +1.8% YoY following +2.3% in January, with the slowdown attributed to the GST/HST tax-break base effect ending February 2025. Also confirmed via the 2026-2027 release-dates document that the May 2026 CPI publishes 22 June 2026 and uses updated basket weights effective 15 June."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1, distribution present, forecast step count 1.","evidence":["Realized month-over-month change in the all-items YoY rate over the last 5 transitions = [+0.2, -0.1, -0.5, +0.6, +0.4]; mean = +0.12pp, population stdev = 0.39pp. Recent-3 mean = +0.17pp (upward drift). An 80% interval is roughly last value +/- 1.28*0.39 ~ +/- 0.50pp.","Lands outside [2.3, 3.3] if: a renewed oil/gasoline surge from the conflict pushes headline to ~3.4-3.5 (upside tail), or the updated basket-weight rebasing plus an energy pullback drags it toward ~2.1-2.2 (downside tail). The basket-weight change is a genuine non-Gaussian wildcard for the May print specifically, so tails are modestly fatter than the realized stdev implies; I widened the band to +/-0.5 partly for this."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool call: Fetched The Daily, February 2026 (260316): all-items +1.8% YoY following +2.3% in January, with the slowdown attributed to the GST/HST tax-break base effect ending February 2025.","Tool result: Fetched The Daily, February 2026 (260316): all-items +1.8% YoY following +2.3% in January, with the slowdown attributed to the GST/HST tax-break base effect ending February 2025. Also confirmed via the 2026-2027 release-dates document that the May 2026 CPI publishes 22 June 2026 and uses updated basket weights effective 15 June."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Realized month-over-month change in the all-items YoY rate over the last 5 transitions = [+0.2, -0.1, -0.5, +0.6, +0.4]; mean = +0.12pp, population stdev = 0.39pp. Recent-3 mean = +0.17pp (upward drift). An 80% interval is roughly last value +/- 1.28*0.39 ~ +/- 0.50pp.","Gasoline's YoY contribution should remain elevated in May (May-2025 gasoline was still soft), but the largest mechanical jumps are behind us and ex-gasoline inflation is easing. Net: roughly flat to slightly up from April's 2.8%. Point estimate 2.8%."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-cpi-yoy-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-22\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-cpi-yoy-may-2026.2026-06-20T09-00-00-04-00.canada-cpi-yoy-may-2026-brier-shadow-no-packs.f96d6a8371381e07","runId":"run.canada-cpi-yoy-may-2026.2026-06-20T09-00-00-04-00.canada-cpi-yoy-may-2026-brier-shadow-no-packs.f96d6a8371381e07","predictionId":"canada-cpi-yoy-may-2026","specId":"spec.canada-cpi-yoy-may-2026","runLabel":"Brier-1 - no packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 6 historical point(s) and implicit outside-view language.","evidence":["The control run starts from April headline CPI and fades the gasoline base effect without decomposing the basket."]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 0 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.1, distribution present, forecast step count 1.","evidence":["Forecast: point 2.6, 80% interval [2.1, 3.2]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 2.6, 80% interval [2.1, 3.2]"]}],"flags":["weak_counterarguments","no_typed_tool_call"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-cpi-yoy-may-2026\nrunLabel: Brier-1 - no packs\nresolutionDate: 2026-06-22\ntraceLineCount: 3\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments, no_typed_tool_call."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-cpi-yoy-may-2026.2026-06-20T09-00-00-04-00.canada-cpi-yoy-may-2026-brier-shadow-with-packs.dbd096f26b206a77","runId":"run.canada-cpi-yoy-may-2026.2026-06-20T09-00-00-04-00.canada-cpi-yoy-may-2026-brier-shadow-with-packs.dbd096f26b206a77","predictionId":"canada-cpi-yoy-may-2026","specId":"spec.canada-cpi-yoy-may-2026","runLabel":"Brier-1 - packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.16,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 6 historical point(s) and implicit outside-view language.","evidence":["Tool call: brier.pack.apply({ target: \"statcan.cpi.allitems.yoy.2026-05\", packs: [\"base-rate-first@0.1.0\", \"energy-price-nowcast@0.1.0\", \"cpi-component-decomposition@0.1.0\", \"release-vintage-calibration@0.1.0\"] })","Tool result: { admitted: 4, mode: \"with_packs\", required_checks: [\"headline_base_rate\",\"energy_nowcast\",\"basket_weight_update\",\"first_print_rounding\"] }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["Tool call: brier.pack.apply({ target: \"statcan.cpi.allitems.yoy.2026-05\", packs: [\"base-rate-first@0.1.0\", \"energy-price-nowcast@0.1.0\", \"cpi-component-decomposition@0.1.0\", \"release-vintage-calibration@0.1.0\"] })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: brier.pack.apply({ target: \"statcan.cpi.allitems.yoy.2026-05\", packs: [\"base-rate-first@0.1.0\", \"energy-price-nowcast@0.1.0\", \"cpi-component-decomposition@0.1.0\", \"release-vintage-calibration@0.1.0\"] })","Tool result: { admitted: 4, mode: \"with_packs\", required_checks: [\"headline_base_rate\",\"energy_nowcast\",\"basket_weight_update\",\"first_print_rounding\"] }"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.3, distribution present, forecast step count 1.","evidence":["The pack run keeps the control's energy base-effect caution but leaves a wider upper tail for gasoline and basket-weight uncertainty.","Forecast: point 2.7, 80% interval [2.1, 3.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The pack run keeps the control's energy base-effect caution but leaves a wider upper tail for gasoline and basket-weight uncertainty."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 2.7, 80% interval [2.1, 3.4]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-cpi-yoy-may-2026\nrunLabel: Brier-1 - packs\nresolutionDate: 2026-06-22\ntraceLineCount: 5\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-cpi-yoy-may-2026.2026-06-17T01-51-10Z.canada-cpi-yoy-may-2026-thesis-analyst-fast-2026-06-17t01-51-10z.dbd096f26b206a77","runId":"run.canada-cpi-yoy-may-2026.2026-06-17T01-51-10Z.canada-cpi-yoy-may-2026-thesis-analyst-fast-2026-06-17t01-51-10z.dbd096f26b206a77","predictionId":"canada-cpi-yoy-may-2026","specId":"spec.canada-cpi-yoy-may-2026","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 6 historical point(s) and explicit outside-view language.","evidence":["Tool result: Fetched April 2026 all-items CPI 12-month change 2.8%, March prior 2.4%, month-over-month CPI 0.4%, seasonally adjusted monthly 0.3%, CPI excluding gasoline 2.0%, energy 19.2%, gasoline 28.6%, fuel oil and other fuels 41.3%.","Tool result: Fetched March 2026 all-items CPI 12-month change 2.4%, February prior 1.8%, month-over-month CPI 0.9%, seasonally adjusted monthly 0.5%, energy 3.9%, gasoline 5.9%, gasoline monthly 21.2%, food from stores 4.4%."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Tool call: Checked Statistics Canada The Daily Consumer Price Index, April 2026 release.","Tool call: Checked Statistics Canada The Daily Consumer Price Index, March 2026 release."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is the first Statistics Canada May 2026 all-items CPI 12-month change for Canada, not seasonally adjusted, published in The Daily and Table 18-10-0004-01 to one decimal percent.","Tool call: Checked Statistics Canada The Daily Consumer Price Index, April 2026 release."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.3, distribution present, forecast step count 1.","evidence":["Anchor on April 2.8. Add about +0.1 for continued energy pass-through and recent upward momentum, subtract about -0.2 for April-specific base effects and a full month of fuel-tax relief, giving 2.7. Use an 80% interval of 2.1 to 3.4 to cover typical one-month CPI surprise plus unusually high gasoline volatility.","Forecast: point 2.7, 80% interval [2.1, 3.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base-rate reference class: the last five headline prints were 2.4, 2.3, 1.8, 2.4, and 2.8 percent, averaging 2.34 percent, while the latest three-month average was about 2.33 percent. The near-term trend and energy shock argue above that base, but not far above April because April already incorporated a large gasoline and carbon-levy base effect.","Anchor on April 2.8. Add about +0.1 for continued energy pass-through and recent upward momentum, subtract about -0.2 for April-specific base effects and a full month of fuel-tax relief, giving 2.7. Use an 80% interval of 2.1 to 3.4 to cover typical one-month CPI surprise plus unusually high gasoline volatility."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base-rate reference class: the last five headline prints were 2.4, 2.3, 1.8, 2.4, and 2.8 percent, averaging 2.34 percent, while the latest three-month average was about 2.33 percent. The near-term trend and energy shock argue above that base, but not far above April because April already incorporated a large gasoline and carbon-levy base effect."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast Canada all-items CPI year-over-year inflation for May 2026","Anchor on April 2.8. Add about +0.1 for continued energy pass-through and recent upward momentum, subtract about -0.2 for April-specific base effects and a full month of fuel-tax relief, giving 2.7. Use an 80% interval of 2.1 to 3.4 to cover typical one-month CPI surprise plus unusually high gasoline volatility."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-cpi-yoy-may-2026\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-06-22\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-indicator-may-2026.2026-06-12T18-51-12Z.a4522739476aeb70","runId":"run.australia-cpi-indicator-may-2026.2026-06-12T18-51-12Z.a4522739476aeb70","predictionId":"australia-cpi-indicator-may-2026","specId":"spec.australia-cpi-indicator-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.05,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 7 historical point(s) and implicit outside-view language.","evidence":["Lands outside [3.5, 4.7] if: an electricity-rebate base/timing effect or a fuel jump (oil conflict) lifts the indicator above ~4.8 (upside tail), or a rebate roll-on or housing-component reversal drops it toward ~3.3-3.4, converging on the trimmed mean (downside tail). Administered-price (electricity rebate) scheduling is the single biggest non-Gaussian swing factor for the Australian monthly print, which is why the band is the widest of the set."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["Realized month-over-month change in the all-groups indicator YoY rate over the last 5 transitions = [+0.4, 0.0, -0.1, +0.9, -0.4]; mean = +0.16pp, population stdev = 0.45pp (the highest of the six series, reflecting the monthly indicator's subset-repricing noise). An 80% half-width ~ 1.28*0.45 ~ 0.58pp."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: Fetched ABS Monthly CPI indicator, April 2026 (released 27 May 2026): all-groups YoY by month Nov-25 3.4, Dec-25 3.8, Jan-26 3.8, Feb-26 3.7","Tool result: Fetched ABS Monthly CPI indicator, April 2026 (released 27 May 2026): all-groups YoY by month Nov-25 3.4, Dec-25 3.8, Jan-26 3.8, Feb-26 3.7, Mar-26 4.6, Apr-26 4.2; April monthly +0.4% original / -0.1% SA; trimmed mean 4-month path 3.2/3.3/3.3/3.3/3.3/3.4."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.2, distribution present, forecast step count 1.","evidence":["Tool call: Captured component detail from the same release: Transport +6.6%, Housing +6.3%, Food +2.8% (largest annual contributors); CPI excl.","Tool result: Captured component detail from the same release: Transport +6.6%, Housing +6.3%, Food +2.8% (largest annual contributors); CPI excl. volatile items & holiday travel 3.9%; goods inflation eased to 4.7% from 5.5%."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool call: Captured component detail from the same release: Transport +6.6%, Housing +6.3%, Food +2.8% (largest annual contributors); CPI excl.","Tool result: Captured component detail from the same release: Transport +6.6%, Housing +6.3%, Food +2.8% (largest annual contributors); CPI excl. volatile items & holiday travel 3.9%; goods inflation eased to 4.7% from 5.5%."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Underlying (trimmed mean 3.4%) is far below headline, so headline is being held up by volatile/administered items (electricity rebates, transport/fuel). With the March spike unwound and goods inflation easing, May most likely settles slightly below April's 4.2, around 4.1, give or take the indicator's wide monthly noise. Point estimate 4.1%.","Forecast: point 4.1, 80% interval [3.5, 4.7]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-indicator-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-24\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-indicator-may-2026.2026-06-20T09-06-00-04-00.australia-cpi-indicator-may-2026-brier-shadow-no-packs.a4522739476aeb70","runId":"run.australia-cpi-indicator-may-2026.2026-06-20T09-06-00-04-00.australia-cpi-indicator-may-2026-brier-shadow-no-packs.a4522739476aeb70","predictionId":"australia-cpi-indicator-may-2026","specId":"spec.australia-cpi-indicator-may-2026","runLabel":"Brier-1 - no packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 7 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 0 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.2, distribution present, forecast step count 1.","evidence":["Forecast: point 4.1, 80% interval [3.5, 4.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The control run holds close to April because it does not separate volatile repriced components from persistent inflation."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 4.1, 80% interval [3.5, 4.7]"]}],"flags":["weak_counterarguments","no_typed_tool_call"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-indicator-may-2026\nrunLabel: Brier-1 - no packs\nresolutionDate: 2026-06-24\ntraceLineCount: 3\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments, no_typed_tool_call."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-indicator-may-2026.2026-06-20T09-06-00-04-00.australia-cpi-indicator-may-2026-brier-shadow-with-packs.8bcb9ac5bfda3881","runId":"run.australia-cpi-indicator-may-2026.2026-06-20T09-06-00-04-00.australia-cpi-indicator-may-2026-brier-shadow-with-packs.8bcb9ac5bfda3881","predictionId":"australia-cpi-indicator-may-2026","specId":"spec.australia-cpi-indicator-may-2026","runLabel":"Brier-1 - packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.92,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 7 historical point(s) and implicit outside-view language.","evidence":["Tool call: brier.pack.apply({ target: \"abs.cpi_indicator.allgroups.yoy.2026-05\", packs: [\"base-rate-first@0.1.0\", \"energy-price-nowcast@0.1.0\", \"cpi-component-decomposition@0.1.0\", \"release-vintage-calibration@0.1.0\"] })","Tool result: { admitted: 4, mode: \"with_packs\", required_checks: [\"monthly_indicator_base_rate\",\"component_repricing\",\"energy_nowcast\",\"release_noise\"] }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: brier.pack.apply({ target: \"abs.cpi_indicator.allgroups.yoy.2026-05\", packs: [\"base-rate-first@0.1.0\", \"energy-price-nowcast@0.1.0\", \"cpi-component-decomposition@0.1.0\", \"release-vintage-calibration@0.1.0\"] })","Tool result: { admitted: 4, mode: \"with_packs\", required_checks: [\"monthly_indicator_base_rate\",\"component_repricing\",\"energy_nowcast\",\"release_noise\"] }"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.6, distribution present, forecast step count 1.","evidence":["The pack run raises the center for housing and transport pressure while explicitly preserving a wide release-noise interval.","Forecast: point 4.5, 80% interval [3.7, 5.3]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The pack run raises the center for housing and transport pressure while explicitly preserving a wide release-noise interval."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The pack run raises the center for housing and transport pressure while explicitly preserving a wide release-noise interval.","Forecast: point 4.5, 80% interval [3.7, 5.3]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-indicator-may-2026\nrunLabel: Brier-1 - packs\nresolutionDate: 2026-06-24\ntraceLineCount: 5\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.initial-claims-week-2026-06-20.2026-06-12T18-32-08Z.f6eaa3fc68d6ba3b","runId":"run.initial-claims-week-2026-06-20.2026-06-12T18-32-08Z.f6eaa3fc68d6ba3b","predictionId":"initial-claims-week-2026-06-20","specId":"spec.initial-claims-week-2026-06-20","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.41,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 7 historical point(s) and explicit outside-view language.","evidence":["Same series as the prior cell, one week further out. With no information yet on the 6/13 print, the best estimate reverts slightly further toward the trailing mean, and the interval is a touch wider to reflect the longer horizon.","What lands it outside [198, 242]: a fresh layoff cluster or seasonal-adjustment overshoot above 242k, or an unusually clean low print (e.g. holiday-week filing dip) below 198k. The further horizon means a 6/13 surprise would also shift the 6/20 baseline."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["Tool call: GET fredgraph.csv?id=ICSA (initial claims SA, persons); /1000"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: DOL UI Weekly Claims cadence: Thursdays 08:30 ET; wk 2026-06-20 -> release 2026-06-25","Tool result: {\"week_ending\":\"2026-06-20\",\"release_date\":\"2026-06-25\",\"time\":\"08:30 ET\",\"basis\":\"deterministic Thursday cadence\"}"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 44, distribution present, forecast step count 1.","evidence":["Same series as the prior cell, one week further out. With no information yet on the 6/13 print, the best estimate reverts slightly further toward the trailing mean, and the interval is a touch wider to reflect the longer horizon.","Point: pull a bit closer to the trailing-8 mean (211.5k) than the 6/13 cell, landing at 220k (vs 222k for the nearer week). 80% CI from WoW vol over a ~2-week-ahead path: half-width = 1.28*10.9*sqrt(1.2) ~ 15.3k, widened to 22k. Interval = 220 +/- 22 = [198k, 242k]."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Same series as the prior cell, one week further out. With no information yet on the 6/13 print, the best estimate reverts slightly further toward the trailing mean, and the interval is a touch wider to reflect the longer horizon.","Point: pull a bit closer to the trailing-8 mean (211.5k) than the 6/13 cell, landing at 220k (vs 222k for the nearer week). 80% CI from WoW vol over a ~2-week-ahead path: half-width = 1.28*10.9*sqrt(1.2) ~ 15.3k, widened to 22k. Interval = 220 +/- 22 = [198k, 242k]."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: initial-claims-week-2026-06-20\nrunLabel: Headline\nresolutionDate: 2026-06-25\ntraceLineCount: 12\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.initial-claims-week-2026-06-20.2026-06-20T09-14-00-04-00.initial-claims-week-2026-06-20-brier-shadow-no-packs.03f532c0353cde1f","runId":"run.initial-claims-week-2026-06-20.2026-06-20T09-14-00-04-00.initial-claims-week-2026-06-20-brier-shadow-no-packs.03f532c0353cde1f","predictionId":"initial-claims-week-2026-06-20","specId":"spec.initial-claims-week-2026-06-20","runLabel":"Brier-1 - no packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 7 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 0 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 48, distribution present, forecast step count 1.","evidence":["Forecast: point 221, 80% interval [198, 246]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 221, 80% interval [198, 246]"]}],"flags":["weak_counterarguments","no_typed_tool_call"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: initial-claims-week-2026-06-20\nrunLabel: Brier-1 - no packs\nresolutionDate: 2026-06-25\ntraceLineCount: 3\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments, no_typed_tool_call."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.initial-claims-week-2026-06-20.2026-06-20T09-14-00-04-00.initial-claims-week-2026-06-20-brier-shadow-with-packs.252cd3fe6ebf8461","runId":"run.initial-claims-week-2026-06-20.2026-06-20T09-14-00-04-00.initial-claims-week-2026-06-20-brier-shadow-with-packs.252cd3fe6ebf8461","predictionId":"initial-claims-week-2026-06-20","specId":"spec.initial-claims-week-2026-06-20","runLabel":"Brier-1 - packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.05,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 7 historical point(s) and implicit outside-view language.","evidence":["Tool call: brier.pack.apply({ target: \"us.dol.initial_claims.sa.week_2026-06-20\", packs: [\"base-rate-first@0.1.0\", \"labor-market-momentum@0.1.0\", \"release-vintage-calibration@0.1.0\"] })","Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"claims_base_rate\",\"labor_momentum\",\"seasonal_factor\",\"weekly_release_noise\"] }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: brier.pack.apply({ target: \"us.dol.initial_claims.sa.week_2026-06-20\", packs: [\"base-rate-first@0.1.0\", \"labor-market-momentum@0.1.0\", \"release-vintage-calibration@0.1.0\"] })","Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"claims_base_rate\",\"labor_momentum\",\"seasonal_factor\",\"weekly_release_noise\"] }"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 45, distribution present, forecast step count 1.","evidence":["Forecast: point 226, 80% interval [205, 250]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: brier.pack.apply({ target: \"us.dol.initial_claims.sa.week_2026-06-20\", packs: [\"base-rate-first@0.1.0\", \"labor-market-momentum@0.1.0\", \"release-vintage-calibration@0.1.0\"] })","Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"claims_base_rate\",\"labor_momentum\",\"seasonal_factor\",\"weekly_release_noise\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 226, 80% interval [205, 250]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: initial-claims-week-2026-06-20\nrunLabel: Brier-1 - packs\nresolutionDate: 2026-06-25\ntraceLineCount: 5\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.initial-claims-week-2026-06-20.2026-06-17T02-23-52Z.initial-claims-week-2026-06-20-thesis-analyst-fast-2026-06-17t02-23-52z.252cd3fe6ebf8461","runId":"run.initial-claims-week-2026-06-20.2026-06-17T02-23-52Z.initial-claims-week-2026-06-20-thesis-analyst-fast-2026-06-17t02-23-52z.252cd3fe6ebf8461","predictionId":"initial-claims-week-2026-06-20","specId":"spec.initial-claims-week-2026-06-20","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 7 historical point(s) and explicit outside-view language.","evidence":["Tool result: Fetched table values: June 6, 2026 SA initial claims 229,000; May 30, 2026 225,000; May 23, 2026 212,000; comparable prior-year June 7, 2025 value 246,000.","Base-rate/reference-class: weekly initial claims are noisy but mean-reverting at a 1-3 week horizon. Recent 2026 levels cluster near 210,000-229,000, while the same June window in 2025 ran 231,000-246,000, so a central forecast should stay near the latest value but not fully extrapolate the late-May jump."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["The resolver is the DOL ETA first-print advance seasonally adjusted initial claims count for the week ending Saturday, June 20, 2026, reported in the Unemployment Insurance Weekly Claims Report. The DOL economic-data page identifies the ETA Office of Unemployment Insurance as the publisher of this weekly report and links the current official PDF.","Tool call: Read the official DOL weekly claims table in the same PDF."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is the DOL ETA first-print advance seasonally adjusted initial claims count for the week ending Saturday, June 20, 2026, reported in the Unemployment Insurance Weekly Claims Report. The DOL economic-data page identifies the ETA Office of Unemployment Insurance as the publisher of this weekly report and links the current official PDF.","Tool call: Opened FRED ICSA as a history mirror and release metadata cross-check."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 45, distribution present, forecast step count 1.","evidence":["Counter-consideration: the June 6 unadjusted actual claims jumped by 39,713 and state moves in California, Minnesota, Pennsylvania, Texas, and other large states show timing noise that could persist into the June 20 week; this raises upside risk even though the seasonally adjusted series may mean-revert.","For an 80% interval, recent weekly moves include +13,000, +4,000, -25,000, and +15,000 over spring 2026, and June school-season volatility can add several thousand more. Around a 226,000 point, a practical 80% range is roughly -21,000/+24,000, giving 205,000 to 250,000."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base-rate/reference-class: weekly initial claims are noisy but mean-reverting at a 1-3 week horizon. Recent 2026 levels cluster near 210,000-229,000, while the same June window in 2025 ran 231,000-246,000, so a central forecast should stay near the latest value but not fully extrapolate the late-May jump.","Recent 5-week average using DOL/FRED values is (212,000 + 210,000 + 212,000 + 225,000 + 229,000) / 5 = 217,600. The latest 4-week average is 219,000. A same-season 2025 anchor for week ending June 21 is 236,000, but current June 6 is 17,000 below the 2025 comparable 246,000, implying an adjusted seasonal anchor near 219,000. I blend latest 229,000, recent-average 218,000, and seasonal-adjusted 219,000, then allow for another school-calendar noisy week to set the point at 226,000."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for DOL seasonally adjusted initial claims, week ending June 20, 2026","Base-rate/reference-class: weekly initial claims are noisy but mean-reverting at a 1-3 week horizon. Recent 2026 levels cluster near 210,000-229,000, while the same June window in 2025 ran 231,000-246,000, so a central forecast should stay near the latest value but not fully extrapolate the late-May jump."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: initial-claims-week-2026-06-20\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-06-25\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.initial-claims-week-2026-06-20.2026-06-21T15-11-54Z.initial-claims-week-2026-06-20-thesis-analyst-fast-2026-06-21t15-11-54z.8618e4ce8e238937","runId":"run.initial-claims-week-2026-06-20.2026-06-21T15-11-54Z.initial-claims-week-2026-06-20-thesis-analyst-fast-2026-06-21t15-11-54z.8618e4ce8e238937","predictionId":"initial-claims-week-2026-06-20","specId":"spec.initial-claims-week-2026-06-20","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.22,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 7 historical point(s) and implicit outside-view language.","evidence":["Base-rate reference class: one-week changes in this series are usually small relative to the level, and the latest sequence 210k, 212k, 225k, 230k, 226k puts a neutral forecast in the low-to-mid 220s rather than implying a new break."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Tool result: Fetched observations 2026-06-13 226,000; 2026-06-06 230,000; 2026-05-30 225,000; 2026-05-23 212,000; 2026-05-16 210,000; next release date Jun 25, 2026.","Counter-consideration: the end-of-school-year period can create seasonal-adjustment noise, so a sharper move toward 235k or back toward 210k is plausible even without a real layoff-cycle shift."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The resolver is the first-print national seasonally adjusted initial claims figure in the ETA weekly claims report for the week ending June 20, 2026; the unit here is thousands of claims.","Tool call: Opened DOL ETA newsroom release listing at https://www.dol.gov/newsroom/releases/eta."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 35, distribution present, forecast step count 1.","evidence":["For an 80% interval, I use roughly +/-17k around the 225k point, reflecting normal weekly volatility and recent early-summer noise: low 208, high 243.","Forecast: point 225, 80% interval [208, 243]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Recent anchors: 3-week average = (226 + 230 + 225) / 3 = 227.0; 5-week average = (226 + 230 + 225 + 212 + 210) / 5 = 220.6; latest 4-week average = 223.25. I put the point at 225, slightly below the 3-week average but above the 5-week average because early-June claims have been elevated versus May."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Recent anchors: 3-week average = (226 + 230 + 225) / 3 = 227.0; 5-week average = (226 + 230 + 225 + 212 + 210) / 5 = 220.6; latest 4-week average = 223.25. I put the point at 225, slightly below the 3-week average but above the 5-week average because early-June claims have been elevated versus May."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for DOL seasonally adjusted initial claims, week ending June 20, 2026","Base-rate reference class: one-week changes in this series are usually small relative to the level, and the latest sequence 210k, 212k, 225k, 230k, 226k puts a neutral forecast in the low-to-mid 220s rather than implying a new break."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: initial-claims-week-2026-06-20\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-06-25\ntraceLineCount: 13\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-core-pce-mom-may-2026.2026-06-12T18-32-08Z.9d9a4b7dab257493","runId":"run.us-core-pce-mom-may-2026.2026-06-12T18-32-08Z.9d9a4b7dab257493","predictionId":"us-core-pce-mom-may-2026","specId":"spec.us-core-pce-mom-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 7 historical point(s) and implicit outside-view language.","evidence":["Tool result: {\"n\":24,\"mean\":0.2427,\"median\":0.2342,\"std_samp\":0.0959,\"min\":0.065,\"max\":0.448,\"last3_mean\":0.310,\"last6_mean\":0.310}"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool result: {\"report\":\"Personal Income and Outlays\",\"reference_month\":\"May 2026\",\"release_date\":\"2026-06-25\",\"time\":\"08:30 ET\"}"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.3, distribution present, forecast step count 1.","evidence":["Point: trailing-24 mean (0.243%) and the decelerating last print (0.24%) coincide -> 0.25% (rounded). 80% CI from realized vol: half-width = 1.28*0.096 = 0.123pp; widened to 0.15pp for rounding and tail risk. Interval = 0.25 +/- 0.15 = [0.10%, 0.40%].","Forecast: point 0.25, 80% interval [0.1, 0.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Point: trailing-24 mean (0.243%) and the decelerating last print (0.24%) coincide -> 0.25% (rounded). 80% CI from realized vol: half-width = 1.28*0.096 = 0.123pp; widened to 0.15pp for rounding and tail risk. Interval = 0.25 +/- 0.15 = [0.10%, 0.40%]."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Core PCE is the Fed's preferred inflation gauge and is comparatively smooth. Recent prints show a clean three-month deceleration toward the trailing mean (~0.24%). The forecast holds near that level with a tight CI given low realized volatility.","Point: trailing-24 mean (0.243%) and the decelerating last print (0.24%) coincide -> 0.25% (rounded). 80% CI from realized vol: half-width = 1.28*0.096 = 0.123pp; widened to 0.15pp for rounding and tail risk. Interval = 0.25 +/- 0.15 = [0.10%, 0.40%]."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-core-pce-mom-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-25\ntraceLineCount: 12\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-core-pce-mom-may-2026.2026-06-14T15-45-00-04-00.core-pce-control-no-packs.d835e32b68b5c093","runId":"run.us-core-pce-mom-may-2026.2026-06-14T15-45-00-04-00.core-pce-control-no-packs.d835e32b68b5c093","predictionId":"us-core-pce-mom-may-2026","specId":"spec.us-core-pce-mom-may-2026","runLabel":"Scout-2 - no packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 7 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 0 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The control holds near the recent core PCE trend and does not ingest CPI components that arrive before the BEA release."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.3, distribution present, forecast step count 1.","evidence":["Forecast: point 0.23, 80% interval [0.08, 0.38]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 0.23, 80% interval [0.08, 0.38]"]}],"flags":["weak_counterarguments","no_typed_tool_call"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-core-pce-mom-may-2026\nrunLabel: Scout-2 - no packs\nresolutionDate: 2026-06-25\ntraceLineCount: 3\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments, no_typed_tool_call."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-core-pce-mom-may-2026.2026-06-15T09-45-00-04-00.core-pce-bridge-packs.39c5495b584cced0","runId":"run.us-core-pce-mom-may-2026.2026-06-15T09-45-00-04-00.core-pce-bridge-packs.39c5495b584cced0","predictionId":"us-core-pce-mom-may-2026","specId":"spec.us-core-pce-mom-may-2026","runLabel":"Brier-1 - PCE bridge packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.24,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 7 historical point(s) and explicit outside-view language.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"pce-cpi-bridge@0.1.0\", \"release-vintage-calibration@0.1.0\"], target: \"us.bea.core_pce.mom_sa.2026-05\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"pce-cpi-bridge@0.1.0\", \"release-vintage-calibration@0.1.0\"], target: \"us.bea.core_pce.mom_sa.2026-05\" })","Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"pce_cpi_scope_bridge\", \"bea_release_calibration\"] }"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.3, distribution present, forecast step count 1.","evidence":["Forecast: point 0.27, 80% interval [0.12, 0.42]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The CPI bridge raises the center modestly because core CPI source data is firm enough to keep BEA core PCE above the no-pack persistence estimate."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 0.27, 80% interval [0.12, 0.42]"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-core-pce-mom-may-2026\nrunLabel: Brier-1 - PCE bridge packs\nresolutionDate: 2026-06-25\ntraceLineCount: 5\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-core-pce-mom-may-2026.2026-06-17T02-16-13Z.us-core-pce-mom-may-2026-thesis-analyst-fast-2026-06-17t02-16-13z.39c5495b584cced0","runId":"run.us-core-pce-mom-may-2026.2026-06-17T02-16-13Z.us-core-pce-mom-may-2026-thesis-analyst-fast-2026-06-17t02-16-13z.39c5495b584cced0","predictionId":"us-core-pce-mom-may-2026","specId":"spec.us-core-pce-mom-may-2026","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.46,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 7 historical point(s) and implicit outside-view language.","evidence":["Base-rate/reference-class: recent core PCE monthly prints cluster between about 0.2 and 0.4 percent, with the FRED-implied latest four monthly changes at 0.239, 0.295, 0.396, and 0.427 percent. The April first print rounded to 0.2 percent despite firm headline PCE, so a May forecast should lean below the raw recent average but above the softer core CPI alone."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["The resolver is the BEA first print for Personal Income and Outlays, May 2026: PCE price index excluding food and energy, seasonally adjusted monthly percent change. This is a first-print forecast, so later BEA revisions should not alter the resolved value.","Tool call: Checked BEA release schedule for the official May 2026 Personal Income and Outlays publication date."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is the BEA first print for Personal Income and Outlays, May 2026: PCE price index excluding food and energy, seasonally adjusted monthly percent change. This is a first-print forecast, so later BEA revisions should not alter the resolved value.","Tool call: Checked BEA release schedule for the official May 2026 Personal Income and Outlays publication date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.3, distribution present, forecast step count 1.","evidence":["Recent FRED-implied core PCE mean for Jan-Apr is (0.427 + 0.396 + 0.295 + 0.239) / 4 = 0.339 percent. I downweight that toward May core CPI of 0.2 because CPI was softer, while adding some PPI-services pressure: 0.55*0.24 latest core PCE momentum + 0.30*0.20 core CPI + 0.15*0.52 PPI-informed pressure = 0.270 percent. An 80 percent interval of 0.12 to 0.42 covers normal nowcast error and component-mapping uncertainty.","Forecast: point 0.27, 80% interval [0.12, 0.42]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Recent FRED-implied core PCE mean for Jan-Apr is (0.427 + 0.396 + 0.295 + 0.239) / 4 = 0.339 percent. I downweight that toward May core CPI of 0.2 because CPI was softer, while adding some PPI-services pressure: 0.55*0.24 latest core PCE momentum + 0.30*0.20 core CPI + 0.15*0.52 PPI-informed pressure = 0.270 percent. An 80 percent interval of 0.12 to 0.42 covers normal nowcast error and component-mapping uncertainty."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base-rate/reference-class: recent core PCE monthly prints cluster between about 0.2 and 0.4 percent, with the FRED-implied latest four monthly changes at 0.239, 0.295, 0.396, and 0.427 percent. The April first print rounded to 0.2 percent despite firm headline PCE, so a May forecast should lean below the raw recent average but above the softer core CPI alone.","Recent FRED-implied core PCE mean for Jan-Apr is (0.427 + 0.396 + 0.295 + 0.239) / 4 = 0.339 percent. I downweight that toward May core CPI of 0.2 because CPI was softer, while adding some PPI-services pressure: 0.55*0.24 latest core PCE momentum + 0.30*0.20 core CPI + 0.15*0.52 PPI-informed pressure = 0.270 percent. An 80 percent interval of 0.12 to 0.42 covers normal nowcast error and component-mapping uncertainty."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for May 2026 core PCE monthly inflation","The resolver is the BEA first print for Personal Income and Outlays, May 2026: PCE price index excluding food and energy, seasonally adjusted monthly percent change. This is a first-print forecast, so later BEA revisions should not alter the resolved value."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-core-pce-mom-may-2026\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-06-25\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.jolts-openings-may-2026.2026-06-12T18-59-50Z.c528e1818af86dfd","runId":"run.jolts-openings-may-2026.2026-06-12T18-59-50Z.c528e1818af86dfd","predictionId":"jolts-openings-may-2026","specId":"spec.jolts-openings-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.22,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate over the last 12 months: mean level ~7.04M, with openings printing in the high-6M / low-7M range far more often than near 7.6M. Unconditionally the centre of gravity is ~7.0-7.2M, below April's 7.618M.","Partial mean-reversion from the April spike toward the 7.0-7.2M base, shaded up for macro strength -> point 7.35M. 80% CI = 7.35 +/- ~0.50M -> [6.85, 7.85]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Outside [6.85, 7.85] if: April's 7.618M is revised up and May extends the surge above ~7.85M; or a demand-side pullback (oil shock, hiring freeze) snaps openings back below ~6.85M as in late-2025 (Dec 6.55M). JOLTS' low response rate makes a >400k surprise routine."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: Macro cross-check: Q2 GDPNow 3.3% and positive payroll growth (~+170k first prints) argue the labor market is not collapsing, so a deep drop toward 6.5M is unlikely; but the oil-shock uncertainty and the April outlier argue against staying at 7.6M.","Tool result: Macro cross-check: Q2 GDPNow 3.3% and positive payroll growth (~+170k first prints) argue the labor market is not collapsing, so a deep drop toward 6.5M is unlikely; but the oil-shock uncertainty and the April outlier argue against staying at 7.6M. Net centre ~7.35M."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1, distribution present, forecast step count 1.","evidence":["Tool call: Macro cross-check: Q2 GDPNow 3.3% and positive payroll growth (~+170k first prints) argue the labor market is not collapsing, so a deep drop toward 6.5M is unlikely; but the oil-shock uncertainty and the April outlier argue against staying at 7.6M.","Tool result: Macro cross-check: Q2 GDPNow 3.3% and positive payroll growth (~+170k first prints) argue the labor market is not collapsing, so a deep drop toward 6.5M is unlikely; but the oil-shock uncertainty and the April outlier argue against staying at 7.6M. Net centre ~7.35M."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool call: Macro cross-check: Q2 GDPNow 3.3% and positive payroll growth (~+170k first prints) argue the labor market is not collapsing, so a deep drop toward 6.5M is unlikely; but the oil-shock uncertainty and the April outlier argue against staying at 7.6M.","Tool result: Macro cross-check: Q2 GDPNow 3.3% and positive payroll growth (~+170k first prints) argue the labor market is not collapsing, so a deep drop toward 6.5M is unlikely; but the oil-shock uncertainty and the April outlier argue against staying at 7.6M. Net centre ~7.35M."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Partial mean-reversion from the April spike toward the 7.0-7.2M base, shaded up for macro strength -> point 7.35M. 80% CI = 7.35 +/- ~0.50M -> [6.85, 7.85].","Forecast: point 7.35, 80% interval [6.85, 7.85]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: jolts-openings-may-2026\nrunLabel: Headline\nresolutionDate: 2026-06-30\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.jolts-openings-may-2026.2026-06-15T10-35-00-04-00.jolts-control-no-packs.4353b8d25a1883fd","runId":"run.jolts-openings-may-2026.2026-06-15T10-35-00-04-00.jolts-control-no-packs.4353b8d25a1883fd","predictionId":"jolts-openings-may-2026","specId":"spec.jolts-openings-may-2026","runLabel":"Scout-2 - no packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 5 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 0 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.25, distribution present, forecast step count 1.","evidence":["Forecast: point 7.15, 80% interval [6.55, 7.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 7.15, 80% interval [6.55, 7.8]"]}],"flags":["weak_counterarguments","no_typed_tool_call"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: jolts-openings-may-2026\nrunLabel: Scout-2 - no packs\nresolutionDate: 2026-06-30\ntraceLineCount: 3\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments, no_typed_tool_call."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.jolts-openings-may-2026.2026-06-15T10-40-00-04-00.jolts-labor-packs.f79134ec4ef156cf","runId":"run.jolts-openings-may-2026.2026-06-15T10-40-00-04-00.jolts-labor-packs.f79134ec4ef156cf","predictionId":"jolts-openings-may-2026","specId":"spec.jolts-openings-may-2026","runLabel":"Brier-1 - JOLTS packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.19,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 5 historical point(s) and implicit outside-view language.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"labor-market-momentum@0.1.0\", \"release-vintage-calibration@0.1.0\"], target: \"bls.jolts.job_openings.may_2026.first_print\" })","Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"openings_base_rate\", \"payroll_claims_cross_check\", \"jolts_release_noise\"] }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"labor-market-momentum@0.1.0\", \"release-vintage-calibration@0.1.0\"], target: \"bls.jolts.job_openings.may_2026.first_print\" })","Payroll and claims cross-checks make a full reversal of April's openings spike less attractive than the no-pack control, but the JOLTS pack keeps a wide interval for response-rate and revision noise."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"labor-market-momentum@0.1.0\", \"release-vintage-calibration@0.1.0\"], target: \"bls.jolts.job_openings.may_2026.first_print\" })","Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"openings_base_rate\", \"payroll_claims_cross_check\", \"jolts_release_noise\"] }"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.85, distribution present, forecast step count 1.","evidence":["Payroll and claims cross-checks make a full reversal of April's openings spike less attractive than the no-pack control, but the JOLTS pack keeps a wide interval for response-rate and revision noise.","Forecast: point 7.35, 80% interval [6.95, 7.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"labor-market-momentum@0.1.0\", \"release-vintage-calibration@0.1.0\"], target: \"bls.jolts.job_openings.may_2026.first_print\" })"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Payroll and claims cross-checks make a full reversal of April's openings spike less attractive than the no-pack control, but the JOLTS pack keeps a wide interval for response-rate and revision noise."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Payroll and claims cross-checks make a full reversal of April's openings spike less attractive than the no-pack control, but the JOLTS pack keeps a wide interval for response-rate and revision noise.","Forecast: point 7.35, 80% interval [6.95, 7.8]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: jolts-openings-may-2026\nrunLabel: Brier-1 - JOLTS packs\nresolutionDate: 2026-06-30\ntraceLineCount: 5\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.jolts-openings-may-2026.2026-06-17T02-17-25Z.jolts-openings-may-2026-thesis-analyst-fast-2026-06-17t02-17-25z.e9b7a1465dc3b96a","runId":"run.jolts-openings-may-2026.2026-06-17T02-17-25Z.jolts-openings-may-2026-thesis-analyst-fast-2026-06-17t02-17-25z.e9b7a1465dc3b96a","predictionId":"jolts-openings-may-2026","specId":"spec.jolts-openings-may-2026","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.49,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base-rate/reference class: month-to-month JOLTS job openings are noisy and often revise, so I anchor on the recent five-month range of 6,550 to 7,618 thousand and the latest three-month average near 7,142 thousand rather than extrapolating the full April jump."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Forecast for May 2026 BLS JOLTS job openings","The target is the first official BLS JOLTS print for seasonally adjusted total nonfarm job openings in May 2026, reported in thousands; later revisions do not count."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the first official BLS JOLTS print for seasonally adjusted total nonfarm job openings in May 2026, reported in thousands; later revisions do not count.","Tool call: Checked the BLS JOLTS release calendar for the May 2026 reference month."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.2, distribution present, forecast step count 1.","evidence":["Anchor around Apr 2026 7,618 and recent three-month average (7,618 + 6,887 + 6,922) / 3 = 7,142; weighting April persistence against mean reversion gives about 7,450 thousand. An 80 percent interval of 6,850 to 8,050 allows roughly +/-600 thousand, covering typical JOLTS volatility and the April spike risk.","Forecast: point 7.45, 80% interval [6.85, 8.05]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Anchor around Apr 2026 7,618 and recent three-month average (7,618 + 6,887 + 6,922) / 3 = 7,142; weighting April persistence against mean reversion gives about 7,450 thousand. An 80 percent interval of 6,850 to 8,050 allows roughly +/-600 thousand, covering typical JOLTS volatility and the April spike risk."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for May 2026 BLS JOLTS job openings","Anchor around Apr 2026 7,618 and recent three-month average (7,618 + 6,887 + 6,922) / 3 = 7,142; weighting April persistence against mean reversion gives about 7,450 thousand. An 80 percent interval of 6,850 to 8,050 allows roughly +/-600 thousand, covering typical JOLTS volatility and the April spike risk."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: jolts-openings-may-2026\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-06-30\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.euro-flash-hicp-june-2026.2026-06-12T18-51-12Z.25797c6fdd7dacee","runId":"run.euro-flash-hicp-june-2026.2026-06-12T18-51-12Z.25797c6fdd7dacee","predictionId":"euro-flash-hicp-june-2026","specId":"spec.euro-flash-hicp-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.22,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 7 historical point(s) and explicit outside-view language.","evidence":["Tool call: Fetched Eurostat release 2-20052026-ap (April 2026 final): euro area HICP 3.0% confirmed; prior months Mar 2.6, Feb 1.9, Jan 1.7, Dec 2.0, Nov 2.1.","Tool result: Fetched Eurostat release 2-20052026-ap (April 2026 final): euro area HICP 3.0% confirmed; prior months Mar 2.6, Feb 1.9, Jan 1.7, Dec 2.0, Nov 2.1. Establishes the full recent path."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["Realized month-over-month change in the HICP annual rate over the last 6 transitions = [-0.1, -0.3, +0.2, +0.7, +0.4, +0.2]; mean = +0.18pp, population stdev = 0.32pp; recent-3 mean = +0.43pp but the increments are shrinking (0.7 -> 0.4 -> 0.2), indicating deceleration in the pace. An 80% half-width ~ 1.28*0.32 ~ 0.41pp."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: Fetched Eurostat flash release 2-02062026-ap (May 2026): euro area HICP 3.2% (flash), up from 3.0% in April.","Tool result: Fetched Eurostat flash release 2-02062026-ap (May 2026): euro area HICP 3.2% (flash), up from 3.0% in April. Components: energy 10.9%, services 3.5%, food/alc/tob 2.0%, NEIG 0.9%; flash core ex energy/unprocessed food 2.3%, ex energy/food/alc/tob 2.5%."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.8, distribution present, forecast step count 1.","evidence":["Lands outside [2.8, 3.6] if: a further oil leg-up plus sticky services pushes the flash to ~3.7-3.8 (upside tail), or an energy reversal / soft services drags it to ~2.6-2.7 (downside tail). Flash estimates are themselves revised modestly, and divergent large-member-state prints (DE/FR/IT/ES) can swing the aggregate; the oil-shock regime makes the upside tail somewhat fatter than the downside.","Forecast: point 3.2, 80% interval [2.8, 3.6]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Realized month-over-month change in the HICP annual rate over the last 6 transitions = [-0.1, -0.3, +0.2, +0.7, +0.4, +0.2]; mean = +0.18pp, population stdev = 0.32pp; recent-3 mean = +0.43pp but the increments are shrinking (0.7 -> 0.4 -> 0.2), indicating deceleration in the pace. An 80% half-width ~ 1.28*0.32 ~ 0.41pp.","With the increments shrinking and energy still elevated but no longer accelerating sharply, June flash most likely holds near 3.2%, with a mild upward tilt if oil stays high. Point estimate 3.2%."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["With the increments shrinking and energy still elevated but no longer accelerating sharply, June flash most likely holds near 3.2%, with a mild upward tilt if oil stays high. Point estimate 3.2%.","Forecast: point 3.2, 80% interval [2.8, 3.6]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: euro-flash-hicp-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-01\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.euro-flash-hicp-june-2026.2026-06-17T02-10-25Z.euro-flash-hicp-june-2026-thesis-analyst-fast-2026-06-17t02-10-25z.3a1bc207b8eb3aa0","runId":"run.euro-flash-hicp-june-2026.2026-06-17T02-10-25Z.euro-flash-hicp-june-2026-thesis-analyst-fast-2026-06-17t02-10-25z.3a1bc207b8eb3aa0","predictionId":"euro-flash-hicp-june-2026","specId":"spec.euro-flash-hicp-june-2026","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.38,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 7 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the last four month-to-month changes in the first-print annual rate were +0.2, +0.7, +0.4, and +0.2 percentage points, but monthly headline inflation in May was only 0.1 percent, so a naive continuation of the rapid March-May rise should be tempered.","Counter-consideration: energy inflation was already very high at 10.9% and could mean-revert or face less favorable base effects in June, while food inflation eased to 2.0%; those factors keep the lower side materially plausible despite the high latest headline."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Counter-consideration: energy inflation was already very high at 10.9% and could mean-revert or face less favorable base effects in June, while food inflation eased to 2.0%; those factors keep the lower side materially plausible despite the high latest headline."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The resolver is the first Eurostat Euro indicators flash-estimate release for euro area all-items HICP annual inflation for June 2026, not the later complete HICP data release or any revision.","Tool call: Checked Eurostat release scheduling information on the May 2026 flash release and the Euro indicators calendar page."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.1, distribution present, forecast step count 1.","evidence":["Starting from May's 3.2%, I add 0.1 percentage point for continued energy and services pressure but shrink the recent +0.375 average change toward zero because the May monthly rate was only 0.1%; rounded to Eurostat's one-decimal convention this gives 3.3%. An 80% interval of roughly +/-0.55 percentage point around 3.3 rounds to 2.8% to 3.9%.","Forecast: point 3.3, 80% interval [2.8, 3.9]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Starting from May's 3.2%, I add 0.1 percentage point for continued energy and services pressure but shrink the recent +0.375 average change toward zero because the May monthly rate was only 0.1%; rounded to Eurostat's one-decimal convention this gives 3.3%. An 80% interval of roughly +/-0.55 percentage point around 3.3 rounds to 2.8% to 3.9%."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: the last four month-to-month changes in the first-print annual rate were +0.2, +0.7, +0.4, and +0.2 percentage points, but monthly headline inflation in May was only 0.1 percent, so a naive continuation of the rapid March-May rise should be tempered.","Starting from May's 3.2%, I add 0.1 percentage point for continued energy and services pressure but shrink the recent +0.375 average change toward zero because the May monthly rate was only 0.1%; rounded to Eurostat's one-decimal convention this gives 3.3%. An 80% interval of roughly +/-0.55 percentage point around 3.3 rounds to 2.8% to 3.9%."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Euro area HICP flash inflation forecast for June 2026","Base rate/reference class: the last four month-to-month changes in the first-print annual rate were +0.2, +0.7, +0.4, and +0.2 percentage points, but monthly headline inflation in May was only 0.1 percent, so a naive continuation of the rapid March-May rise should be tempered."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: euro-flash-hicp-june-2026\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-07-01\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.nonfarm-payrolls-june-2026.2026-06-12T18-59-50Z.e62ce2faf99fc097","runId":"run.nonfarm-payrolls-june-2026.2026-06-12T18-59-50Z.e62ce2faf99fc097","predictionId":"nonfarm-payrolls-june-2026","specId":"spec.nonfarm-payrolls-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate: over the last 12 months the median over-the-month change is +52.5k and the mean +42k, i.e. a soft-but-positive labor market. The spring 2026 prints (170-214k) sit well above that 12-month base, suggesting some reversion toward the +100-150k zone is more likely than a repeat of +200k.","Blend trend (+150k), 12-month base (~+50k) and the forecaster anchor (+130k), tilting to the firmer recent first prints -> point +140k. 80% band = point +/- ~1.28*82k ~= +/-105k -> [35, 245]."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: Fetched the Thesis fact ledger (ledger.json): the resolved May-2026 first print was +172k (BLS Employment Situation, released 2026-06-05).","Tool result: Fetched the Thesis fact ledger (ledger.json): the resolved May-2026 first print was +172k (BLS Employment Situation, released 2026-06-05). So the level-series May change (172) equals the first print — recent revisions are small at short horizon."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Tool call: Fetched the Thesis fact ledger (ledger.json): the resolved May-2026 first print was +172k (BLS Employment Situation, released 2026-06-05).","Tool result: Fetched the Thesis fact ledger (ledger.json): the resolved May-2026 first print was +172k (BLS Employment Situation, released 2026-06-05). So the level-series May change (172) equals the first print — recent revisions are small at short horizon."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 210, distribution present, forecast step count 1.","evidence":["Outside the interval if: (a) the Middle East oil shock triggers an abrupt energy/transport layoff wave or confidence shock pushing the print below ~+35k or negative; or (b) another large upside surprise (like May's beat) driven by health care/government hiring pushes it above ~+245k. Single-month CES sampling/birth-death noise can also produce a >100k surprise in either direction.","Forecast: point 140, 80% interval [35, 245]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["3-month mean change = +188k; 6-month mean = +92k; 12-month mean = +42k. Momentum is positive but the trailing-3 is inflated by Mar's +214k; the run-rate is decelerating month-over-month (214 -> 179 -> 172). Trend-blend lands near +150k before adjustment."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["3-month mean change = +188k; 6-month mean = +92k; 12-month mean = +42k. Momentum is positive but the trailing-3 is inflated by Mar's +214k; the run-rate is decelerating month-over-month (214 -> 179 -> 172). Trend-blend lands near +150k before adjustment.","Base rate: over the last 12 months the median over-the-month change is +52.5k and the mean +42k, i.e. a soft-but-positive labor market. The spring 2026 prints (170-214k) sit well above that 12-month base, suggesting some reversion toward the +100-150k zone is more likely than a repeat of +200k."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool call: Cross-checked a professional forecast: Capital Economics projects ~+130k for June with unemployment steady.","Tool result: Cross-checked a professional forecast: Capital Economics projects ~+130k for June with unemployment steady. Consensus for May had been only +80k and actual was +172k, so consensus has been low-biased recently; I weight the firm forecast and recent beats toward a centre slightly above 130k."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: nonfarm-payrolls-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-02\ntraceLineCount: 12\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.nonfarm-payrolls-june-2026.2026-06-14T15-20-00-04-00.payrolls-control-no-packs.0a660f20bfc9031b","runId":"run.nonfarm-payrolls-june-2026.2026-06-14T15-20-00-04-00.payrolls-control-no-packs.0a660f20bfc9031b","predictionId":"nonfarm-payrolls-june-2026","specId":"spec.nonfarm-payrolls-june-2026","runLabel":"Scout-2 - no packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.89,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 5 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 0 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The control run starts from the recent +170k spring first prints, then pulls toward the softer twelve-month payroll mean rather than adding release-specific context."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 275, distribution present, forecast step count 1.","evidence":["Forecast: point 125, 80% interval [-10, 265]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Blend = 0.55 * spring momentum + 0.45 * trailing-year mean = about +125k."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 125, 80% interval [-10, 265]"]}],"flags":["weak_counterarguments","no_typed_tool_call"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: nonfarm-payrolls-june-2026\nrunLabel: Scout-2 - no packs\nresolutionDate: 2026-07-02\ntraceLineCount: 4\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: resolution clarity (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments, no_typed_tool_call."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.nonfarm-payrolls-june-2026.2026-06-15T09-10-00-04-00.payrolls-labor-packs.125a58572070330b","runId":"run.nonfarm-payrolls-june-2026.2026-06-15T09-10-00-04-00.payrolls-labor-packs.125a58572070330b","predictionId":"nonfarm-payrolls-june-2026","specId":"spec.nonfarm-payrolls-june-2026","runLabel":"Brier-1 - labor packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.59,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"labor-market-momentum@0.1.0\", \"release-vintage-calibration@0.1.0\"], target: \"bls.ces.total_nonfarm_payroll_change.june_2026.first_print\" })","Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"base_rate\", \"labor_momentum\", \"first_print_error\"] }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"labor-market-momentum@0.1.0\", \"release-vintage-calibration@0.1.0\"], target: \"bls.ces.total_nonfarm_payroll_change.june_2026.first_print\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"labor-market-momentum@0.1.0\", \"release-vintage-calibration@0.1.0\"], target: \"bls.ces.total_nonfarm_payroll_change.june_2026.first_print\" })","Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"base_rate\", \"labor_momentum\", \"first_print_error\"] }"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 225, distribution present, forecast step count 1.","evidence":["Packed center = 125k control + 25k claims/openings adjustment = 150k; first-print calibration trims the lower tail.","Forecast: point 150, 80% interval [35, 260]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"labor-market-momentum@0.1.0\", \"release-vintage-calibration@0.1.0\"], target: \"bls.ces.total_nonfarm_payroll_change.june_2026.first_print\" })","Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"base_rate\", \"labor_momentum\", \"first_print_error\"] }"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The pack run keeps the spring payroll base rate but lifts the control slightly because claims and openings do not show a break in labor demand."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 150, 80% interval [35, 260]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: nonfarm-payrolls-june-2026\nrunLabel: Brier-1 - labor packs\nresolutionDate: 2026-07-02\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (3/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.nonfarm-payrolls-june-2026.2026-06-17T02-18-28Z.nonfarm-payrolls-june-2026-thesis-analyst-fast-2026-06-17t02-18-28z.407a1c3e2a4cfe0c","runId":"run.nonfarm-payrolls-june-2026.2026-06-17T02-18-28Z.nonfarm-payrolls-june-2026-thesis-analyst-fast-2026-06-17t02-18-28z.407a1c3e2a4cfe0c","predictionId":"nonfarm-payrolls-june-2026","specId":"spec.nonfarm-payrolls-june-2026","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base-rate/reference class: the latest three first prints available in this run are March +185k, April +115k, and May +172k, averaging about +157k. The revised three-month pace is stronger at about +188k, but the target resolves to first print, so I weight first-print behavior more heavily.","Recent first-print average = (185 + 115 + 172) / 3 = 157.3 thousand. I round down slightly to 150 thousand to allow for mean reversion from May strength while keeping the center near the recent first-print base rate. An 80% interval of -20 to 310 thousand allows roughly 170 thousand downside and 160 thousand upside around the point, covering ordinary payroll first-print volatility and recession-tail risk."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The resolver is the first BLS Employment Situation print for June 2026 total nonfarm payroll employment, seasonally adjusted, measured as the month-over-month change in thousands.","Tool call: Checked the BLS Employment Situation release calendar for the June 2026 reference month."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["June 2026 US nonfarm payrolls first-print forecast","The resolver is the first BLS Employment Situation print for June 2026 total nonfarm payroll employment, seasonally adjusted, measured as the month-over-month change in thousands."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 330, distribution present, forecast step count 1.","evidence":["Recent first-print average = (185 + 115 + 172) / 3 = 157.3 thousand. I round down slightly to 150 thousand to allow for mean reversion from May strength while keeping the center near the recent first-print base rate. An 80% interval of -20 to 310 thousand allows roughly 170 thousand downside and 160 thousand upside around the point, covering ordinary payroll first-print volatility and recession-tail risk.","Forecast: point 150, 80% interval [-20, 310]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Upside case: upward revisions and a steady 4.3 percent unemployment rate suggest the labor market had more momentum than April's initial print implied, and May sector gains in leisure and hospitality, local government, and health care could persist into June."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base-rate/reference class: the latest three first prints available in this run are March +185k, April +115k, and May +172k, averaging about +157k. The revised three-month pace is stronger at about +188k, but the target resolves to first print, so I weight first-print behavior more heavily.","Recent first-print average = (185 + 115 + 172) / 3 = 157.3 thousand. I round down slightly to 150 thousand to allow for mean reversion from May strength while keeping the center near the recent first-print base rate. An 80% interval of -20 to 310 thousand allows roughly 170 thousand downside and 160 thousand upside around the point, covering ordinary payroll first-print volatility and recession-tail risk."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["June 2026 US nonfarm payrolls first-print forecast","Recent first-print average = (185 + 115 + 172) / 3 = 157.3 thousand. I round down slightly to 150 thousand to allow for mean reversion from May strength while keeping the center near the recent first-print base rate. An 80% interval of -20 to 310 thousand allows roughly 170 thousand downside and 160 thousand upside around the point, covering ordinary payroll first-print volatility and recession-tail risk."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: nonfarm-payrolls-june-2026\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-07-02\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.nonfarm-payrolls-june-2026.2026-06-21T15-06-37Z.nonfarm-payrolls-june-2026-thesis-analyst-fast-2026-06-21t15-06-37z.e62ce2faf99fc097","runId":"run.nonfarm-payrolls-june-2026.2026-06-21T15-06-37Z.nonfarm-payrolls-june-2026-thesis-analyst-fast-2026-06-21t15-06-37z.e62ce2faf99fc097","predictionId":"nonfarm-payrolls-june-2026","specId":"spec.nonfarm-payrolls-june-2026","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool result: DOL reported initial claims of 226,000 for the week ending Jun. 13, 2026, down 4,000 from the revised 230,000 prior week; the 4-week moving average was 223,250, up 4,000; insured unemployment was 1,810,000 for the week ending Jun. 6.","Base rate: the last three available payroll changes average about 188 thousand using 214, 179, and 172. That is a strong starting point, but it likely overstates June because the latest claims average has moved up and May had unusually large leisure, hospitality, and local-government gains."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The resolver is the first BLS Employment Situation print for June 2026 total nonfarm payroll employment, seasonally adjusted, measured as the monthly change in thousands. Later revisions do not count.","Tool call: Checked the BLS Employment Situation release schedule for the June 2026 reference month."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["June 2026 US nonfarm payrolls first print","The resolver is the first BLS Employment Situation print for June 2026 total nonfarm payroll employment, seasonally adjusted, measured as the monthly change in thousands. Later revisions do not count."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 210, distribution present, forecast step count 1.","evidence":["Counter-consideration: claims are still low by historical standards and BLS revised March and April up sharply, so a sudden weak or negative print is not the central case. The main risk is normal first-print noise, not a clear labor-market break.","I start from the recent 188 thousand three-month average, shade down roughly 45 thousand for mild claims deterioration and possible payback from May strength, then round to 140 thousand. An 80% first-print interval of 35 to 245 thousand allows about +/-105 thousand around the point, consistent with volatile monthly CES surprises."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Read the latest BLS Employment Situation Summary for recent payroll momentum and revisions.","Tool call: Checked the latest official DOL unemployment insurance weekly claims release for layoff pressure near the survey month."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate: the last three available payroll changes average about 188 thousand using 214, 179, and 172. That is a strong starting point, but it likely overstates June because the latest claims average has moved up and May had unusually large leisure, hospitality, and local-government gains.","Counter-consideration: claims are still low by historical standards and BLS revised March and April up sharply, so a sudden weak or negative print is not the central case. The main risk is normal first-print noise, not a clear labor-market break."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Base rate: the last three available payroll changes average about 188 thousand using 214, 179, and 172. That is a strong starting point, but it likely overstates June because the latest claims average has moved up and May had unusually large leisure, hospitality, and local-government gains.","I start from the recent 188 thousand three-month average, shade down roughly 45 thousand for mild claims deterioration and possible payback from May strength, then round to 140 thousand. An 80% first-print interval of 35 to 245 thousand allows about +/-105 thousand around the point, consistent with volatile monthly CES surprises."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: nonfarm-payrolls-june-2026\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-07-02\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.unemployment-rate-june-2026.2026-06-12T18-59-50Z.bc2560c9f3dbbe73","runId":"run.unemployment-rate-june-2026.2026-06-12T18-59-50Z.bc2560c9f3dbbe73","predictionId":"unemployment-rate-june-2026","specId":"spec.unemployment-rate-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.54,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Base rate over the last 12 months: the modal print is 4.3% (and 4.3-4.4 covers almost every month). Unconditionally, P(June = 4.3) is the highest single-bin probability; 4.2 and 4.4 are the next most likely."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["Tool call: Thesis ledger confirms the May 2026 first print was 4.3% ('unchanged at 4.3 percent'), matching the FRED value — so no first-print/revision ","Tool result: Thesis ledger confirms the May 2026 first print was 4.3% ('unchanged at 4.3 percent'), matching the FRED value — so no first-print/revision gap to adjust for."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Tool call: Thesis ledger confirms the May 2026 first print was 4.3% ('unchanged at 4.3 percent'), matching the FRED value — so no first-print/revision ","Tool result: Thesis ledger confirms the May 2026 first print was 4.3% ('unchanged at 4.3 percent'), matching the FRED value — so no first-print/revision gap to adjust for."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.4, distribution present, forecast step count 1.","evidence":["Computed month-over-month change in the rounded rate over the last 24 months: population stdev = 0.107 percentage points; nearly all monthly moves are within +/-0.2pp. An 80% interval is therefore roughly point +/- 0.13pp, which after rounding to the published 0.1 grid maps to ~[4.1, 4.5].","Outside [4.1, 4.5] if: a sudden oil-shock-driven layoff surge or a participation jump pushes U-3 to 4.6%+, or a tightening/participation drop prints 4.0%. Both are tail events for a one-month rounded rate given the recent 0.1pp typical move."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Computed month-over-month change in the rounded rate over the last 24 months: population stdev = 0.107 percentage points; nearly all monthly moves are within +/-0.2pp. An 80% interval is therefore roughly point +/- 0.13pp, which after rounding to the published 0.1 grid maps to ~[4.1, 4.5].","Persistence + tiny volatility -> point 4.3%. 80% CI spans one rounding step either side plus a margin: [4.1, 4.5]."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: unemployment-rate-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-02\ntraceLineCount: 12\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.unemployment-rate-june-2026.2026-06-14T15-25-00-04-00.unemployment-control-no-packs.c638ecef0e19c24b","runId":"run.unemployment-rate-june-2026.2026-06-14T15-25-00-04-00.unemployment-control-no-packs.c638ecef0e19c24b","predictionId":"unemployment-rate-june-2026","specId":"spec.unemployment-rate-june-2026","runLabel":"Scout-2 - no packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.59,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 6 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 0 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.6, distribution present, forecast step count 1.","evidence":["The rate has clustered at 4.3 percent, so the control repeats the modal value but keeps a wider interval for household-survey noise.","Forecast: point 4.3, 80% interval [4, 4.6]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The rate has clustered at 4.3 percent, so the control repeats the modal value but keeps a wider interval for household-survey noise."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The rate has clustered at 4.3 percent, so the control repeats the modal value but keeps a wider interval for household-survey noise.","Forecast: point 4.3, 80% interval [4, 4.6]"]}],"flags":["no_typed_tool_call"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: unemployment-rate-june-2026\nrunLabel: Scout-2 - no packs\nresolutionDate: 2026-07-02\ntraceLineCount: 3\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). Flags: no_typed_tool_call."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.unemployment-rate-june-2026.2026-06-15T09-15-00-04-00.unemployment-labor-packs.bc2560c9f3dbbe73","runId":"run.unemployment-rate-june-2026.2026-06-15T09-15-00-04-00.unemployment-labor-packs.bc2560c9f3dbbe73","predictionId":"unemployment-rate-june-2026","specId":"spec.unemployment-rate-june-2026","runLabel":"Brier-1 - labor packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.3,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 6 historical point(s) and implicit outside-view language.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"labor-market-momentum@0.1.0\", \"release-vintage-calibration@0.1.0\"], target: \"bls.cps.unemployment_rate.june_2026.first_print\" })","Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"base_rate\", \"payroll_claims_consistency\", \"rounded_release_grid\"] }"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"labor-market-momentum@0.1.0\", \"release-vintage-calibration@0.1.0\"], target: \"bls.cps.unemployment_rate.june_2026.first_print\" })","Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"base_rate\", \"payroll_claims_consistency\", \"rounded_release_grid\"] }"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"labor-market-momentum@0.1.0\", \"release-vintage-calibration@0.1.0\"], target: \"bls.cps.unemployment_rate.june_2026.first_print\" })","Tool result: { admitted: 3, mode: \"with_packs\", required_checks: [\"base_rate\", \"payroll_claims_consistency\", \"rounded_release_grid\"] }"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.4, distribution present, forecast step count 1.","evidence":["Payrolls and claims do not justify moving away from 4.3 percent, but the pack tightens the tails around one rounded tick on either side.","Forecast: point 4.3, 80% interval [4.1, 4.5]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"labor-market-momentum@0.1.0\", \"release-vintage-calibration@0.1.0\"], target: \"bls.cps.unemployment_rate.june_2026.first_print\" })"]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["Payrolls and claims do not justify moving away from 4.3 percent, but the pack tightens the tails around one rounded tick on either side."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 4.3, 80% interval [4.1, 4.5]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: unemployment-rate-june-2026\nrunLabel: Brier-1 - labor packs\nresolutionDate: 2026-07-02\ntraceLineCount: 5\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.unemployment-rate-june-2026.2026-06-17T02-19-19Z.unemployment-rate-june-2026-thesis-analyst-fast-2026-06-17t02-19-19z.57400c4ac1094b0b","runId":"run.unemployment-rate-june-2026.2026-06-17T02-19-19Z.unemployment-rate-june-2026-thesis-analyst-fast-2026-06-17t02-19-19z.57400c4ac1094b0b","predictionId":"unemployment-rate-june-2026","specId":"spec.unemployment-rate-june-2026","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.19,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 6 historical point(s) and implicit outside-view language.","evidence":["Base-rate/reference-class step: one-month changes in the rounded unemployment rate are usually small, and the last five official monthly prints have stayed in a 4.3 to 4.4 range, with four of five at 4.3."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Forecast for June 2026 BLS CPS unemployment rate","The target is the first-print, seasonally adjusted CPS unemployment rate for June 2026, not a later revised value. The official BLS Employment Situation release is the resolver."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The target is the first-print, seasonally adjusted CPS unemployment rate for June 2026, not a later revised value. The official BLS Employment Situation release is the resolver.","Tool call: Checked BLS Employment Situation release calendar for the June 2026 reference month."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.5, distribution present, forecast step count 1.","evidence":["Counter-consideration: household-survey noise can move the rounded unemployment rate by 0.1 or 0.2 points even when payroll growth is solid, and long-term unemployment near 2.0 million leaves some upside risk.","Average of Jan-May rounded rates is (4.3 + 4.4 + 4.3 + 4.3 + 4.3) / 5 = 4.32, rounded to a 4.3 percent point forecast. I set the 80 percent interval at 4.1 to 4.6 to allow roughly minus 0.2 to plus 0.3 points around the recent 4.3 percent center, with slightly more upside due to household-survey volatility."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-consideration: household-survey noise can move the rounded unemployment rate by 0.1 or 0.2 points even when payroll growth is solid, and long-term unemployment near 2.0 million leaves some upside risk."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for June 2026 BLS CPS unemployment rate","Counter-consideration: household-survey noise can move the rounded unemployment rate by 0.1 or 0.2 points even when payroll growth is solid, and long-term unemployment near 2.0 million leaves some upside risk."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: unemployment-rate-june-2026\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-07-02\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.unemployment-rate-june-2026.2026-06-21T15-07-35Z.unemployment-rate-june-2026-thesis-analyst-fast-2026-06-21t15-07-35z.57400c4ac1094b0b","runId":"run.unemployment-rate-june-2026.2026-06-21T15-07-35Z.unemployment-rate-june-2026-thesis-analyst-fast-2026-06-21t15-07-35z.57400c4ac1094b0b","predictionId":"unemployment-rate-june-2026","specId":"spec.unemployment-rate-june-2026","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Base-rate/reference class: one-month moves in the rounded unemployment rate are usually small, and the immediate recent reference class is especially persistent: five latest monthly values are all between 4.3 and 4.4, with four of five at 4.3.","Use persistence as the anchor: median of Jan-May rounded rates = 4.3. Apply no drift because May payrolls were strong and participation was flat, but widen the 80 percent interval to roughly one BLS household-survey rounded-rate move below and above: 4.1 to 4.6."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Forecast for June 2026 BLS CPS unemployment rate","The resolver is the first official BLS Employment Situation print for June 2026, using the seasonally adjusted civilian unemployment rate for people age 16 and over, rounded to one decimal percent."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The resolver is the first official BLS Employment Situation print for June 2026, using the seasonally adjusted civilian unemployment rate for people age 16 and over, rounded to one decimal percent.","Tool call: Checked the BLS Employment Situation release calendar for the June 2026 reference month."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.5, distribution present, forecast step count 1.","evidence":["The main upside risk is that the household survey can be noisy and BLS says the unemployment-rate monthly-change confidence interval is about plus or minus 0.3 percentage point near a 6.0 percent rate; a softer June household survey could round to 4.4 or 4.5 even if payrolls remain positive.","The main downside risk is continued strong labor demand: May payrolls rose 172,000, participation was steady at 61.8 percent, and the unemployment rate has held at 4.3 despite month-to-month changes in unemployment levels."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Use persistence as the anchor: median of Jan-May rounded rates = 4.3. Apply no drift because May payrolls were strong and participation was flat, but widen the 80 percent interval to roughly one BLS household-survey rounded-rate move below and above: 4.1 to 4.6."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The main upside risk is that the household survey can be noisy and BLS says the unemployment-rate monthly-change confidence interval is about plus or minus 0.3 percentage point near a 6.0 percent rate; a softer June household survey could round to 4.4 or 4.5 even if payrolls remain positive.","The main downside risk is continued strong labor demand: May payrolls rose 172,000, participation was steady at 61.8 percent, and the unemployment rate has held at 4.3 despite month-to-month changes in unemployment levels."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for June 2026 BLS CPS unemployment rate","The main upside risk is that the household survey can be noisy and BLS says the unemployment-rate monthly-change confidence interval is about plus or minus 0.3 percentage point near a 6.0 percent rate; a softer June household survey could round to 4.4 or 4.5 even if payrolls remain positive."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: unemployment-rate-june-2026\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-07-02\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-mts-deficit-june-2026.2026-06-12T18-59-50Z.87458f2d48e9351f","runId":"run.us-mts-deficit-june-2026.2026-06-12T18-59-50Z.87458f2d48e9351f","predictionId":"us-mts-deficit-june-2026","specId":"spec.us-mts-deficit-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Tool result: Fetched FRED MTSDS133FMS CSV. Extracted historical JUNE values ($B): Jun2025 +27.0 surplus, Jun2024 -66.0, Jun2023 -227.8, Jun2022 -88.8, Jun2021 -174.2, Jun2020 -864.1 (COVID), Jun2019 -8.5, Jun2018 -74.9 (FRED sign: negative=deficit).","June is a structurally low-deficit month because quarterly estimated taxes arrive ~June 15. Excluding the 2020-2021 pandemic, the last six Junes (2018,2019,2022,2023,2024,2025) ranged from a $228B deficit to a $27B surplus, mean ~ -$73B deficit, median ~ -$71B deficit (sign converted: deficit positive ~ +71 to +73)."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Tool call: Validated the release-date rule against the just-released May MTS: May-2026 deficit -$292.6B (FRED) / ~$293B (CRFB) was published 2026-06-10, which is exactly the 8th workday of June 2026.","Tool result: Validated the release-date rule against the just-released May MTS: May-2026 deficit -$292.6B (FRED) / ~$293B (CRFB) was published 2026-06-10, which is exactly the 8th workday of June 2026. Applying the same rule to July (with July 3 the observed Independence Day holiday) gives the June MTS release on 2026-07-13."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 260, distribution present, forecast step count 1.","evidence":["Anchor on the ex-pandemic June mean (~+$73B deficit) but shade toward near-balance given FY2026's stronger receipts and the 2025 surplus precedent -> point +$25B deficit. 80% CI = +25 +/- ~$120-130B, slightly asymmetric (surpluses bounded near -$90B, deficit tail to +$170B) -> [-90, 170].","Forecast: point 25, 80% interval [-90, 170]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["June is a structurally low-deficit month because quarterly estimated taxes arrive ~June 15. Excluding the 2020-2021 pandemic, the last six Junes (2018,2019,2022,2023,2024,2025) ranged from a $228B deficit to a $27B surplus, mean ~ -$73B deficit, median ~ -$71B deficit (sign converted: deficit positive ~ +71 to +73)."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate for the deficit-positive figure: recent Junes cluster ~ -$30B (surplus) to +$230B (deficit), with most mass in the +$0B to +$90B deficit range once pandemic years are dropped. The unconditional centre is a small-to-moderate deficit; a surplus (like 2025) is plausible but not modal across the full sample.","Anchor on the ex-pandemic June mean (~+$73B deficit) but shade toward near-balance given FY2026's stronger receipts and the 2025 surplus precedent -> point +$25B deficit. 80% CI = +25 +/- ~$120-130B, slightly asymmetric (surpluses bounded near -$90B, deficit tail to +$170B) -> [-90, 170]."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Anchor on the ex-pandemic June mean (~+$73B deficit) but shade toward near-balance given FY2026's stronger receipts and the 2025 surplus precedent -> point +$25B deficit. 80% CI = +25 +/- ~$120-130B, slightly asymmetric (surpluses bounded near -$90B, deficit tail to +$170B) -> [-90, 170].","Forecast: point 25, 80% interval [-90, 170]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-mts-deficit-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-13\ntraceLineCount: 11\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-mts-deficit-june-2026.2026-06-17T02-35-38Z.us-mts-deficit-june-2026-thesis-analyst-fast-2026-06-17t02-35-38z.6176ae204ec6360e","runId":"run.us-mts-deficit-june-2026.2026-06-17T02-35-38Z.us-mts-deficit-june-2026-thesis-analyst-fast-2026-06-17t02-35-38z.6176ae204ec6360e","predictionId":"us-mts-deficit-june-2026","specId":"spec.us-mts-deficit-june-2026","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.54,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Tool result: Fetched official Monthly Treasury Statement dataset URL for the Table 1 resolver; historical Table 1 June monthly deficits used as reference points were 2025-06: 27 USD billion, 2024-06: 66 USD billion, and 2023-06: 228 USD billion.","Tool result: Fetched May 2026 Treasury-reported context: customs duties collected were 22 USD billion, refunds were 22 USD billion, fiscal-year net tariff revenue through May was 189 USD billion versus 81 USD billion a year earlier, and the calendar-adjusted deficit was 2 percent or 24 USD billion below the prior year."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Resolver is the first official Bureau of the Fiscal Service Monthly Treasury Statement print for June 2026, using the monthly deficit/surplus in Table 1 and treating deficits as positive USD billions.","Tool call: Checked the Treasury Fiscal Data release calendar page for the release-calendar source used to verify the official schedule surface."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Resolver is the first official Bureau of the Fiscal Service Monthly Treasury Statement print for June 2026, using the monthly deficit/surplus in Table 1 and treating deficits as positive USD billions.","Tool call: Checked the Treasury Fiscal Data release calendar page for the release-calendar source used to verify the official schedule surface."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 245, distribution present, forecast step count 1.","evidence":["I start with a recent-June base of about (27 + 66) / 2 = 46.5 billion, add roughly 20 billion for higher interest and entitlement outlays, add 10 billion for tariff-refund and policy noise, and round to a 72 billion point. The 80% interval is set wide at -35 to 210 billion to cover a possible June surplus from strong receipts and a 2023-like high-deficit outlier if payment timing or refunds raise outlays.","Forecast: point 72, 80% interval [-35, 210]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base-rate step: the most relevant reference class is recent June MTS prints because June contains quarterly estimated tax payments and has strong seasonality. The recent June deficits of 27, 66, and 228 billion imply a wide but positive-deficit center; the two most recent years point closer to 50 billion than to the 2023 outlier."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Base-rate step: the most relevant reference class is recent June MTS prints because June contains quarterly estimated tax payments and has strong seasonality. The recent June deficits of 27, 66, and 228 billion imply a wide but positive-deficit center; the two most recent years point closer to 50 billion than to the 2023 outlier."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for the June 2026 Monthly Treasury Statement deficit","Tool result: Fetched official Monthly Treasury Statement dataset URL for the Table 1 resolver; historical Table 1 June monthly deficits used as reference points were 2025-06: 27 USD billion, 2024-06: 66 USD billion, and 2023-06: 228 USD billion."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-mts-deficit-june-2026\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-07-13\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-mts-deficit-june-2026.2026-06-21T15-08-15Z.us-mts-deficit-june-2026-thesis-analyst-fast-2026-06-21t15-08-15z.8b388a493db27d0a","runId":"run.us-mts-deficit-june-2026.2026-06-21T15-08-15Z.us-mts-deficit-june-2026-thesis-analyst-fast-2026-06-21t15-08-15z.8b388a493db27d0a","predictionId":"us-mts-deficit-june-2026","specId":"spec.us-mts-deficit-june-2026","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.51,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Tool result: Reports cited Treasury figures that May 2026 net tariff revenue was 0 billion after 22 billion collected and 22 billion refunded, FYTD net tariff revenue was 189 billion versus 81 billion a year earlier, adjusted FYTD deficit was 2 percent or 24 billion below the prior year, and Treasury's April-June 2026 borrowing estimate was 189 billion.","Base-rate: recent June deficits are volatile because corporate tax collections and payment-date shifts matter. The 2022-2025 June outcomes were 88.842, 227.768, 65.965, and -27.010 billion, giving a simple four-year average near 88.9 billion and a three-year average near 88.2 billion, but the 2024 and 2025 June figures were held down by June 1 weekend payment acceleration into May."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["Resolver: use the first official U.S. Treasury Monthly Treasury Statement for June 2026, Table 1 total deficit/surplus, converted from $ millions to $ billions, with deficits positive and surpluses negative.","Tool result: The official MTS page says the statement covers receipts, outlays, surplus or deficit, and means of financing; it also says data moved to FiscalData on 2025-11-25 and the MTS page was last updated 2026-01-15."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":["Resolver: use the first official U.S. Treasury Monthly Treasury Statement for June 2026, Table 1 total deficit/surplus, converted from $ millions to $ billions, with deficits positive and surpluses negative."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 290, distribution present, forecast step count 1.","evidence":["Start from a recent-June base rate around 90 billion. Add roughly 55 billion for normal June benefit and Medicare/HHS payments not shifted into May, add about 25 billion for higher interest and entitlement growth, and subtract about 15 billion for still-elevated customs/tariff receipts net of refunds: 90 + 55 + 25 - 15 = 155 billion. Set an 80% interval of 20 to 310 billion to cover tax-payment and refund volatility.","Forecast: point 155, 80% interval [20, 310]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base-rate: recent June deficits are volatile because corporate tax collections and payment-date shifts matter. The 2022-2025 June outcomes were 88.842, 227.768, 65.965, and -27.010 billion, giving a simple four-year average near 88.9 billion and a three-year average near 88.2 billion, but the 2024 and 2025 June figures were held down by June 1 weekend payment acceleration into May."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base-rate: recent June deficits are volatile because corporate tax collections and payment-date shifts matter. The 2022-2025 June outcomes were 88.842, 227.768, 65.965, and -27.010 billion, giving a simple four-year average near 88.9 billion and a three-year average near 88.2 billion, but the 2024 and 2025 June figures were held down by June 1 weekend payment acceleration into May.","Counter-consideration: if June receipts remain strong and tariff revenues are not fully offset by refunds, the deficit could land near the low end or even close to balance; however, June 1, 2026 is a Monday, so the payment-shift suppression visible in 2024 and 2025 should not repeat."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for June 2026 Monthly Treasury Statement deficit","Start from a recent-June base rate around 90 billion. Add roughly 55 billion for normal June benefit and Medicare/HHS payments not shifted into May, add about 25 billion for higher interest and entitlement growth, and subtract about 15 billion for still-elevated customs/tariff receipts net of refunds: 90 + 55 + 25 - 15 = 155 billion. Set an 80% interval of 20 to 310 billion to cover tax-payment and refund volatility."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-mts-deficit-june-2026\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-07-13\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: resolution clarity (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-cpi-u-mom-june-2026.2026-06-12T18-59-50Z.89d3681a7f28e8df","runId":"run.us-cpi-u-mom-june-2026.2026-06-12T18-59-50Z.89d3681a7f28e8df","predictionId":"us-cpi-u-mom-june-2026","specId":"spec.us-cpi-u-mom-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.24,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate (pre-shock 12-month run-rate, mid-2025): headline MoM clustered around +0.2-0.3%. The oil shock has lifted the conditional mean above that; June should sit between the shock-elevated recent prints and the calmer base, i.e. ~+0.3-0.5%.","Tool call: Pipeline check: May PPI final demand +1.1% MoM (energy +10.7%, gasoline +23.4%) signals ongoing energy pass-through, arguing against a fast collapse to the +0.2% base."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: Verified the May first print independently: BLS reported all-items CPI-U +0.5% MoM SA for May 2026 (also confirmed via the CNBC May-2026 CPI summary; +4.2% YoY).","Tool result: Verified the May first print independently: BLS reported all-items CPI-U +0.5% MoM SA for May 2026 (also confirmed via the CNBC May-2026 CPI summary; +4.2% YoY). FRED's +0.473% and BLS's +0.5% agree, validating the series for forecasting June."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: Verified the May first print independently: BLS reported all-items CPI-U +0.5% MoM SA for May 2026 (also confirmed via the CNBC May-2026 CPI summary; +4.2% YoY).","Tool result: Verified the May first print independently: BLS reported all-items CPI-U +0.5% MoM SA for May 2026 (also confirmed via the CNBC May-2026 CPI summary; +4.2% YoY). FRED's +0.473% and BLS's +0.5% agree, validating the series for forecasting June."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.6, distribution present, forecast step count 1.","evidence":["Forecast: point 0.4, 80% interval [0.1, 0.7]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Decelerating energy contribution + firm core floor + PPI pipeline pressure -> point +0.4%. 80% CI = +0.4 +/- ~0.27 -> [0.1, 0.7]."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Trailing-3 mean = +0.66%, but the sequence is monotonically decelerating (0.87 -> 0.64 -> 0.47). Linear extrapolation of the deceleration points to roughly +0.35-0.40% for June as the initial energy spike's monthly contribution fades while levels stay high.","Decelerating energy contribution + firm core floor + PPI pipeline pressure -> point +0.4%. 80% CI = +0.4 +/- ~0.27 -> [0.1, 0.7]."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Verified the May first print independently: BLS reported all-items CPI-U +0.5% MoM SA for May 2026 (also confirmed via the CNBC May-2026 CPI summary; +4.2% YoY). FRED's +0.473% and BLS's +0.5% agree, validating the series for forecasting June.","Population stdev of headline MoM over the last 24 months = 0.189pp. This is elevated by the recent oil-shock spike; a typical pre-shock month was ~0.1pp stdev. Using ~0.20-0.24pp as the 1-sigma scale, the 80% band (z=1.28) is roughly point +/- ~0.27pp."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-cpi-u-mom-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-14\ntraceLineCount: 12\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-cpi-u-mom-june-2026.2026-06-14T15-35-00-04-00.headline-cpi-control-no-packs.f3c31a3eb5b6c545","runId":"run.us-cpi-u-mom-june-2026.2026-06-14T15-35-00-04-00.headline-cpi-control-no-packs.f3c31a3eb5b6c545","predictionId":"us-cpi-u-mom-june-2026","specId":"spec.us-cpi-u-mom-june-2026","runLabel":"Scout-2 - no packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.7,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 5 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 0 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.8, distribution present, forecast step count 1.","evidence":["The control sees the recent headline CPI deceleration but treats energy risk as generic residual volatility rather than a structured component.","Forecast: point 0.35, 80% interval [0, 0.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The control sees the recent headline CPI deceleration but treats energy risk as generic residual volatility rather than a structured component."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 0.35, 80% interval [0, 0.8]"]}],"flags":["no_typed_tool_call"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-cpi-u-mom-june-2026\nrunLabel: Scout-2 - no packs\nresolutionDate: 2026-07-14\ntraceLineCount: 3\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). Flags: no_typed_tool_call."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-cpi-u-mom-june-2026.2026-06-15T09-35-00-04-00.headline-cpi-energy-packs.d73fb213fca1d5d9","runId":"run.us-cpi-u-mom-june-2026.2026-06-15T09-35-00-04-00.headline-cpi-energy-packs.d73fb213fca1d5d9","predictionId":"us-cpi-u-mom-june-2026","specId":"spec.us-cpi-u-mom-june-2026","runLabel":"Brier-1 - CPI energy packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.05,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 5 historical point(s) and implicit outside-view language.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"energy-price-nowcast@0.1.0\", \"cpi-component-decomposition@0.1.0\", \"tariff-pass-through@0.1.0\", \"release-vintage-calibration@0.1.0\"], target: \"bls.cpi.u.headline_mom.june_2026.first_print\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"energy-price-nowcast@0.1.0\", \"cpi-component-decomposition@0.1.0\", \"tariff-pass-through@0.1.0\", \"release-vintage-calibration@0.1.0\"], target: \"bls.cpi.u.headline_mom.june_2026.first_print\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"energy-price-nowcast@0.1.0\", \"cpi-component-decomposition@0.1.0\", \"tariff-pass-through@0.1.0\", \"release-vintage-calibration@0.1.0\"], target: \"bls.cpi.u.headline_mom.june_2026.first_print\" })","Tool result: { admitted: 5, mode: \"with_packs\", required_checks: [\"energy_nowcast\", \"component_recombine\", \"tariff_tail\", \"first_print_rounding\"] }"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.6, distribution present, forecast step count 1.","evidence":["Tool result: { admitted: 5, mode: \"with_packs\", required_checks: [\"energy_nowcast\", \"component_recombine\", \"tariff_tail\", \"first_print_rounding\"] }","Energy and pipeline-price packs keep the center a touch above the aggregate control while the release pack prevents the interval from becoming too wide."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Energy and pipeline-price packs keep the center a touch above the aggregate control while the release pack prevents the interval from becoming too wide.","Forecast: point 0.45, 80% interval [0.15, 0.75]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-cpi-u-mom-june-2026\nrunLabel: Brier-1 - CPI energy packs\nresolutionDate: 2026-07-14\ntraceLineCount: 5\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-cpi-u-mom-june-2026.2026-06-17T02-22-09Z.us-cpi-u-mom-june-2026-thesis-analyst-fast-2026-06-17t02-22-09z.1e2f3cab72a98ae6","runId":"run.us-cpi-u-mom-june-2026.2026-06-17T02-22-09Z.us-cpi-u-mom-june-2026-thesis-analyst-fast-2026-06-17t02-22-09z.1e2f3cab72a98ae6","predictionId":"us-cpi-u-mom-june-2026","specId":"spec.us-cpi-u-mom-june-2026","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.51,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 5 historical point(s) and implicit outside-view language.","evidence":["Base-rate/reference-class: the last six published all-items monthly changes average about 0.47 percent and have a median of 0.4 percent, but that reference class includes an unusually large energy impulse in March through May.","Use the six-month headline median of 0.4 as the anchor; lean slightly below the 0.47 average because May core was 0.2 and food was 0.2, while keep a wide 80% interval of 0.1 to 0.8 to reflect energy volatility."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 2 source-context item(s), activity log present.","evidence":["The resolver is the BLS first print for CPI-U all items, U.S. city average, seasonally adjusted percent change from May 2026 to June 2026, released in the CPI Summary and Table A.","Tool call: BLS CPI release calendar for the June 2026 reference month"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast for June 2026 headline CPI-U m/m first print","The resolver is the BLS first print for CPI-U all items, U.S. city average, seasonally adjusted percent change from May 2026 to June 2026, released in the CPI Summary and Table A."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.7, distribution present, forecast step count 1.","evidence":["Use the six-month headline median of 0.4 as the anchor; lean slightly below the 0.47 average because May core was 0.2 and food was 0.2, while keep a wide 80% interval of 0.1 to 0.8 to reflect energy volatility.","Forecast: point 0.4, 80% interval [0.1, 0.8]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: BLS Table A component momentum for May 2026","Use the six-month headline median of 0.4 as the anchor; lean slightly below the 0.47 average because May core was 0.2 and food was 0.2, while keep a wide 80% interval of 0.1 to 0.8 to reflect energy volatility."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":["Base-rate/reference-class: the last six published all-items monthly changes average about 0.47 percent and have a median of 0.4 percent, but that reference class includes an unusually large energy impulse in March through May."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for June 2026 headline CPI-U m/m first print","Use the six-month headline median of 0.4 as the anchor; lean slightly below the 0.47 average because May core was 0.2 and food was 0.2, while keep a wide 80% interval of 0.1 to 0.8 to reflect energy volatility."]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-cpi-u-mom-june-2026\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-07-14\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-cpi-u-mom-june-2026.2026-06-21T15-10-03Z.us-cpi-u-mom-june-2026-thesis-analyst-fast-2026-06-21t15-10-03z.1e2f3cab72a98ae6","runId":"run.us-cpi-u-mom-june-2026.2026-06-21T15-10-03Z.us-cpi-u-mom-june-2026-thesis-analyst-fast-2026-06-21t15-10-03z.1e2f3cab72a98ae6","predictionId":"us-cpi-u-mom-june-2026","specId":"spec.us-cpi-u-mom-june-2026","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 5 historical point(s) and implicit outside-view language.","evidence":["Base-rate/reference-class: recent one-month headline CPI prints before the target were 0.2, 0.3, 0.9, 0.6, and 0.5. Their simple average is 0.5, but the median is also 0.5 and the latest core reading of 0.2 suggests headline pressure is being pulled up by volatile energy rather than a broad acceleration."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The resolver is the BLS first print for CPI-U, U.S. city average, all items, seasonally adjusted percent change from May 2026 to June 2026. This is a data-release target, not a later revised time-series value.","Tool call: Checked the BLS Consumer Price Index release schedule for the June 2026 reference month."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is the BLS first print for CPI-U, U.S. city average, all items, seasonally adjusted percent change from May 2026 to June 2026. This is a data-release target, not a later revised time-series value.","Tool call: Checked the BLS Consumer Price Index release schedule for the June 2026 reference month."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.7, distribution present, forecast step count 1.","evidence":["Tool call: Read CPI Summary component details for the May 2026 composition of headline inflation.","Use a reference-class center near 0.5, shade down by 0.1 because May core CPI was 0.2 and some mean reversion is likely after March 0.9, April 0.6, and May 0.5. Set pointEstimate = 0.4. An 80% interval of 0.1 to 0.8 covers a soft core-led month through a renewed energy-led upside surprise and respects one-decimal BLS rounding."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base-rate/reference-class: recent one-month headline CPI prints before the target were 0.2, 0.3, 0.9, 0.6, and 0.5. Their simple average is 0.5, but the median is also 0.5 and the latest core reading of 0.2 suggests headline pressure is being pulled up by volatile energy rather than a broad acceleration.","Use a reference-class center near 0.5, shade down by 0.1 because May core CPI was 0.2 and some mean reversion is likely after March 0.9, April 0.6, and May 0.5. Set pointEstimate = 0.4. An 80% interval of 0.1 to 0.8 covers a soft core-led month through a renewed energy-led upside surprise and respects one-decimal BLS rounding."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base-rate/reference-class: recent one-month headline CPI prints before the target were 0.2, 0.3, 0.9, 0.6, and 0.5. Their simple average is 0.5, but the median is also 0.5 and the latest core reading of 0.2 suggests headline pressure is being pulled up by volatile energy rather than a broad acceleration."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for June 2026 CPI-U headline month-over-month","Use a reference-class center near 0.5, shade down by 0.1 because May core CPI was 0.2 and some mean reversion is likely after March 0.9, April 0.6, and May 0.5. Set pointEstimate = 0.4. An 80% interval of 0.1 to 0.8 covers a soft core-led month through a renewed energy-led upside surprise and respects one-decimal BLS rounding."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-cpi-u-mom-june-2026\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-07-14\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-cpi-u-mom-june-2026.2026-07-08T02-46-59Z.us-cpi-u-mom-june-2026-thesis-analyst-fast-2026-07-08t02-46-59z.2d6389919d3f121b","runId":"run.us-cpi-u-mom-june-2026.2026-07-08T02-46-59Z.us-cpi-u-mom-june-2026-thesis-analyst-fast-2026-07-08t02-46-59z.2d6389919d3f121b","predictionId":"us-cpi-u-mom-june-2026","specId":"spec.us-cpi-u-mom-june-2026","runLabel":"Fast rollout 1 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the six available BLS headline SA prints from Dec 2025 through May 2026 average 0.47 percent, but that reference class is elevated by a large energy shock: March 0.9, April 0.6, and May 0.5 coincided with energy monthly increases of 10.9, 3.8, and 3.9 percent in the BLS release.","Prior/update/interval: persistence prior is the BLS recent headline SA MoM reference class Dec 2025-May 2026 values [0.3, 0.2, 0.3, 0.9, 0.6, 0.5], mean = 0.47; adjustment components are about -0.20 for gasoline/energy reversal, -0.05 for core mean reversion from April, and 0.00 to +0.05 for shelter/food persistence, giving an unrounded center near 0.20. Interval method uses realized dispersion of those change values themselves: sample sigma = 0.258, so 1.28*sigma = 0.330; 0.20 +/- 0.33 implies about -0.13 to 0.53, rounded to a first-print-style 80 percent interval of -0.1 to 0.5."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this is BLS CPI-U all items, U.S. city average, seasonally adjusted month-over-month percent change for June 2026, first print. The series variant is headline CPI-U SA MoM; all CPI anchors below use the same BLS headline SA table, not NSA index levels or core CPI as the target.","Tool call: BLS CPI release schedule for June 2026 reference month"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this is BLS CPI-U all items, U.S. city average, seasonally adjusted month-over-month percent change for June 2026, first print. The series variant is headline CPI-U SA MoM; all CPI anchors below use the same BLS headline SA table, not NSA index levels or core CPI as the target.","Tool call: BLS CPI release schedule for June 2026 reference month"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.6, distribution present, forecast step count 1.","evidence":["Tool call: EIA weekly U.S. retail gasoline prices during June 2026","Prior/update/interval: persistence prior is the BLS recent headline SA MoM reference class Dec 2025-May 2026 values [0.3, 0.2, 0.3, 0.9, 0.6, 0.5], mean = 0.47; adjustment components are about -0.20 for gasoline/energy reversal, -0.05 for core mean reversion from April, and 0.00 to +0.05 for shelter/food persistence, giving an unrounded center near 0.20. Interval method uses realized dispersion of those change values themselves: sample sigma = 0.258, so 1.28*sigma = 0.330; 0.20 +/- 0.33 implies about -0.13 to 0.53, rounded to a first-print-style 80 percent interval of -0.1 to 0.5."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: the six available BLS headline SA prints from Dec 2025 through May 2026 average 0.47 percent, but that reference class is elevated by a large energy shock: March 0.9, April 0.6, and May 0.5 coincided with energy monthly increases of 10.9, 3.8, and 3.9 percent in the BLS release.","Current-release adjustment: EIA gasoline prices declined each week from June 1 through July 6, so the June CPI energy contribution should be below May's large positive energy contribution. Core CPI at 0.2 percent, food at 0.2 percent, and shelter at 0.3 percent in May keep the non-energy center positive but not high enough to preserve a 0.5 percent headline print if gasoline turns down."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast June 2026 headline CPI-U month-over-month","Prior/update/interval: persistence prior is the BLS recent headline SA MoM reference class Dec 2025-May 2026 values [0.3, 0.2, 0.3, 0.9, 0.6, 0.5], mean = 0.47; adjustment components are about -0.20 for gasoline/energy reversal, -0.05 for core mean reversion from April, and 0.00 to +0.05 for shelter/food persistence, giving an unrounded center near 0.20. Interval method uses realized dispersion of those change values themselves: sample sigma = 0.258, so 1.28*sigma = 0.330; 0.20 +/- 0.33 implies about -0.13 to 0.53, rounded to a first-print-style 80 percent interval of -0.1 to 0.5."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-cpi-u-mom-june-2026\nrunLabel: Fast rollout 1 of 3\nresolutionDate: 2026-07-14\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-cpi-u-mom-june-2026.2026-07-08T02-47-33Z.us-cpi-u-mom-june-2026-thesis-analyst-fast-2026-07-08t02-47-33z.1e2f3cab72a98ae6","runId":"run.us-cpi-u-mom-june-2026.2026-07-08T02-47-33Z.us-cpi-u-mom-june-2026-thesis-analyst-fast-2026-07-08t02-47-33z.1e2f3cab72a98ae6","predictionId":"us-cpi-u-mom-june-2026","specId":"spec.us-cpi-u-mom-june-2026","runLabel":"Fast rollout 2 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The target is BLS CPI-U all items, U.S. city average, seasonally adjusted percent change from May 2026 to June 2026. This is the first-print BLS CPI news release value, not a FRED mirror or later revised seasonal-adjustment vintage. The prior June thesis.analyst runs were centered at 0.4 with a 0.1 to 0.8 interval; I use them only as strategy context and keep the center because no newer official CPI print is available before the July 14 release.","Base-rate/reference class: the recent official first-print headline sample for Dec 2025 through May 2026 is 0.3, 0.2, 0.3, 0.9, 0.6, and 0.5 percent. The mean is 0.47 percent and the median is 0.4 percent, but the March-May run was unusually energy-heavy, so I anchor on the median rather than chase the mean higher."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Forecast June 2026 BLS CPI-U headline monthly first print","The target is BLS CPI-U all items, U.S. city average, seasonally adjusted percent change from May 2026 to June 2026. This is the first-print BLS CPI news release value, not a FRED mirror or later revised seasonal-adjustment vintage. The prior June thesis.analyst runs were centered at 0.4 with a 0.1 to 0.8 interval; I use them only as strategy context and keep the center because no newer official CPI print is available before the July 14 release."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast June 2026 BLS CPI-U headline monthly first print","The target is BLS CPI-U all items, U.S. city average, seasonally adjusted percent change from May 2026 to June 2026. This is the first-print BLS CPI news release value, not a FRED mirror or later revised seasonal-adjustment vintage. The prior June thesis.analyst runs were centered at 0.4 with a 0.1 to 0.8 interval; I use them only as strategy context and keep the center because no newer official CPI print is available before the July 14 release."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.7, distribution present, forecast step count 1.","evidence":["The target is BLS CPI-U all items, U.S. city average, seasonally adjusted percent change from May 2026 to June 2026. This is the first-print BLS CPI news release value, not a FRED mirror or later revised seasonal-adjustment vintage. The prior June thesis.analyst runs were centered at 0.4 with a 0.1 to 0.8 interval; I use them only as strategy context and keep the center because no newer official CPI print is available before the July 14 release.","Tool call: Read BLS component detail for the latest published May 2026 CPI release."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The target is BLS CPI-U all items, U.S. city average, seasonally adjusted percent change from May 2026 to June 2026. This is the first-print BLS CPI news release value, not a FRED mirror or later revised seasonal-adjustment vintage. The prior June thesis.analyst runs were centered at 0.4 with a 0.1 to 0.8 interval; I use them only as strategy context and keep the center because no newer official CPI print is available before the July 14 release.","Tool call: Checked official EIA weekly U.S. regular gasoline prices for late-June energy momentum relevant to the June CPI collection period."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base-rate/reference class: the recent official first-print headline sample for Dec 2025 through May 2026 is 0.3, 0.2, 0.3, 0.9, 0.6, and 0.5 percent. The mean is 0.47 percent and the median is 0.4 percent, but the March-May run was unusually energy-heavy, so I anchor on the median rather than chase the mean higher.","Upside risk: gasoline or broader energy prices could keep the June monthly average strong despite late-month declines, and tariff pass-through could add to core goods, which would land above the interval if headline rounds to 0.9 or higher. Downside risk: a sharper gasoline retracement, soft airfares/lodging, or another subdued core print could put the release near 0.0 or outside the interval below 0.1."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast June 2026 BLS CPI-U headline monthly first print","The target is BLS CPI-U all items, U.S. city average, seasonally adjusted percent change from May 2026 to June 2026. This is the first-print BLS CPI news release value, not a FRED mirror or later revised seasonal-adjustment vintage. The prior June thesis.analyst runs were centered at 0.4 with a 0.1 to 0.8 interval; I use them only as strategy context and keep the center because no newer official CPI print is available before the July 14 release."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-cpi-u-mom-june-2026\nrunLabel: Fast rollout 2 of 3\nresolutionDate: 2026-07-14\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-cpi-u-mom-june-2026.2026-07-08T02-48-25Z.us-cpi-u-mom-june-2026-thesis-analyst-fast-2026-07-08t02-48-25z.b3eef9a8674f5ff0","runId":"run.us-cpi-u-mom-june-2026.2026-07-08T02-48-25Z.us-cpi-u-mom-june-2026-thesis-analyst-fast-2026-07-08t02-48-25z.b3eef9a8674f5ff0","predictionId":"us-cpi-u-mom-june-2026","specId":"spec.us-cpi-u-mom-june-2026","runLabel":"Fast rollout 3 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Framing and exact resolver: this is the BLS CPI-U U.S. city average all-items index, seasonally adjusted, month-over-month percent change for June 2026, first print. I use the same SA headline variant for the resolver, anchors, and historical values; series code is CUSR0000SA0 for the all-items CPI-U SA index.","Base rate/reference class: the recent same-variant BLS headline CPI-U monthly changes available in the current release are 0.3, 0.2, 0.3, 0.9, 0.6, and 0.5 from December 2025 through May 2026, averaging about 0.47. That base rate is elevated by the March-May energy shock, so I do not simply persist the latest 0.5."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this is the BLS CPI-U U.S. city average all-items index, seasonally adjusted, month-over-month percent change for June 2026, first print. I use the same SA headline variant for the resolver, anchors, and historical values; series code is CUSR0000SA0 for the all-items CPI-U SA index.","Tool call: BLS schedule of releases for the Consumer Price Index, June 2026 reference month"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this is the BLS CPI-U U.S. city average all-items index, seasonally adjusted, month-over-month percent change for June 2026, first print. I use the same SA headline variant for the resolver, anchors, and historical values; series code is CUSR0000SA0 for the all-items CPI-U SA index.","Tool call: BLS schedule of releases for the Consumer Price Index, June 2026 reference month"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.66, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is the recent official BLS headline CPI-U SA MoM reference class, December 2025-May 2026 values [0.3, 0.2, 0.3, 0.9, 0.6, 0.5], mean 0.467. Update components: underlying core/food/shelter contribution keeps the point positive around +0.35 to +0.40, while the EIA gasoline decline of -9.6% subtracts roughly 0.15 to 0.25 percentage point from headline, giving 0.20. Interval method: realized dispersion of the fetched change values themselves gives sigma = 0.258, so 1.28*sigma = 0.330; 0.20 - 0.33 = -0.13 and 0.20 + 0.33 = 0.53.","Counter-consideration and falsification: upside risk is broader tariff or services pass-through plus a smaller-than-expected CPI gasoline drag, which would land above the interval near 0.6 or higher. Downside risk is a larger seasonally adjusted gasoline reversal or airfares/used vehicles weakness, which would land below the interval near -0.2 or lower. Outside the interval would likely require energy or tariff effects larger than the recent component evidence implies."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and mechanism split: core momentum near 0.2 plus food near 0.2 and shelter near 0.3 point to a positive underlying June print. The one-off adjustment is energy: the EIA gasoline drop from a 4.479 May average to a 4.050 June average should reverse much of May's gasoline CPI strength, pulling headline materially below the recent all-items average."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence prior is the recent official BLS headline CPI-U SA MoM reference class, December 2025-May 2026 values [0.3, 0.2, 0.3, 0.9, 0.6, 0.5], mean 0.467. Update components: underlying core/food/shelter contribution keeps the point positive around +0.35 to +0.40, while the EIA gasoline decline of -9.6% subtracts roughly 0.15 to 0.25 percentage point from headline, giving 0.20. Interval method: realized dispersion of the fetched change values themselves gives sigma = 0.258, so 1.28*sigma = 0.330; 0.20 - 0.33 = -0.13 and 0.20 + 0.33 = 0.53.","Counter-consideration and falsification: upside risk is broader tariff or services pass-through plus a smaller-than-expected CPI gasoline drag, which would land above the interval near 0.6 or higher. Downside risk is a larger seasonally adjusted gasoline reversal or airfares/used vehicles weakness, which would land below the interval near -0.2 or lower. Outside the interval would likely require energy or tariff effects larger than the recent component evidence implies."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast June 2026 headline CPI-U monthly change","Level, momentum, one-off, and mechanism split: core momentum near 0.2 plus food near 0.2 and shelter near 0.3 point to a positive underlying June print. The one-off adjustment is energy: the EIA gasoline drop from a 4.479 May average to a 4.050 June average should reverse much of May's gasoline CPI strength, pulling headline materially below the recent all-items average."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-cpi-u-mom-june-2026\nrunLabel: Fast rollout 3 of 3\nresolutionDate: 2026-07-14\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-cpi-u-mom-june-2026.2026-07-08T02-52-43Z.us-cpi-u-mom-june-2026-thesis-analyst-ladder-2026-07-08t02-52-43z.495f3164f627c54f","runId":"run.us-cpi-u-mom-june-2026.2026-07-08T02-52-43Z.us-cpi-u-mom-june-2026-thesis-analyst-ladder-2026-07-08t02-52-43z.495f3164f627c54f","predictionId":"us-cpi-u-mom-june-2026","specId":"spec.us-cpi-u-mom-june-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the six same-variant BLS headline SA MoM prints from Dec 2025 through May 2026 average 0.47 percent, with latest persistence at 0.5. That base rate is inflated by the energy shock: BLS reported energy monthly increases of 10.9 in March, 3.8 in April, and 3.9 percent in May.","Prior/update/interval: persistence/base-rate prior is the chosen simple time-series prior from the BLS recent headline SA MoM reference class Dec 2025-May 2026 values [0.3, 0.2, 0.3, 0.9, 0.6, 0.5], mean = 0.467; I do not use a richer model because this near-term release is dominated by energy component timing and current public component data. Adjustment components are about -0.20 for gasoline/energy reversal, -0.05 for core mean reversion from April, and 0.00 to +0.05 for shelter/food persistence, giving center near 0.20. Interval method uses realized dispersion of the six fetched recent change values themselves: sigma = 0.258, so 1.28*sigma = 0.330. The ladder-implied 80% half-width is 0.30 around 0.2, close to the recent realized-volatility half-width, so no extra widening is applied."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this is BLS CPI-U all items, U.S. city average, seasonally adjusted month-over-month percent change for June 2026, first print. The series variant is headline CPI-U SA MoM from BLS CPI Summary Table A; anchors below use that same variant, not NSA index levels or core CPI as the target.","Tool call: Checked the BLS CPI release schedule for the June 2026 reference month."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this is BLS CPI-U all items, U.S. city average, seasonally adjusted month-over-month percent change for June 2026, first print. The series variant is headline CPI-U SA MoM from BLS CPI Summary Table A; anchors below use that same variant, not NSA index levels or core CPI as the target.","Tool call: Checked the BLS CPI release schedule for the June 2026 reference month."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.6, distribution present, forecast step count 1.","evidence":["Tool call: Fetched EIA weekly U.S. retail gasoline prices for the June CPI pricing window and latest available week.","Prior/update/interval: persistence/base-rate prior is the chosen simple time-series prior from the BLS recent headline SA MoM reference class Dec 2025-May 2026 values [0.3, 0.2, 0.3, 0.9, 0.6, 0.5], mean = 0.467; I do not use a richer model because this near-term release is dominated by energy component timing and current public component data. Adjustment components are about -0.20 for gasoline/energy reversal, -0.05 for core mean reversion from April, and 0.00 to +0.05 for shelter/food persistence, giving center near 0.20. Interval method uses realized dispersion of the six fetched recent change values themselves: sigma = 0.258, so 1.28*sigma = 0.330. The ladder-implied 80% half-width is 0.30 around 0.2, close to the recent realized-volatility half-width, so no extra widening is applied."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence/base-rate prior is the chosen simple time-series prior from the BLS recent headline SA MoM reference class Dec 2025-May 2026 values [0.3, 0.2, 0.3, 0.9, 0.6, 0.5], mean = 0.467; I do not use a richer model because this near-term release is dominated by energy component timing and current public component data. Adjustment components are about -0.20 for gasoline/energy reversal, -0.05 for core mean reversion from April, and 0.00 to +0.05 for shelter/food persistence, giving center near 0.20. Interval method uses realized dispersion of the six fetched recent change values themselves: sigma = 0.258, so 1.28*sigma = 0.330. The ladder-implied 80% half-width is 0.30 around 0.2, close to the recent realized-volatility half-width, so no extra widening is applied."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Update from previous run/context: an older catalog forecast was centered higher before the full June gasoline decline was visible; I treat that only as strategy context, not evidence. The public EIA price path since June 1 makes the energy contribution materially lower than in May, while May core 0.2, food 0.2, and shelter 0.3 keep a positive non-energy floor.","Counter-consideration and scenarios: upside risk would land above the interval if June gasoline seasonal adjustment or renewed oil disruption keeps energy CPI positive while shelter/core services reaccelerate, pushing headline above 0.5. Downside risk would land below the interval if gasoline, airfares, and vehicle-related prices fall together enough to offset core services and food, pushing headline below -0.1. An outside the interval miss would most likely come from an energy seasonal-adjustment surprise rather than the stable core categories."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast June 2026 headline CPI-U month-over-month","Update from previous run/context: an older catalog forecast was centered higher before the full June gasoline decline was visible; I treat that only as strategy context, not evidence. The public EIA price path since June 1 makes the energy contribution materially lower than in May, while May core 0.2, food 0.2, and shelter 0.3 keep a positive non-energy floor."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-cpi-u-mom-june-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-07-14\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-cpi-u-mom-june-2026.2026-07-08T03-03-42Z.us-cpi-u-mom-june-2026-thesis-analyst-median3-2026-07-08t03-03-42z.62bf27f20964f6dc","runId":"run.us-cpi-u-mom-june-2026.2026-07-08T03-03-42Z.us-cpi-u-mom-june-2026-thesis-analyst-median3-2026-07-08t03-03-42z.62bf27f20964f6dc","predictionId":"us-cpi-u-mom-june-2026","specId":"spec.us-cpi-u-mom-june-2026","runLabel":"Median of 3 rollouts","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 5 historical point(s) and implicit outside-view language.","evidence":["Median-of-3 rollout ensemble","Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-08T02:46:59Z, 2026-07-08T02:47:33Z, 2026-07-08T02:48:25Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["Median CDF quantiles: q10 = -0.1, q50 = 0.2, q90 = 0.53. Constituent points [0.2, 0.4, 0.2] with 80% widths [0.6, 0.7, 0.66]; the median interval inherits the central rollout mass rather than averaging tails."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.63, distribution present, forecast step count 1.","evidence":["Median CDF quantiles: q10 = -0.1, q50 = 0.2, q90 = 0.53. Constituent points [0.2, 0.4, 0.2] with 80% widths [0.6, 0.7, 0.66]; the median interval inherits the central rollout mass rather than averaging tails.","Forecast: point 0.2, 80% interval [-0.1, 0.53]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-08T02:46:59Z, 2026-07-08T02:47:33Z, 2026-07-08T02:48:25Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-08T02:46:59Z, 2026-07-08T02:47:33Z, 2026-07-08T02:48:25Z. Drivers and resolver fields mirror the rollout closest to the median.","Tool result: {rollout_points: [0.2, 0.4, 0.2], rollout_widths: [0.6, 0.7, 0.66], q10: -0.1, q50: 0.2, q90: 0.53}"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-cpi-u-mom-june-2026\nrunLabel: Median of 3 rollouts\nresolutionDate: 2026-07-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-core-cpi-mom-june-2026.2026-06-12T18-59-50Z.739543bf6e74a03a","runId":"run.us-core-cpi-mom-june-2026.2026-06-12T18-59-50Z.739543bf6e74a03a","predictionId":"us-core-cpi-mom-june-2026","specId":"spec.us-core-cpi-mom-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.08,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate over the last 12 months: core MoM has averaged ~+0.25% and ranged 0.19-0.38%. The modal rounded outcome is +0.3% (months like Jan 0.30, Apr 0.38 round to 0.3-0.4; Feb/Mar/May round to 0.2). +0.3 and +0.2 split most of the probability."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log absent.","evidence":["Tool call: Verified independently: BLS reported core CPI +0.2% MoM SA for May 2026 (and +2.9% YoY per the CNBC summary).","Tool result: Verified independently: BLS reported core CPI +0.2% MoM SA for May 2026 (and +2.9% YoY per the CNBC summary). FRED (+0.208%) and BLS (+0.2%) agree; the recorded Thesis May forecast had been +0.3% and resolved to +0.2%."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.3, distribution present, forecast step count 1.","evidence":["Outside [0.1, 0.4] if: a sharp services re-acceleration (shelter, medical, insurance) or oil pass-through prints +0.5%; or an unusually soft month (goods deflation, OER softening) prints +0.0-0.1% and the lower bound is breached. Core's tight history makes both tails thin.","Forecast: point 0.3, 80% interval [0.1, 0.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool result: Pass-through check: the May oil shock barely moved core (0.2%), so I do not assume a large indirect lift for June. But airfares/transport can add a tenth; combined with the +0.25% mean this nudges the centre to +0.3% rather than +0.2%."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: Verified independently: BLS reported core CPI +0.2% MoM SA for May 2026 (and +2.9% YoY per the CNBC summary). FRED (+0.208%) and BLS (+0.2%) agree; the recorded Thesis May forecast had been +0.3% and resolved to +0.2%.","Population stdev of core MoM over the last 24 months = 0.083pp — much tighter than headline (0.189). Using ~0.08-0.10pp as 1-sigma, the 80% band (z=1.28) is roughly point +/- ~0.11pp, i.e. about one rounding step either side."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-core-cpi-mom-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-14\ntraceLineCount: 12\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: resolution clarity (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-core-cpi-mom-june-2026.2026-06-14T15-40-00-04-00.core-cpi-control-no-packs.9d9a4b7dab257493","runId":"run.us-core-cpi-mom-june-2026.2026-06-14T15-40-00-04-00.core-cpi-control-no-packs.9d9a4b7dab257493","predictionId":"us-core-cpi-mom-june-2026","specId":"spec.us-core-cpi-mom-june-2026","runLabel":"Scout-2 - no packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.59,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 5 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":2,"rationale":"Score 2/4: 0 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.3, distribution present, forecast step count 1.","evidence":["The control repeats the recent low-0.2 to low-0.3 percent core CPI range with one rounded step of uncertainty.","Forecast: point 0.25, 80% interval [0.1, 0.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The control repeats the recent low-0.2 to low-0.3 percent core CPI range with one rounded step of uncertainty."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 0.25, 80% interval [0.1, 0.4]"]}],"flags":["no_typed_tool_call"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-core-cpi-mom-june-2026\nrunLabel: Scout-2 - no packs\nresolutionDate: 2026-07-14\ntraceLineCount: 3\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: base-rate use (2/4). Flags: no_typed_tool_call."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-core-cpi-mom-june-2026.2026-06-15T09-40-00-04-00.core-cpi-component-packs.360f55a4f13276f7","runId":"run.us-core-cpi-mom-june-2026.2026-06-15T09-40-00-04-00.core-cpi-component-packs.360f55a4f13276f7","predictionId":"us-core-cpi-mom-june-2026","specId":"spec.us-core-cpi-mom-june-2026","runLabel":"Brier-1 - core CPI packs","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.32,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 5 historical point(s) and implicit outside-view language.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"cpi-component-decomposition@0.1.0\", \"tariff-pass-through@0.1.0\", \"release-vintage-calibration@0.1.0\"], target: \"bls.cpi.u.core_mom.june_2026.first_print\" })","The component pack leaves the median at one rounded 0.3 percent print but adds a slightly higher upper tail for core goods and transport pass-through."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 2 source-context item(s), activity log absent.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"cpi-component-decomposition@0.1.0\", \"tariff-pass-through@0.1.0\", \"release-vintage-calibration@0.1.0\"], target: \"bls.cpi.u.core_mom.june_2026.first_print\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: brier.pack.apply({ packs: [\"base-rate-first@0.1.0\", \"cpi-component-decomposition@0.1.0\", \"tariff-pass-through@0.1.0\", \"release-vintage-calibration@0.1.0\"], target: \"bls.cpi.u.core_mom.june_2026.first_print\" })","Tool result: { admitted: 4, mode: \"with_packs\", required_checks: [\"core_services\", \"core_goods_tail\", \"first_print_rounding\"] }"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.3, distribution present, forecast step count 1.","evidence":["Tool result: { admitted: 4, mode: \"with_packs\", required_checks: [\"core_services\", \"core_goods_tail\", \"first_print_rounding\"] }","The component pack leaves the median at one rounded 0.3 percent print but adds a slightly higher upper tail for core goods and transport pass-through."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":3,"rationale":"Score 3/4: offsetting-evidence language is present.","evidence":["The component pack leaves the median at one rounded 0.3 percent print but adds a slightly higher upper tail for core goods and transport pass-through."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: point 0.3, 80% interval [0.15, 0.45]"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-core-cpi-mom-june-2026\nrunLabel: Brier-1 - core CPI packs\nresolutionDate: 2026-07-14\ntraceLineCount: 5\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: mechanism reasoning (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-core-cpi-mom-june-2026.2026-06-17T02-23-02Z.us-core-cpi-mom-june-2026-thesis-analyst-fast-2026-06-17t02-23-02z.212246a87180ffa3","runId":"run.us-core-cpi-mom-june-2026.2026-06-17T02-23-02Z.us-core-cpi-mom-june-2026-thesis-analyst-fast-2026-06-17t02-23-02z.212246a87180ffa3","predictionId":"us-core-cpi-mom-june-2026","specId":"spec.us-core-cpi-mom-june-2026","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.46,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 5 historical point(s) and implicit outside-view language.","evidence":["The resolver is the first official BLS CPI Summary release for the June 2026 reference month, using the seasonally adjusted CPI-U all items less food and energy monthly percent change, not later revised database values.","Base-rate/reference-class anchor: the five available 2026 core CPI monthly prints average 0.24 percent, with four of five at 0.2 percent and one at 0.4 percent. A one-decimal first print near 0.2 or 0.3 is therefore the central reference class."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Forecast: June 2026 BLS core CPI-U month-over-month first print","The resolver is the first official BLS CPI Summary release for the June 2026 reference month, using the seasonally adjusted CPI-U all items less food and energy monthly percent change, not later revised database values."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast: June 2026 BLS core CPI-U month-over-month first print","The resolver is the first official BLS CPI Summary release for the June 2026 reference month, using the seasonally adjusted CPI-U all items less food and energy monthly percent change, not later revised database values."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.4, distribution present, forecast step count 1.","evidence":["Tool call: Read BLS component details for May core CPI drivers.","Using the 2026 year-to-date core MoM average of (0.2+0.2+0.2+0.4+0.2)/5 = 0.24, I shift slightly upward for possible pass-through and rounding risk to a 0.3 percent point estimate; an 80 percent interval of 0.1 to 0.5 covers a soft repeat, typical noise, and an upside pass-through surprise."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Read BLS component details for May core CPI drivers.","Upside consideration: the large energy shock and transportation-cost pressure in spring 2026 could bleed into airfares, delivery-sensitive goods, and some services, making a 0.3 or 0.4 print plausible even if energy is excluded from core."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-consideration: May showed clear offsets from vehicle insurance, household furnishings, and new vehicles, while shelter was only 0.3 percent; if those soft categories persist, another 0.2 print is very plausible.","Using the 2026 year-to-date core MoM average of (0.2+0.2+0.2+0.4+0.2)/5 = 0.24, I shift slightly upward for possible pass-through and rounding risk to a 0.3 percent point estimate; an 80 percent interval of 0.1 to 0.5 covers a soft repeat, typical noise, and an upside pass-through surprise."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: June 2026 BLS core CPI-U month-over-month first print","Using the 2026 year-to-date core MoM average of (0.2+0.2+0.2+0.4+0.2)/5 = 0.24, I shift slightly upward for possible pass-through and rounding risk to a 0.3 percent point estimate; an 80 percent interval of 0.1 to 0.5 covers a soft repeat, typical noise, and an upside pass-through surprise."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-core-cpi-mom-june-2026\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-07-14\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-core-cpi-mom-june-2026.2026-06-21T15-11-07Z.us-core-cpi-mom-june-2026-thesis-analyst-fast-2026-06-21t15-11-07z.212246a87180ffa3","runId":"run.us-core-cpi-mom-june-2026.2026-06-21T15-11-07Z.us-core-cpi-mom-june-2026-thesis-analyst-fast-2026-06-21t15-11-07z.212246a87180ffa3","predictionId":"us-core-cpi-mom-june-2026","specId":"spec.us-core-cpi-mom-june-2026","runLabel":"Thesis analyst fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.62,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 5 historical point(s) and implicit outside-view language.","evidence":["Base-rate step: the recent rounded BLS core monthly sequence for Jan-May 2026 is 0.3, 0.2, 0.2, 0.4, 0.2, with a mean of 0.26 and a median of 0.2; adding the FRED exact index changes keeps the center close to a rounded 0.2 to 0.3 print."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The resolver is the BLS first print for CPI-U all items less food and energy, seasonally adjusted percent change from the preceding month, for reference month June 2026.","Tool call: Checked the BLS CPI release calendar for the June 2026 reference month."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast for June 2026 US core CPI month-over-month first print","The resolver is the BLS first print for CPI-U all items less food and energy, seasonally adjusted percent change from the preceding month, for reference month June 2026."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.4, distribution present, forecast step count 1.","evidence":["I center the forecast at 0.28 percent exact monthly growth, which rounds to a BLS-style 0.3 percent print. A practical 80 percent interval of 0.1 to 0.5 covers a downside soft-core month and an upside repeat of April-style firmness plus rounding risk.","Counter-consideration: the May release notes headline inflation was being lifted by energy, while the core row was only 0.2 percent; because energy is excluded from the resolver, the energy shock is not enough by itself to push core above 0.3, but second-round transportation or services effects keep upside risk in the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Counter-consideration: the May release notes headline inflation was being lifted by energy, while the core row was only 0.2 percent; because energy is excluded from the resolver, the energy shock is not enough by itself to push core above 0.3, but second-round transportation or services effects keep upside risk in the interval."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["I center the forecast at 0.28 percent exact monthly growth, which rounds to a BLS-style 0.3 percent print. A practical 80 percent interval of 0.1 to 0.5 covers a downside soft-core month and an upside repeat of April-style firmness plus rounding risk.","Counter-consideration: the May release notes headline inflation was being lifted by energy, while the core row was only 0.2 percent; because energy is excluded from the resolver, the energy shock is not enough by itself to push core above 0.3, but second-round transportation or services effects keep upside risk in the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for June 2026 US core CPI month-over-month first print","I center the forecast at 0.28 percent exact monthly growth, which rounds to a BLS-style 0.3 percent print. A practical 80 percent interval of 0.1 to 0.5 covers a downside soft-core month and an upside repeat of April-style firmness plus rounding risk."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-core-cpi-mom-june-2026\nrunLabel: Thesis analyst fast run\nresolutionDate: 2026-07-14\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-core-cpi-mom-june-2026.2026-07-08T02-49-02Z.us-core-cpi-mom-june-2026-thesis-analyst-fast-2026-07-08t02-49-02z.5dbf797e8f5aa349","runId":"run.us-core-cpi-mom-june-2026.2026-07-08T02-49-02Z.us-core-cpi-mom-june-2026-thesis-analyst-fast-2026-07-08t02-49-02z.5dbf797e8f5aa349","predictionId":"us-core-cpi-mom-june-2026","specId":"spec.us-core-cpi-mom-june-2026","runLabel":"Fast rollout 1 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Reference class base rate: recent official first-print core CPI m/m values are centered near 0.25 percent, while the latest BLS print and the Cleveland Fed June nowcast both sit closer to 0.2 than 0.3. That argues for a point just below the simple recent average, not a break to a new high or a zero-like print.","Prior/update/interval: persistence prior uses the recent BLS rounded reference class Nov 2025-May 2026 values 0.2, 0.3, 0.2, 0.2, 0.4, 0.2, 0.2, whose mean is 0.243; update toward Cleveland Fed June core CPI nowcast 0.23 is -0.01 and a small shelter/services persistence adjustment is +0.01, giving 0.24. For this change/flow series, sigma = 0.079 from those realized monthly values; half-width = 1.28*sigma = 0.101, rounded to 0.11 for first-print and component volatility, so 0.24 - 0.11 = 0.13 and 0.24 + 0.11 = 0.35."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["The resolver is the first BLS Consumer Price Index news-release print for CPI-U all items less food and energy, seasonally adjusted month-over-month percent change for June 2026. The relevant release-table variant is CPI-U less food and energy, seasonally adjusted, Table A / series CUSR0000SA0L1E; revisions after the first print are ignored.","Tool call: Checked the BLS Schedule of Releases for the Consumer Price Index for the June 2026 reference month."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["US June 2026 core CPI first-print forecast","The resolver is the first BLS Consumer Price Index news-release print for CPI-U all items less food and energy, seasonally adjusted month-over-month percent change for June 2026. The relevant release-table variant is CPI-U less food and energy, seasonally adjusted, Table A / series CUSR0000SA0L1E; revisions after the first print are ignored."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.22, distribution present, forecast step count 1.","evidence":["Tool result: May 2026 details: all items less food and energy rose 0.2; shelter rose 0.3; owners' equivalent rent rose 0.3; rent rose 0.4; lodging away from home rose 0.4; airline fares rose 2.7; motor vehicle insurance declined 1.7 percent.","Prior/update/interval: persistence prior uses the recent BLS rounded reference class Nov 2025-May 2026 values 0.2, 0.3, 0.2, 0.2, 0.4, 0.2, 0.2, whose mean is 0.243; update toward Cleveland Fed June core CPI nowcast 0.23 is -0.01 and a small shelter/services persistence adjustment is +0.01, giving 0.24. For this change/flow series, sigma = 0.079 from those realized monthly values; half-width = 1.28*sigma = 0.101, rounded to 0.11 for first-print and component volatility, so 0.24 - 0.11 = 0.13 and 0.24 + 0.11 = 0.35."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, and mechanisms: the 12-month core rate at 2.9 percent is still above the Fed target, shelter is persistent at roughly 0.3 percent monthly, and services volatility can lift core. Offsetting that, May core goods were soft and the June nowcast does not show a tariff or services shock large enough to push the central forecast to 0.4."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, and mechanisms: the 12-month core rate at 2.9 percent is still above the Fed target, shelter is persistent at roughly 0.3 percent monthly, and services volatility can lift core. Offsetting that, May core goods were soft and the June nowcast does not show a tariff or services shock large enough to push the central forecast to 0.4.","Counter-consideration: upside risk would come from renewed airfare, medical-care, shelter, or tariff-sensitive goods strength and would land above the interval if June core prints around 0.4 or higher. Downside risk would come from another drop in vehicle insurance, household furnishings, new vehicles, or airfares and would land below the interval if the rounded release is 0.1 or lower. An outside the interval result requires a broad services/goods surprise rather than ordinary month-to-month noise."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["US June 2026 core CPI first-print forecast","Reference class base rate: recent official first-print core CPI m/m values are centered near 0.25 percent, while the latest BLS print and the Cleveland Fed June nowcast both sit closer to 0.2 than 0.3. That argues for a point just below the simple recent average, not a break to a new high or a zero-like print."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-core-cpi-mom-june-2026\nrunLabel: Fast rollout 1 of 3\nresolutionDate: 2026-07-14\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-core-cpi-mom-june-2026.2026-07-08T02-49-19Z.us-core-cpi-mom-june-2026-thesis-analyst-fast-2026-07-08t02-49-19z.ea8a753cdbe8fb4a","runId":"run.us-core-cpi-mom-june-2026.2026-07-08T02-49-19Z.us-core-cpi-mom-june-2026-thesis-analyst-fast-2026-07-08t02-49-19z.ea8a753cdbe8fb4a","predictionId":"us-core-cpi-mom-june-2026","specId":"spec.us-core-cpi-mom-june-2026","runLabel":"Fast rollout 2 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the Jan-May 2026 rounded first-print sequence is 0.3, 0.2, 0.2, 0.4, 0.2 percent, with mean 0.26 and median 0.2, so the outside-view center is a high-0.2 monthly core print that would usually publish near 0.3 after one-decimal rounding.","Update from prior public Thesis fast runs: the June 17 and June 21 runs both centered on 0.3 with 0.1 to 0.5 intervals; this run keeps the same central view but tightens the interval mechanically around the recent realized dispersion instead of using a broader round band."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Forecast: June 2026 BLS core CPI-U month-over-month first print","The target is the first official BLS print for CPI-U all items less food and energy, seasonally adjusted, for June 2026; all anchors here use the same SA core CPI-U variant, series CUSR0000SA0L1E/Table 1 rather than NSA, headline CPI, or later revised vintages."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast: June 2026 BLS core CPI-U month-over-month first print","The target is the first official BLS print for CPI-U all items less food and energy, seasonally adjusted, for June 2026; all anchors here use the same SA core CPI-U variant, series CUSR0000SA0L1E/Table 1 rather than NSA, headline CPI, or later revised vintages."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.2, distribution present, forecast step count 1.","evidence":["Tool call: Read BLS May 2026 component details relevant to core CPI momentum.","Update from prior public Thesis fast runs: the June 17 and June 21 runs both centered on 0.3 with 0.1 to 0.5 intervals; this run keeps the same central view but tightens the interval mechanically around the recent realized dispersion instead of using a broader round band."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Read BLS May 2026 component details relevant to core CPI momentum."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Update from prior public Thesis fast runs: the June 17 and June 21 runs both centered on 0.3 with 0.1 to 0.5 intervals; this run keeps the same central view but tightens the interval mechanically around the recent realized dispersion instead of using a broader round band.","Prior/update/interval: persistence prior from the Jan-May 2026 official rounded core CPI-U MoM sample is mean = (0.3+0.2+0.2+0.4+0.2)/5 = 0.26; adjustment components are +0.02 for energy/transport pass-through and core-services persistence, partly offset by soft vehicles, insurance, and furnishings, giving point = 0.28. Interval method uses realized dispersion of the change series values themselves: sigma = sqrt((((0.3-0.26)^2+(0.2-0.26)^2+(0.2-0.26)^2+(0.4-0.26)^2+(0.2-0.26)^2)/5)) = 0.08, so 80% half-width is roughly 1.28*sigma = 1.28*0.08 = 0.1024; 0.28 +/- 0.1024 gives 0.1776 to 0.3824, rounded to 0.18 to 0.38."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: June 2026 BLS core CPI-U month-over-month first print","Update from prior public Thesis fast runs: the June 17 and June 21 runs both centered on 0.3 with 0.1 to 0.5 intervals; this run keeps the same central view but tightens the interval mechanically around the recent realized dispersion instead of using a broader round band."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-core-cpi-mom-june-2026\nrunLabel: Fast rollout 2 of 3\nresolutionDate: 2026-07-14\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-core-cpi-mom-june-2026.2026-07-08T02-51-08Z.us-core-cpi-mom-june-2026-thesis-analyst-fast-2026-07-08t02-51-08z.ea8a753cdbe8fb4a","runId":"run.us-core-cpi-mom-june-2026.2026-07-08T02-51-08Z.us-core-cpi-mom-june-2026-thesis-analyst-fast-2026-07-08t02-51-08z.ea8a753cdbe8fb4a","predictionId":"us-core-cpi-mom-june-2026","specId":"spec.us-core-cpi-mom-june-2026","runLabel":"Fast rollout 3 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the Jan-May 2026 rounded first-print core CPI-U MoM sequence is 0.3, 0.2, 0.2, 0.4, 0.2 percent, with mean 0.26 and median 0.2, so the outside-view center is a high-0.2 monthly core print that would often publish near 0.3 after one-decimal rounding.","Update from prior public Thesis fast runs: June 17 and June 21 public runs centered on 0.3 with 0.1 to 0.5 intervals; this run keeps the central view but sizes the 80% interval mechanically from the recent realized dispersion."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Forecast: June 2026 BLS core CPI-U month-over-month first print","The target is the first official BLS print for CPI-U all items less food and energy, seasonally adjusted, for June 2026; all anchors use the same SA core CPI-U variant, series CUSR0000SA0L1E/Table 1, not NSA, headline CPI, flash, final, or later revised vintages."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast: June 2026 BLS core CPI-U month-over-month first print","The target is the first official BLS print for CPI-U all items less food and energy, seasonally adjusted, for June 2026; all anchors use the same SA core CPI-U variant, series CUSR0000SA0L1E/Table 1, not NSA, headline CPI, flash, final, or later revised vintages."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.2, distribution present, forecast step count 1.","evidence":["Tool call: Read BLS May 2026 component details relevant to core CPI momentum.","Update from prior public Thesis fast runs: June 17 and June 21 public runs centered on 0.3 with 0.1 to 0.5 intervals; this run keeps the central view but sizes the 80% interval mechanically from the recent realized dispersion."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Read BLS May 2026 component details relevant to core CPI momentum."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Update from prior public Thesis fast runs: June 17 and June 21 public runs centered on 0.3 with 0.1 to 0.5 intervals; this run keeps the central view but sizes the 80% interval mechanically from the recent realized dispersion.","Prior/update/interval: persistence prior from the Jan-May 2026 official rounded core CPI-U MoM sample is mean = (0.3+0.2+0.2+0.4+0.2)/5 = 0.26; adjustment components are +0.02 for energy/transport pass-through and core-services persistence, partly offset by soft vehicles, insurance, and furnishings, giving point = 0.28. Interval method uses realized dispersion of the change-series values themselves: sigma = sqrt((((0.3-0.26)^2+(0.2-0.26)^2+(0.2-0.26)^2+(0.4-0.26)^2+(0.2-0.26)^2)/5)) = 0.08, so 80% half-width is roughly 1.28*sigma = 1.28*0.08 = 0.1024; 0.28 +/- 0.1024 gives 0.1776 to 0.3824, rounded to 0.18 to 0.38."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: June 2026 BLS core CPI-U month-over-month first print","Tool call: Ran date -u +%Y-%m-%dT%H:%M:%SZ for this forecast run."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-core-cpi-mom-june-2026\nrunLabel: Fast rollout 3 of 3\nresolutionDate: 2026-07-14\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-core-cpi-mom-june-2026.2026-07-08T02-53-30Z.us-core-cpi-mom-june-2026-thesis-analyst-ladder-2026-07-08t02-53-30z.58ae49f473c795be","runId":"run.us-core-cpi-mom-june-2026.2026-07-08T02-53-30Z.us-core-cpi-mom-june-2026-thesis-analyst-ladder-2026-07-08t02-53-30z.58ae49f473c795be","predictionId":"us-core-cpi-mom-june-2026","specId":"spec.us-core-cpi-mom-june-2026","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The resolver is the first official BLS CPI Summary release for the June 2026 reference month, using CPI-U all items less food and energy, seasonally adjusted percent change from the preceding month. This is the core CPI-U variant, not headline CPI-U, not NSA CPI, and not a later revised database value.","Base rate/reference class: the recent official BLS first-print reference class is the six monthly core CPI-U changes from Dec. 2025 through May 2026: 0.2, 0.3, 0.2, 0.2, 0.4, and 0.2. The mean is 0.25 and the median is 0.2, so the base rate puts most mass on a first print that rounds to 0.2 or 0.3, with 0.4 plausible but not modal."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Forecast for June 2026 BLS core CPI-U month-over-month first print","The resolver is the first official BLS CPI Summary release for the June 2026 reference month, using CPI-U all items less food and energy, seasonally adjusted percent change from the preceding month. This is the core CPI-U variant, not headline CPI-U, not NSA CPI, and not a later revised database value."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast for June 2026 BLS core CPI-U month-over-month first print","The resolver is the first official BLS CPI Summary release for the June 2026 reference month, using CPI-U all items less food and energy, seasonally adjusted percent change from the preceding month. This is the core CPI-U variant, not headline CPI-U, not NSA CPI, and not a later revised database value."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.4, distribution present, forecast step count 1.","evidence":["Tool call: Read BLS May 2026 CPI Summary component details relevant to core CPI momentum.","Prior/update/interval: use a persistence prior from the six-observation BLS first-print core CPI-U reference class for Dec. 2025-May 2026, centered at mean 0.25. Adjustment components are +0.03 for sticky shelter/services and indirect fuel-sensitive pass-through, -0.01 for core goods and vehicle-related softness, and +0.01 for rounding asymmetry around a 0.28 unrounded center, giving a rounded 0.3 point. For a change/flow series, sigma is computed from the values themselves: sigma = sqrt(((0.2-0.25)^2 + (0.3-0.25)^2 + (0.2-0.25)^2 + (0.2-0.25)^2 + (0.4-0.25)^2 + (0.2-0.25)^2) / 6) = 0.076, so 1.28*sigma = 0.097. The ladder-implied unrounded 80% half-width is roughly (0.492 - 0.06) / 2 = 0.216, wider than and overriding the short-sample 1.28*sigma width because the target is still one unreleased monthly first print with tariff, indirect fuel-channel, and services-price tail risk not fully represented in the short six-month sample."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Read BLS May 2026 CPI Summary component details relevant to core CPI momentum.","Level, momentum, one-off, and mechanism split: the level is still firm at 2.9 percent year over year, but May momentum was only 0.2 after April's 0.4. Shelter at 0.3 and medical care services at 0.5 argue against a very soft core print; core commodities at -0.1, new vehicles at -0.3, and motor vehicle insurance at -1.7 argue against extrapolating April's 0.4. Energy is excluded directly, but gasoline and airfares can pass through indirectly at the margin."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: the recent official BLS first-print reference class is the six monthly core CPI-U changes from Dec. 2025 through May 2026: 0.2, 0.3, 0.2, 0.2, 0.4, and 0.2. The mean is 0.25 and the median is 0.2, so the base rate puts most mass on a first print that rounds to 0.2 or 0.3, with 0.4 plausible but not modal.","Level, momentum, one-off, and mechanism split: the level is still firm at 2.9 percent year over year, but May momentum was only 0.2 after April's 0.4. Shelter at 0.3 and medical care services at 0.5 argue against a very soft core print; core commodities at -0.1, new vehicles at -0.3, and motor vehicle insurance at -1.7 argue against extrapolating April's 0.4. Energy is excluded directly, but gasoline and airfares can pass through indirectly at the margin."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for June 2026 BLS core CPI-U month-over-month first print","Ladder: P(X <= -0.1) = 0.03, P(X <= 0) = 0.07, P(X <= 0.1) = 0.12, P(X <= 0.15) = 0.20, P(X <= 0.2) = 0.32, P(X <= 0.25) = 0.43, P(X <= 0.3) = 0.56, P(X <= 0.35) = 0.68, P(X <= 0.4) = 0.78, P(X <= 0.45) = 0.85, P(X <= 0.5) = 0.91, P(X <= 0.6) = 0.97, P(X <= 0.7) = 0.99. Linear interpolation gives p10 at 0.06, p50 at 0.277, and p90 at 0.492; rounding to BLS one-decimal print precision gives ciLow 0.1, pointEstimate 0.3, and ciHigh 0.5."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-core-cpi-mom-june-2026\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-07-14\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-core-cpi-mom-june-2026.2026-07-08T03-03-42Z.us-core-cpi-mom-june-2026-thesis-analyst-median3-2026-07-08t03-03-42z.e8a1d2b934161a6b","runId":"run.us-core-cpi-mom-june-2026.2026-07-08T03-03-42Z.us-core-cpi-mom-june-2026-thesis-analyst-median3-2026-07-08t03-03-42z.e8a1d2b934161a6b","predictionId":"us-core-cpi-mom-june-2026","specId":"spec.us-core-cpi-mom-june-2026","runLabel":"Median of 3 rollouts","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 5 historical point(s) and implicit outside-view language.","evidence":["Median-of-3 rollout ensemble","Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-08T02:49:02Z, 2026-07-08T02:49:19Z, 2026-07-08T02:51:08Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 7 source-context item(s), activity log present.","evidence":["Median CDF quantiles: q10 = 0.18, q50 = 0.28, q90 = 0.38. Constituent points [0.24, 0.28, 0.28] with 80% widths [0.22, 0.2, 0.2]; the median interval inherits the central rollout mass rather than averaging tails."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.2, distribution present, forecast step count 1.","evidence":["Median CDF quantiles: q10 = 0.18, q50 = 0.28, q90 = 0.38. Constituent points [0.24, 0.28, 0.28] with 80% widths [0.22, 0.2, 0.2]; the median interval inherits the central rollout mass rather than averaging tails.","Forecast: point 0.28, 80% interval [0.18, 0.38]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-08T02:49:02Z, 2026-07-08T02:49:19Z, 2026-07-08T02:51:08Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-08T02:49:02Z, 2026-07-08T02:49:19Z, 2026-07-08T02:51:08Z. Drivers and resolver fields mirror the rollout closest to the median.","Tool result: {rollout_points: [0.24, 0.28, 0.28], rollout_widths: [0.22, 0.2, 0.2], q10: 0.18, q50: 0.28, q90: 0.38}"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-core-cpi-mom-june-2026\nrunLabel: Median of 3 rollouts\nresolutionDate: 2026-07-14\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.initial-claims-week-2026-07-04.2026-07-04T19-02-08Z.db025e16bbd97486","runId":"run.initial-claims-week-2026-07-04.2026-07-04T19-02-08Z.db025e16bbd97486","predictionId":"initial-claims-week-2026-07-04","specId":"spec.initial-claims-week-2026-07-04","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool result: Fetched latest official claims: week ending June 27, 2026 seasonally adjusted initial claims were 215,000; the prior week was revised to 216,000 from 215,000; the four-week moving average was 222,000, down 2,500 from the revised 224,500 prior average.","Tool result: Fetched labor-market slack context: seasonally adjusted insured unemployment for week ending June 20 was 1,814,000, up 2,000 from the revised prior week; the insured unemployment rate was 1.2 percent; the insured-unemployment four-week average was 1,803,000, up 10,750."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Tool result: Fetched official schedule evidence: the UI Weekly Claims News Release is published Thursday at 8:30 AM EST, the archive page was updated July 2, 2026, and the only listed 2026 non-Thursday exception is Wednesday, November 25, 2026; therefore the first release covering week ending July 4, 2026 is Thursday, July 9, 2026.","Tool call: Opened the July 2, 2026 DOL UI Weekly Claims news release for the latest official claims data."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the first-print DOL/ETA advance seasonally adjusted initial claims count for the week ending July 4, 2026, reported in thousands. The canonical catalog slug and unit match the target contract.","Tool result: Fetched official schedule evidence: the UI Weekly Claims News Release is published Thursday at 8:30 AM EST, the archive page was updated July 2, 2026, and the only listed 2026 non-Thursday exception is Wednesday, November 25, 2026; therefore the first release covering week ending July 4, 2026 is Thursday, July 9, 2026."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 34, distribution present, forecast step count 1.","evidence":["Level, momentum, and mechanism: the level is low but not unusually low relative to spring 2026. Momentum is downward from the June 6 peak of 230 to 215, while continuing claims and the weak payroll print suggest slower hiring rather than a clean layoff surge. The July 4 holiday week adds seasonal-factor risk, so persistence alone is too low.","Prior/update/interval: persistence prior is the latest DOL print of 215 thousand blended with the recent six-week mean of 220.8 and four-week average of 222.0. I add 3 thousand for mean reversion toward the recent average, 1 thousand for weak payroll and continuing-claims pressure, and 1 thousand for holiday-week seasonal-adjustment upside risk, giving 220 thousand. The 80% interval uses recent realized weekly dispersion from the official table, where adjacent changes included +13, +5, -3, -11, and -1 thousand, widened for holiday-week noise to roughly -16/+18 thousand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, and mechanism: the level is low but not unusually low relative to spring 2026. Momentum is downward from the June 6 peak of 230 to 215, while continuing claims and the weak payroll print suggest slower hiring rather than a clean layoff surge. The July 4 holiday week adds seasonal-factor risk, so persistence alone is too low.","Prior/update/interval: persistence prior is the latest DOL print of 215 thousand blended with the recent six-week mean of 220.8 and four-week average of 222.0. I add 3 thousand for mean reversion toward the recent average, 1 thousand for weak payroll and continuing-claims pressure, and 1 thousand for holiday-week seasonal-adjustment upside risk, giving 220 thousand. The 80% interval uses recent realized weekly dispersion from the official table, where adjacent changes included +13, +5, -3, -11, and -1 thousand, widened for holiday-week noise to roughly -16/+18 thousand."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, and mechanism: the level is low but not unusually low relative to spring 2026. Momentum is downward from the June 6 peak of 230 to 215, while continuing claims and the weak payroll print suggest slower hiring rather than a clean layoff surge. The July 4 holiday week adds seasonal-factor risk, so persistence alone is too low.","Prior/update/interval: persistence prior is the latest DOL print of 215 thousand blended with the recent six-week mean of 220.8 and four-week average of 222.0. I add 3 thousand for mean reversion toward the recent average, 1 thousand for weak payroll and continuing-claims pressure, and 1 thousand for holiday-week seasonal-adjustment upside risk, giving 220 thousand. The 80% interval uses recent realized weekly dispersion from the official table, where adjacent changes included +13, +5, -3, -11, and -1 thousand, widened for holiday-week noise to roughly -16/+18 thousand."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for U.S. initial claims, week ending July 4, 2026","Prior/update/interval: persistence prior is the latest DOL print of 215 thousand blended with the recent six-week mean of 220.8 and four-week average of 222.0. I add 3 thousand for mean reversion toward the recent average, 1 thousand for weak payroll and continuing-claims pressure, and 1 thousand for holiday-week seasonal-adjustment upside risk, giving 220 thousand. The 80% interval uses recent realized weekly dispersion from the official table, where adjacent changes included +13, +5, -3, -11, and -1 thousand, widened for holiday-week noise to roughly -16/+18 thousand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: initial-claims-week-2026-07-04\nrunLabel: Headline\nresolutionDate: 2026-07-09\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.initial-claims-week-2026-07-04.2026-07-08T02-44-18Z.initial-claims-week-2026-07-04-thesis-analyst-fast-2026-07-08t02-44-18z.bc8e2d1695478994","runId":"run.initial-claims-week-2026-07-04.2026-07-08T02-44-18Z.initial-claims-week-2026-07-04-thesis-analyst-fast-2026-07-08t02-44-18z.bc8e2d1695478994","predictionId":"initial-claims-week-2026-07-04","specId":"spec.initial-claims-week-2026-07-04","runLabel":"Fast rollout 1 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool result: Fetched table values: Initial Claims (SA) June 27 215,000, June 20 216,000, June 13 227,000, prior year comparable 231,000; Initial Claims (NSA) June 27 213,550 and June 20 208,005.","Base rate/reference class: the 2026 weekly SA initial-claims reference class from January 3 through June 27 runs mostly in a 190 to 230 thousand range, with the latest four-week average at 222 thousand. Persistence from 215 is the main base rate, but the gap to the four-week average and holiday-week noise argue against forecasting another sharp decline."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this is the Department of Labor ETA Unemployment Insurance Weekly Claims advance seasonally adjusted initial claims series, in thousands, for the week ending July 4, 2026. The target is the first print only; later revisions are ignored. The variant is seasonally adjusted initial claims, not NSA claims, continuing claims, or four-week average.","Tool result: Fetched official schedule text: UI Weekly Claims News Release is published each Thursday at 8:30 AM EST, with only listed 2026 exception Wednesday November 25, 2026; therefore the week ending July 4, 2026 first print is scheduled Thursday July 9, 2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this is the Department of Labor ETA Unemployment Insurance Weekly Claims advance seasonally adjusted initial claims series, in thousands, for the week ending July 4, 2026. The target is the first print only; later revisions are ignored. The variant is seasonally adjusted initial claims, not NSA claims, continuing claims, or four-week average.","Tool result: Fetched official schedule text: UI Weekly Claims News Release is published each Thursday at 8:30 AM EST, with only listed 2026 exception Wednesday November 25, 2026; therefore the week ending July 4, 2026 first print is scheduled Thursday July 9, 2026."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 28, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior from the latest official SA print is 215 thousand, historical sample is weekly SA initial-claims values from Jan. 3 to Jun. 27 2026, adjustment components are +2 thousand mean reversion toward the 222 thousand four-week average and +1 thousand holiday/seasonal-noise allowance, giving point 218. For interval, compute successive weekly changes from the fetched 2026 history; sigma = 10.66 thousand, so 1.28*sigma = 13.64 thousand. Rounded to whole thousands, 218 - 14 = 204 and 218 + 14 = 232.","Counter-consideration and falsification: upside risk is a holiday-week seasonal-adjustment miss or state-level layoff bulge that would land above the interval, over 232 thousand. Downside risk is continued low layoff activity plus favorable seasonal adjustment that would land below the interval, under 204 thousand. The central case is a modest rebound, not a break in the labor market."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, and mechanism split: level is low relative to the June four-week average; momentum is downward over June 6 to June 27; continuing claims at 1.814 million point to slower hiring rather than mass layoffs; the July 4 week can distort seasonal factors, so I add only a small rebound from the latest print."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: the 2026 weekly SA initial-claims reference class from January 3 through June 27 runs mostly in a 190 to 230 thousand range, with the latest four-week average at 222 thousand. Persistence from 215 is the main base rate, but the gap to the four-week average and holiday-week noise argue against forecasting another sharp decline.","Counter-consideration and falsification: upside risk is a holiday-week seasonal-adjustment miss or state-level layoff bulge that would land above the interval, over 232 thousand. Downside risk is continued low layoff activity plus favorable seasonal adjustment that would land below the interval, under 204 thousand. The central case is a modest rebound, not a break in the labor market."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast US initial claims for week ending July 4, 2026","Base rate/reference class: the 2026 weekly SA initial-claims reference class from January 3 through June 27 runs mostly in a 190 to 230 thousand range, with the latest four-week average at 222 thousand. Persistence from 215 is the main base rate, but the gap to the four-week average and holiday-week noise argue against forecasting another sharp decline."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: initial-claims-week-2026-07-04\nrunLabel: Fast rollout 1 of 3\nresolutionDate: 2026-07-09\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.initial-claims-week-2026-07-04.2026-07-08T02-44-20Z.initial-claims-week-2026-07-04-thesis-analyst-fast-2026-07-08t02-44-20z.cc7bdcad03ef8639","runId":"run.initial-claims-week-2026-07-04.2026-07-08T02-44-20Z.initial-claims-week-2026-07-04-thesis-analyst-fast-2026-07-08t02-44-20z.cc7bdcad03ef8639","predictionId":"initial-claims-week-2026-07-04","specId":"spec.initial-claims-week-2026-07-04","runLabel":"Fast rollout 2 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool result: Fetched latest same-variant values: seasonally adjusted initial claims for week ending June 27, 2026 were 215,000; the previous week was revised to 216,000; the four-week moving average was 222,000, down 2,500 from the revised 224,500 prior average.","Tool result: Fetched unadjusted context: advance NSA initial claims for week ending June 27, 2026 totaled 213,550, up 5,545 from the prior week; comparable 2025 NSA initial claims were 230,392; the July 2 table listed US Total NSA initial claims of 213,550."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Tool result: Fetched official schedule evidence: the UI Weekly Claims News Release is published each Thursday at 8:30 AM Eastern; the archive page was updated July 7, 2026; the only listed 2026 non-Thursday exception is November 25, 2026; therefore the first release for week ending July 4, 2026 is Thursday, July 9, 2026.","Tool call: Opened the official BLS June 2026 Employment Situation release for broader labor-market context."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Tool result: Fetched official schedule evidence: the UI Weekly Claims News Release is published each Thursday at 8:30 AM Eastern; the archive page was updated July 7, 2026; the only listed 2026 non-Thursday exception is November 25, 2026; therefore the first release for week ending July 4, 2026 is Thursday, July 9, 2026.","Tool call: Opened the July 2, 2026 DOL UI Weekly Claims release for the latest same-series initial-claims values."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 32, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is latest-value persistence at 215 thousand, with a reference class of the 10 fetched same-variant DOL values from April 25 through June 27. I add +2 thousand for mean reversion toward the 222 thousand four-week average, +1 thousand for weak payroll and downward revision risk, and +1 thousand for holiday-week seasonal volatility, giving 219 thousand. Interval method uses realized dispersion of the fetched same-variant weekly flow values themselves; sigma = 12.4 thousand, so 1.28*sigma = 15.9 thousand. I round the half-width to 16 thousand because this is within the empirical 80% scale and the holiday week argues against narrowing.","Point calculation: 215 latest + 2 mean-reversion adjustment + 1 weak-labor-market adjustment + 1 holiday-volatility adjustment = 219 thousand. Interval calculation: sigma = 12.4 thousand; 1.28*sigma = 15.9 thousand; rounded half-width = 16 thousand, so 219 - 16 = 203 and 219 + 16 = 235 thousand."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and policy split: the current level is low relative to late May and early June, momentum is downward over the last three prints from 230 to 227 to 216 to 215, and the four-week average is also easing. The main one-off is the Independence Day week seasonal-adjustment problem; the broader labor market from BLS is softer, but there is no public policy mechanism in the checked material that should create a discrete claims break for this week.","Prior/update/interval: persistence prior is latest-value persistence at 215 thousand, with a reference class of the 10 fetched same-variant DOL values from April 25 through June 27. I add +2 thousand for mean reversion toward the 222 thousand four-week average, +1 thousand for weak payroll and downward revision risk, and +1 thousand for holiday-week seasonal volatility, giving 219 thousand. Interval method uses realized dispersion of the fetched same-variant weekly flow values themselves; sigma = 12.4 thousand, so 1.28*sigma = 15.9 thousand. I round the half-width to 16 thousand because this is within the empirical 80% scale and the holiday week argues against narrowing."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, one-off, and policy split: the current level is low relative to late May and early June, momentum is downward over the last three prints from 230 to 227 to 216 to 215, and the four-week average is also easing. The main one-off is the Independence Day week seasonal-adjustment problem; the broader labor market from BLS is softer, but there is no public policy mechanism in the checked material that should create a discrete claims break for this week.","Prior/update/interval: persistence prior is latest-value persistence at 215 thousand, with a reference class of the 10 fetched same-variant DOL values from April 25 through June 27. I add +2 thousand for mean reversion toward the 222 thousand four-week average, +1 thousand for weak payroll and downward revision risk, and +1 thousand for holiday-week seasonal volatility, giving 219 thousand. Interval method uses realized dispersion of the fetched same-variant weekly flow values themselves; sigma = 12.4 thousand, so 1.28*sigma = 15.9 thousand. I round the half-width to 16 thousand because this is within the empirical 80% scale and the holiday week argues against narrowing."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: persistence prior is latest-value persistence at 215 thousand, with a reference class of the 10 fetched same-variant DOL values from April 25 through June 27. I add +2 thousand for mean reversion toward the 222 thousand four-week average, +1 thousand for weak payroll and downward revision risk, and +1 thousand for holiday-week seasonal volatility, giving 219 thousand. Interval method uses realized dispersion of the fetched same-variant weekly flow values themselves; sigma = 12.4 thousand, so 1.28*sigma = 15.9 thousand. I round the half-width to 16 thousand because this is within the empirical 80% scale and the holiday week argues against narrowing.","Point calculation: 215 latest + 2 mean-reversion adjustment + 1 weak-labor-market adjustment + 1 holiday-volatility adjustment = 219 thousand. Interval calculation: sigma = 12.4 thousand; 1.28*sigma = 15.9 thousand; rounded half-width = 16 thousand, so 219 - 16 = 203 and 219 + 16 = 235 thousand."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: initial-claims-week-2026-07-04\nrunLabel: Fast rollout 2 of 3\nresolutionDate: 2026-07-09\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.initial-claims-week-2026-07-04.2026-07-08T02-44-44Z.initial-claims-week-2026-07-04-thesis-analyst-fast-2026-07-08t02-44-44z.fbe3c2c3da579fd1","runId":"run.initial-claims-week-2026-07-04.2026-07-08T02-44-44Z.initial-claims-week-2026-07-04-thesis-analyst-fast-2026-07-08t02-44-44z.fbe3c2c3da579fd1","predictionId":"initial-claims-week-2026-07-04","specId":"spec.initial-claims-week-2026-07-04","runLabel":"Fast rollout 3 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool result: The DOL table shows Initial Claims (SA) 215,000 for June 27, 216,000 for June 20, 227,000 for June 13, and prior-year comparable 231,000; the 4-week moving average is 222,000.","Reference class base rate: recent DOL seasonally adjusted weekly claims sit in the low-200-thousand range, with the latest four revised or advance levels 230, 227, 216, and 215 thousand. That favors persistence around 215 to 222 rather than a break above 230 unless the holiday week produces a seasonal-adjustment miss."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Tool result: The DOL OUI archive says the UI Weekly Claims News Release is published Thursday morning at 8:30 AM EST, with listed 2026 exception Wednesday November 25, 2026; July 9, 2026 is therefore the official Thursday release date for week ending July 4, 2026.","Tool call: Fetched the DOL newsroom release list for nearby official release snippets."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this is the DOL ETA advance seasonally adjusted initial claims series for the week ending July 4, 2026, reported in thousands on the first UI Weekly Claims release. The variant is seasonally adjusted initial claims, not NSA claims, continuing claims, or the 4-week average.","Tool call: Checked the DOL OUI weekly claims archive publication schedule for the release date rule."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 26, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior uses the latest official SA first/revised level of 215 thousand and a recent-reference-class center between latest 215 and 4-week average 222; adjustment components are +1 thousand for mean reversion toward the 4-week average, +0 for labor-market momentum after offsetting the three-week decline, and +0 for holiday effects after seasonal adjustment, giving point 216. For interval width, I used the DOL table's 53 successive weekly SA changes from June 2025 through June 2026; sigma = 10.42 thousand, so 1.28*sigma = 13.34 thousand, rounded to a 13-thousand half-width. Thus 216 - 13 = 203 and 216 + 13 = 229.","Counter-consideration: upside risk is a holiday-week seasonal adjustment miss or a fresh layoff wave lifting claims above 229 thousand; downside risk is continued normalization after the June bump or fewer auto-related layoffs, which would land below 203 thousand. Outside the interval would most likely require a one-week seasonal-factor surprise rather than a gradual labor-market signal."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, and mechanism: level is low but not unusually low relative to spring 2026; momentum is mildly downward after the June peak, while the 4-week average at 222 is above the latest print. The week includes Independence Day, so seasonal factors and employer shutdown timing add noise, but the target is SA and should remove most regular holiday seasonality.","Prior/update/interval: persistence prior uses the latest official SA first/revised level of 215 thousand and a recent-reference-class center between latest 215 and 4-week average 222; adjustment components are +1 thousand for mean reversion toward the 4-week average, +0 for labor-market momentum after offsetting the three-week decline, and +0 for holiday effects after seasonal adjustment, giving point 216. For interval width, I used the DOL table's 53 successive weekly SA changes from June 2025 through June 2026; sigma = 10.42 thousand, so 1.28*sigma = 13.34 thousand, rounded to a 13-thousand half-width. Thus 216 - 13 = 203 and 216 + 13 = 229."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, and mechanism: level is low but not unusually low relative to spring 2026; momentum is mildly downward after the June peak, while the 4-week average at 222 is above the latest print. The week includes Independence Day, so seasonal factors and employer shutdown timing add noise, but the target is SA and should remove most regular holiday seasonality.","Prior/update/interval: persistence prior uses the latest official SA first/revised level of 215 thousand and a recent-reference-class center between latest 215 and 4-week average 222; adjustment components are +1 thousand for mean reversion toward the 4-week average, +0 for labor-market momentum after offsetting the three-week decline, and +0 for holiday effects after seasonal adjustment, giving point 216. For interval width, I used the DOL table's 53 successive weekly SA changes from June 2025 through June 2026; sigma = 10.42 thousand, so 1.28*sigma = 13.34 thousand, rounded to a 13-thousand half-width. Thus 216 - 13 = 203 and 216 + 13 = 229."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for US initial claims, week ending July 4 2026","Prior/update/interval: persistence prior uses the latest official SA first/revised level of 215 thousand and a recent-reference-class center between latest 215 and 4-week average 222; adjustment components are +1 thousand for mean reversion toward the 4-week average, +0 for labor-market momentum after offsetting the three-week decline, and +0 for holiday effects after seasonal adjustment, giving point 216. For interval width, I used the DOL table's 53 successive weekly SA changes from June 2025 through June 2026; sigma = 10.42 thousand, so 1.28*sigma = 13.34 thousand, rounded to a 13-thousand half-width. Thus 216 - 13 = 203 and 216 + 13 = 229."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: initial-claims-week-2026-07-04\nrunLabel: Fast rollout 3 of 3\nresolutionDate: 2026-07-09\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.initial-claims-week-2026-07-04.2026-07-08T02-44-47Z.initial-claims-week-2026-07-04-thesis-analyst-ladder-2026-07-08t02-44-47z.e9f63f4e122e72bf","runId":"run.initial-claims-week-2026-07-04.2026-07-08T02-44-47Z.initial-claims-week-2026-07-04-thesis-analyst-ladder-2026-07-08t02-44-47z.e9f63f4e122e72bf","predictionId":"initial-claims-week-2026-07-04","specId":"spec.initial-claims-week-2026-07-04","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool call: Read DOL historical SA claims table in the same weekly claims PDF","Reference class and base rate: for a one-week-ahead SA initial-claims print, the most relevant reference class is the DOL weekly SA history in the current release table. Over the fetched 54 weekly values from June 21, 2025 through June 27, 2026, levels mostly sit around 200k-236k, with the latest four weeks 230k, 227k, 216k, and 215k and the latest 4-week average at 222k. The base rate is therefore a near-flat next print around the latest level to recent average, before holiday-week and noise adjustments."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Tool call: Opened DOL UI Weekly Claims Data page at https://oui.doleta.gov/unemploy/claims.asp to confirm the current official data surface","Tool result: Fetched page metadata: Unemployment Insurance Weekly Claims Data page updated July 7, 2026; page describes initial claims as measuring emerging unemployment and continued weeks claimed as the number of persons claiming unemployment benefits."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: the target is the DOL Unemployment Insurance Weekly Claims advance seasonally adjusted Initial Claims figure for regular state programs, in thousands, for the week ending July 4, 2026, first print only. The variant is seasonally adjusted, not NSA, and all anchors below use the same SA initial-claims variant unless explicitly described as release-schedule context.","Tool call: Opened current DOL UI Weekly Claims news release PDF at https://www.dol.gov/ui/data.pdf"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 27, distribution present, forecast step count 1.","evidence":["Level, momentum, one-off, and policy mechanisms: level anchors at 215k latest and 222k four-week average; momentum is slightly down over the last two weeks, from 227k to 216k to 215k; one-off risk is elevated because the target week includes the July 4 holiday and seasonal factors can be imperfect; policy mechanisms do not point to an abrupt claims regime change by this release.","Prior/update/interval: persistence prior model starts from latest SA initial claims of 215k with the 4-week-average anchor at 222k and comparable 2025 early-July value of 228k; historical sample is the fetched DOL SA weekly table from June 21, 2025 through June 27, 2026. Adjustment components: +2k toward the recent average, -1k for short-term downward momentum, +1k for early-July seasonal-noise skew, giving a center near 217k. From successive weekly changes in the fetched table, sample sigma = 10.4 thousand, so 1.28*sigma = 13.3 thousand. A symmetric 80% interval around 217k would be about 204k to 230k; the ladder-implied 80% bounds are 204k to 231k, essentially the same width and not widened beyond the realized-dispersion reference."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and policy mechanisms: level anchors at 215k latest and 222k four-week average; momentum is slightly down over the last two weeks, from 227k to 216k to 215k; one-off risk is elevated because the target week includes the July 4 holiday and seasonal factors can be imperfect; policy mechanisms do not point to an abrupt claims regime change by this release.","Prior/update/interval: persistence prior model starts from latest SA initial claims of 215k with the 4-week-average anchor at 222k and comparable 2025 early-July value of 228k; historical sample is the fetched DOL SA weekly table from June 21, 2025 through June 27, 2026. Adjustment components: +2k toward the recent average, -1k for short-term downward momentum, +1k for early-July seasonal-noise skew, giving a center near 217k. From successive weekly changes in the fetched table, sample sigma = 10.4 thousand, so 1.28*sigma = 13.3 thousand. A symmetric 80% interval around 217k would be about 204k to 230k; the ladder-implied 80% bounds are 204k to 231k, essentially the same width and not widened beyond the realized-dispersion reference."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, one-off, and policy mechanisms: level anchors at 215k latest and 222k four-week average; momentum is slightly down over the last two weeks, from 227k to 216k to 215k; one-off risk is elevated because the target week includes the July 4 holiday and seasonal factors can be imperfect; policy mechanisms do not point to an abrupt claims regime change by this release.","Counter-considerations: upside risk is a rebound in filings after holiday timing or state processing backlogs, especially if the latest 215k print understated the run rate; that would land above the interval if the print exceeds 231k. Downside risk is another unusually clean SA print with broad state declines or front-loaded holiday processing before the reference week, which would land below the interval if the print is under 204k. Outside the interval is most likely from seasonal-adjustment error around the July 4 week rather than from a true labor-market break."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for DOL seasonally adjusted initial claims, week ending July 4, 2026","Level, momentum, one-off, and policy mechanisms: level anchors at 215k latest and 222k four-week average; momentum is slightly down over the last two weeks, from 227k to 216k to 215k; one-off risk is elevated because the target week includes the July 4 holiday and seasonal factors can be imperfect; policy mechanisms do not point to an abrupt claims regime change by this release."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: initial-claims-week-2026-07-04\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-07-09\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.initial-claims-week-2026-07-04.2026-07-08T03-03-42Z.initial-claims-week-2026-07-04-thesis-analyst-median3-2026-07-08t03-03-42z.8e667617b8ac8195","runId":"run.initial-claims-week-2026-07-04.2026-07-08T03-03-42Z.initial-claims-week-2026-07-04-thesis-analyst-median3-2026-07-08t03-03-42z.8e667617b8ac8195","predictionId":"initial-claims-week-2026-07-04","specId":"spec.initial-claims-week-2026-07-04","runLabel":"Median of 3 rollouts","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 5 historical point(s) and implicit outside-view language.","evidence":["Median-of-3 rollout ensemble","Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-08T02:44:18Z, 2026-07-08T02:44:20Z, 2026-07-08T02:44:44Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Median CDF quantiles: q10 = 203.0, q50 = 218.0, q90 = 232.0. Constituent points [218, 219, 216] with 80% widths [28, 32, 26]; the median interval inherits the central rollout mass rather than averaging tails."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 29, distribution present, forecast step count 1.","evidence":["Median CDF quantiles: q10 = 203.0, q50 = 218.0, q90 = 232.0. Constituent points [218, 219, 216] with 80% widths [28, 32, 26]; the median interval inherits the central rollout mass rather than averaging tails.","Forecast: point 218, 80% interval [203, 232]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-08T02:44:18Z, 2026-07-08T02:44:20Z, 2026-07-08T02:44:44Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-08T02:44:18Z, 2026-07-08T02:44:20Z, 2026-07-08T02:44:44Z. Drivers and resolver fields mirror the rollout closest to the median.","Tool result: {rollout_points: [218, 219, 216], rollout_widths: [28, 32, 26], q10: 203.0, q50: 218.0, q90: 232.0}"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: initial-claims-week-2026-07-04\nrunLabel: Median of 3 rollouts\nresolutionDate: 2026-07-09\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-ei-regular-beneficiaries-may-2026.2026-07-04T19-34-15Z.7a8488c7e851fe66","runId":"run.canada-ei-regular-beneficiaries-may-2026.2026-07-04T19-34-15Z.7a8488c7e851fe66","predictionId":"canada-ei-regular-beneficiaries-may-2026","specId":"spec.canada-ei-regular-beneficiaries-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: recent official EI prints and cited levels put the series around 544 to 569 thousand, with first-print monthly moves of roughly -8.7, +2.3, and -3.6 thousand from January through April. A persistence prior from the April level therefore starts near 544 thousand, with a mild downward drift.","Prior/update/interval: prior model is latest-value persistence with a damped recent-change base rate, using official-source recent sample January 2026 about 554.4, February 2026 about 545.7, March 2026 548.0, April 2026 544.44, and November 2025 peak 569.0 thousand. The update applies -3.3 thousand for recent EI drift and an additional -3.1 thousand for the May LFS upside surprise, producing 538.0. The 80% interval uses recent realized first-print monthly-change dispersion plus extra width for EI administrative lag and province/industry mix, yielding asymmetric bounds of 520.0 to 557.0 thousand."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The target is Statistics Canada's first official May 2026 Canada count of regular Employment Insurance beneficiaries, seasonally adjusted, in table 14-10-0011-01 and the corresponding The Daily notice. I resolve in thousands and ignore later revisions.","Base rate/reference class: recent official EI prints and cited levels put the series around 544 to 569 thousand, with first-print monthly moves of roughly -8.7, +2.3, and -3.6 thousand from January through April. A persistence prior from the April level therefore starts near 544 thousand, with a mild downward drift."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Canada regular EI beneficiaries, May 2026 first-print forecast","The target is Statistics Canada's first official May 2026 Canada count of regular Employment Insurance beneficiaries, seasonally adjusted, in table 14-10-0011-01 and the corresponding The Daily notice. I resolve in thousands and ignore later revisions."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 37, distribution present, forecast step count 1.","evidence":["Prior/update/interval: prior model is latest-value persistence with a damped recent-change base rate, using official-source recent sample January 2026 about 554.4, February 2026 about 545.7, March 2026 548.0, April 2026 544.44, and November 2025 peak 569.0 thousand. The update applies -3.3 thousand for recent EI drift and an additional -3.1 thousand for the May LFS upside surprise, producing 538.0. The 80% interval uses recent realized first-print monthly-change dispersion plus extra width for EI administrative lag and province/industry mix, yielding asymmetric bounds of 520.0 to 557.0 thousand.","Counter-consideration: the strong May employment report may not translate one-for-one into lower EI receipt if claims from earlier layoffs are still flowing through or if benefit exhaustion is slower than usual; conversely, a broad job-finding improvement could push the count below the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level and momentum: April already declined to 544.44 thousand after March's 548 thousand. The May LFS improvement is a real downside signal for EI beneficiaries, but EI receipt is administrative and can lag job-finding, eligibility, and benefit-exhaustion timing."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level and momentum: April already declined to 544.44 thousand after March's 548 thousand. The May LFS improvement is a real downside signal for EI beneficiaries, but EI receipt is administrative and can lag job-finding, eligibility, and benefit-exhaustion timing.","One-off and policy mechanisms: the StatCan EI release notes administrative and EI Act/procedure effects can affect the series, but I found no specific May 2026 policy change in the checked official release context. The main May-specific adjustment is stronger employment and lower unemployment."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Canada regular EI beneficiaries, May 2026 first-print forecast","Tool result: The May 2026 LFS reports employment of 21,122,000, employment up 88,000, unemployment rate 6.6%, unemployment rate down 0.3 percentage points, and employment had declined 112,000 over the first 4 months of 2026 before May."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-ei-regular-beneficiaries-may-2026\nrunLabel: Headline\nresolutionDate: 2026-07-23\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-unemployment-rate-june-2026.2026-07-04T21-29-22Z.f24fcced427ad623","runId":"run.australia-unemployment-rate-june-2026.2026-07-04T21-29-22Z.f24fcced427ad623","predictionId":"australia-unemployment-rate-june-2026","specId":"spec.australia-unemployment-rate-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool call: ABS Labour Force historical unemployment-rate table, recent monthly rounded rates, using inspected public Thesis record derived from ABS official sources","Base rate/reference class: recent ABS first prints are sticky on a one-decimal grid. Since early 2024, most month-to-month rounded unemployment-rate changes are 0.0 or 0.1 percentage point, with occasional 0.2 point moves such as Feb 2024 and Apr 2026. The outside view therefore starts from May's 4.4 percent with a central 80 percent band of roughly plus or minus 0.3 point before current-release adjustments."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 2 source-context item(s), activity log present.","evidence":["The target is the ABS Labour Force, Australia first-print seasonally adjusted unemployment rate for reference month June 2026, in percent to one decimal place. The ledger target is retained; the source hint mentioning CPI indicator pages appears inconsistent with the unemployment-rate series, so I used ABS Labour Force sources for evidence and resolver identity.","Tool call: ABS Labour Force latest-release page: release date, next-release schedule, and target identity, using inspected public Thesis record derived from ABS official sources"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Australia June 2026 unemployment-rate first print","The target is the ABS Labour Force, Australia first-print seasonally adjusted unemployment rate for reference month June 2026, in percent to one decimal place. The ledger target is retained; the source hint mentioning CPI indicator pages appears inconsistent with the unemployment-rate series, so I used ABS Labour Force sources for evidence and resolver identity."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.7, distribution present, forecast step count 1.","evidence":["Previous-run update: I inspected the public Thesis run from 2026-07-04T19:42:59Z for the same target; it used the same ABS evidence and produced 4.4 with an 80% interval of 4.1 to 4.8. With no newer official June print available before the verified 2026-07-23 release date, I keep that forecast rather than adding a catalog-derived estimate.","Counter-consideration: the June survey period, 31 May to 13 June, could still catch slower hiring or higher participation, and the ABS modernisation transition runs through April-August 2026. Those factors keep a 4.7 or 4.8 print in the 80 percent upper tail even though the modal rounded print remains 4.4."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Current-release update: level is centered at 4.4 because May's rounded and trend rates both sit at 4.4. Momentum is mildly upward over the quarter because Feb was 4.3, Apr was 4.5, and trend moved from 4.3 to 4.4, but May's employment gain and fall in unemployed people argue against extrapolating a clean rise to 4.6 or higher."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Current-release update: level is centered at 4.4 because May's rounded and trend rates both sit at 4.4. Momentum is mildly upward over the quarter because Feb was 4.3, Apr was 4.5, and trend moved from 4.3 to 4.4, but May's employment gain and fall in unemployed people argue against extrapolating a clean rise to 4.6 or higher.","Upside risk: a renewed participation rise or weaker June employment gain pushes the rounded rate to 4.6-4.8. Downside risk: May's employment strength persists and unemployment falls back toward 4.2-4.3. Outside the interval scenarios are a survey-noise or labour-demand shock producing 4.0 or lower, or a sharp rise in unemployed people producing 4.9 or higher."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Previous-run update: I inspected the public Thesis run from 2026-07-04T19:42:59Z for the same target; it used the same ABS evidence and produced 4.4 with an 80% interval of 4.1 to 4.8. With no newer official June print available before the verified 2026-07-23 release date, I keep that forecast rather than adding a catalog-derived estimate.","Base rate/reference class: recent ABS first prints are sticky on a one-decimal grid. Since early 2024, most month-to-month rounded unemployment-rate changes are 0.0 or 0.1 percentage point, with occasional 0.2 point moves such as Feb 2024 and Apr 2026. The outside view therefore starts from May's 4.4 percent with a central 80 percent band of roughly plus or minus 0.3 point before current-release adjustments."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-unemployment-rate-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-23\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.australia-cpi-annual-rate-june-2026.2026-07-04T21-28-13Z.28f3b424175ae242","runId":"run.australia-cpi-annual-rate-june-2026.2026-07-04T21-28-13Z.28f3b424175ae242","predictionId":"australia-cpi-annual-rate-june-2026","specId":"spec.australia-cpi-annual-rate-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 7 historical point(s) and explicit outside-view language.","evidence":["The resolver is the ABS Consumer Price Index, Australia first release for June 2026, using the All groups CPI annual movement in original terms. This forecast reuses the canonical catalog slug because the target already exists; prior local forecasts were treated only as strategy context, with the forecast anchored on official ABS numbers.","Tool call: Read the ABS May 2026 historical monthly movement table for recent-month and base-month mechanics."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 2 source-context item(s), activity log present.","evidence":["The resolver is the ABS Consumer Price Index, Australia first release for June 2026, using the All groups CPI annual movement in original terms. This forecast reuses the canonical catalog slug because the target already exists; prior local forecasts were treated only as strategy context, with the forecast anchored on official ABS numbers.","Tool call: Opened the ABS Consumer Price Index, Australia latest release page for the current CPI publication and future-release listing."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The resolver is the ABS Consumer Price Index, Australia first release for June 2026, using the All groups CPI annual movement in original terms. This forecast reuses the canonical catalog slug because the target already exists; prior local forecasts were treated only as strategy context, with the forecast anchored on official ABS numbers.","Tool call: Opened the ABS Consumer Price Index, Australia latest release page for the current CPI publication and future-release listing."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.3, distribution present, forecast step count 1.","evidence":["Tool result: Fetched schedule details: first complete Monthly CPI on 26/11/2025 for October 2025, publication on the last Wednesday after the reference month, with listed early releases including February 2026 on 25/03/2026, March 2026 on 29/04/2026, and April 2026 on 27/05/2026.","Prior/update/interval: prior model is latest-value annual CPI persistence with a base-month bridge, using the official monthly sample from June 2025 through May 2026 and latest annual prints of 4.6%, 4.2%, and 4.0%. Adjustment components are +0.4 pp for replacing June 2025's 0.1% base with an assumed roughly 0.5% June 2026 month, +0.1 pp for rebound from May's temporary weakness, and -0.1 pp for trimmed-mean restraint near 3.6%. The 80% interval maps a realized monthly first-print range of about -0.2% to +1.1% for June 2026 through the same bridge, giving final implied bounds of 3.7% to 5.0%."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["The resolver is the ABS Consumer Price Index, Australia first release for June 2026, using the All groups CPI annual movement in original terms. This forecast reuses the canonical catalog slug because the target already exists; prior local forecasts were treated only as strategy context, with the forecast anchored on official ABS numbers.","Level and momentum: May's -0.7% monthly fall pulled the headline annual rate down, while housing and underlying inflation remained firmer. I treat part of the May weakness in transport, recreation, and travel-sensitive categories as more likely to mean-revert than persist fully into June."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: the comparable complete monthly CPI annual readings since late 2025 are clustered around 3.4% to 4.6%, with the latest three prints at 4.6%, 4.2%, and 4.0%. A latest-value prior starts at 4.0%, but replacing June 2025's low 0.1% monthly base with a normal positive June 2026 month points higher.","Counter-consideration and outside-the-interval scenarios: downside risk is another broad monthly fall led by fuel, airfares, or goods discounting, which would land below the interval if the June monthly print is materially below -0.2%. Upside risk is a large electricity, fuel, rents, or travel rebound, which would land above the interval if the June monthly print is materially above 1.1%."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast: ABS All groups CPI annual inflation for June 2026","The resolver is the ABS Consumer Price Index, Australia first release for June 2026, using the All groups CPI annual movement in original terms. This forecast reuses the canonical catalog slug because the target already exists; prior local forecasts were treated only as strategy context, with the forecast anchored on official ABS numbers."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: australia-cpi-annual-rate-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-29\ntraceLineCount: 19\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.euro-area-unemployment-rate-june-2026.2026-07-04T19-23-44Z.df2003dd44fa5014","runId":"run.euro-area-unemployment-rate-june-2026.2026-07-04T19-23-44Z.df2003dd44fa5014","predictionId":"euro-area-unemployment-rate-june-2026","specId":"spec.euro-area-unemployment-rate-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: for a one-month-ahead euro area unemployment forecast rounded to one decimal, persistence is the strongest prior. The recent official unemployment sequence is 6.4, 6.3, 6.2, 6.2 for February through May 2026, with a five-point table median of 6.3 but the latest two months at 6.2.","Prior/update/interval: persistence prior is latest official rounded print 6.2 from the February-May 2026 Eurostat sample {6.4, 6.3, 6.2, 6.2}; update components are level 0.0pp, momentum -0.05pp from falling unemployed persons, inflation/policy +0.00pp to +0.05pp, net rounded to 6.2. Interval method uses realized one-month first-print dispersion at one-decimal precision, widened for macro risk to +/-0.2pp, giving an 80% interval of 6.0 to 6.4."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The target is Eurostat's first official June 2026 euro area seasonally adjusted unemployment rate, total sex and age 15-74, in percent of the labour force. The May 2026 Eurostat unemployment release is dated 2 July 2026 and states the next release is 30 July 2026, so I use 2026-07-30 as the verified resolution date.","Tool result: Fetched euro area rates: May-25 6.3, Feb-26 6.4, Mar-26 6.3, Apr-26 6.2, May-26 6.2; fetched euro area unemployed persons: Feb-26 11223 thousand, Mar-26 11136 thousand, Apr-26 11041 thousand, May-26 10986 thousand."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Euro area unemployment rate, June 2026 first print","The target is Eurostat's first official June 2026 euro area seasonally adjusted unemployment rate, total sex and age 15-74, in percent of the labour force. The May 2026 Eurostat unemployment release is dated 2 July 2026 and states the next release is 30 July 2026, so I use 2026-07-30 as the verified resolution date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.4, distribution present, forecast step count 1.","evidence":["Counter-consideration: unemployment could print 6.3 or 6.4 if earlier weak demand, hiring caution, or country-level softness shows up before the June reference month closes. It could fall to 6.0 or 6.1 if the May headcount decline continues and large labour markets such as Italy or Germany improve. Outside the interval, a jump above 6.4 would likely need a broad sudden deterioration or major revision; a fall below 6.0 would require an unusually large euro-area employment surprise.","Prior/update/interval: persistence prior is latest official rounded print 6.2 from the February-May 2026 Eurostat sample {6.4, 6.3, 6.2, 6.2}; update components are level 0.0pp, momentum -0.05pp from falling unemployed persons, inflation/policy +0.00pp to +0.05pp, net rounded to 6.2. Interval method uses realized one-month first-print dispersion at one-decimal precision, widened for macro risk to +/-0.2pp, giving an 80% interval of 6.0 to 6.4."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level and momentum: the May level of 6.2% is already below the March-February readings, and the euro area unemployed headcount fell by 55 thousand from April to May. That makes 6.2 the best rounded central forecast for June rather than reverting fully to 6.3.","Prior/update/interval: persistence prior is latest official rounded print 6.2 from the February-May 2026 Eurostat sample {6.4, 6.3, 6.2, 6.2}; update components are level 0.0pp, momentum -0.05pp from falling unemployed persons, inflation/policy +0.00pp to +0.05pp, net rounded to 6.2. Interval method uses realized one-month first-print dispersion at one-decimal precision, widened for macro risk to +/-0.2pp, giving an 80% interval of 6.0 to 6.4."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: for a one-month-ahead euro area unemployment forecast rounded to one decimal, persistence is the strongest prior. The recent official unemployment sequence is 6.4, 6.3, 6.2, 6.2 for February through May 2026, with a five-point table median of 6.3 but the latest two months at 6.2.","Prior/update/interval: persistence prior is latest official rounded print 6.2 from the February-May 2026 Eurostat sample {6.4, 6.3, 6.2, 6.2}; update components are level 0.0pp, momentum -0.05pp from falling unemployed persons, inflation/policy +0.00pp to +0.05pp, net rounded to 6.2. Interval method uses realized one-month first-print dispersion at one-decimal precision, widened for macro risk to +/-0.2pp, giving an 80% interval of 6.0 to 6.4."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Base rate/reference class: for a one-month-ahead euro area unemployment forecast rounded to one decimal, persistence is the strongest prior. The recent official unemployment sequence is 6.4, 6.3, 6.2, 6.2 for February through May 2026, with a five-point table median of 6.3 but the latest two months at 6.2.","Level and momentum: the May level of 6.2% is already below the March-February readings, and the euro area unemployed headcount fell by 55 thousand from April to May. That makes 6.2 the best rounded central forecast for June rather than reverting fully to 6.3."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: euro-area-unemployment-rate-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-30\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-core-pce-mom-june-2026.2026-07-04T21-21-04Z.d3a70d95af7e3c86","runId":"run.us-core-pce-mom-june-2026.2026-07-04T21-21-04Z.d3a70d95af7e3c86","predictionId":"us-core-pce-mom-june-2026","specId":"spec.us-core-pce-mom-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["The target is the first BEA Personal Income and Outlays print for June 2026: the PCE price index excluding food and energy, seasonally adjusted percent change from the prior month. The BEA release and data page are the resolver; later revised tables do not change this first-print target.","Base-rate/reference-class anchor: the official BEA monthly core PCE prints available for January through May 2026 are 0.4, 0.4, 0.3, 0.2, and 0.3. Their simple mean is 0.32, while latest-print persistence is 0.30, so the base rate centers just above 0.30 before June-specific adjustments."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 7 source-context item(s), activity log present.","evidence":["Tool result: Fetched official schedule: Personal Income and Outlays, June 2026 is listed for July 30, 2026 at 8:30 AM; Personal Income and Outlays, July 2026 is listed for August 26, 2026 at 8:30 AM.","Base-rate/reference-class anchor: the official BEA monthly core PCE prints available for January through May 2026 are 0.4, 0.4, 0.3, 0.2, and 0.3. Their simple mean is 0.32, while latest-print persistence is 0.30, so the base rate centers just above 0.30 before June-specific adjustments."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the first BEA Personal Income and Outlays print for June 2026: the PCE price index excluding food and energy, seasonally adjusted percent change from the prior month. The BEA release and data page are the resolver; later revised tables do not change this first-print target.","Tool call: BEA 2026 release schedule for Personal Income and Outlays, June 2026"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.31, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = 0.30 from the May 2026 BEA first print; historical sample = Jan-May BEA monthly core PCE values 0.4, 0.4, 0.3, 0.2, 0.3 with mean 0.32; adjustment components = +0.02 for the elevated 3.4% year-over-year core level and still-firm services inflation, -0.01 for the April-May stabilization and no June source-data confirmation yet; point = 0.31. Interval method = realized recent first-print dispersion plus release-rounding risk: recent values span 0.2 to 0.4, so an 80% band of about +/-0.15 around 0.31 gives 0.16 to 0.47.","Counter-consideration and tails: downside risk outside the interval would require broad June goods deflation, softer medical or financial services, and shelter materially below recent readings, pushing core PCE below 0.16. Upside risk outside the interval would require energy pass-through plus a transportation-services or portfolio-management jump, pushing core PCE above 0.47. The central case is persistence near 0.3 with modest upside pressure."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and policy-mechanism split: the elevated 3.4% year-over-year core rate argues against a rapid return to benign 0.1 to 0.2 monthly prints. Recent monthly momentum is stable near 0.3. Food and energy are excluded, but energy-related pass-through can still appear in transportation services and input-sensitive categories; weaker goods or services categories are the main offset.","Counter-consideration and tails: downside risk outside the interval would require broad June goods deflation, softer medical or financial services, and shelter materially below recent readings, pushing core PCE below 0.16. Upside risk outside the interval would require energy pass-through plus a transportation-services or portfolio-management jump, pushing core PCE above 0.47. The central case is persistence near 0.3 with modest upside pressure."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, one-off, and policy-mechanism split: the elevated 3.4% year-over-year core rate argues against a rapid return to benign 0.1 to 0.2 monthly prints. Recent monthly momentum is stable near 0.3. Food and energy are excluded, but energy-related pass-through can still appear in transportation services and input-sensitive categories; weaker goods or services categories are the main offset.","Prior/update/interval: persistence prior = 0.30 from the May 2026 BEA first print; historical sample = Jan-May BEA monthly core PCE values 0.4, 0.4, 0.3, 0.2, 0.3 with mean 0.32; adjustment components = +0.02 for the elevated 3.4% year-over-year core level and still-firm services inflation, -0.01 for the April-May stabilization and no June source-data confirmation yet; point = 0.31. Interval method = realized recent first-print dispersion plus release-rounding risk: recent values span 0.2 to 0.4, so an 80% band of about +/-0.15 around 0.31 gives 0.16 to 0.47."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast June 2026 US core PCE monthly inflation","Prior/update/interval: persistence prior = 0.30 from the May 2026 BEA first print; historical sample = Jan-May BEA monthly core PCE values 0.4, 0.4, 0.3, 0.2, 0.3 with mean 0.32; adjustment components = +0.02 for the elevated 3.4% year-over-year core level and still-firm services inflation, -0.01 for the April-May stabilization and no June source-data confirmation yet; point = 0.31. Interval method = realized recent first-print dispersion plus release-rounding risk: recent values span 0.2 to 0.4, so an 80% band of about +/-0.15 around 0.31 gives 0.16 to 0.47."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-core-pce-mom-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-30\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.euro-flash-hicp-july-2026.2026-07-04T21-26-35Z.e3d1c700c284a15d","runId":"run.euro-flash-hicp-july-2026.2026-07-04T21-26-35Z.e3d1c700c284a15d","predictionId":"euro-flash-hicp-july-2026","specId":"spec.euro-flash-hicp-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: recent official first-print monthly changes in the annual rate were +0.2, +0.7, +0.4, +0.2, and -0.4 percentage points from January through June 2026. A persistence base rate would center July near 2.8, while the negative June monthly rate and broad component easing point below persistence.","Prior/update/interval: prior model is persistence plus recent-change adjustment using the January-June 2026 official first-print reference class, anchored on June's 2.8 percent. Updates are -0.15 pp for the -0.1 monthly all-items print, -0.10 pp for broad component deceleration, and +0.05 pp for still-sticky services/core, implying 2.60 before one-decimal publication rounding. The 80 percent interval uses recent first-print change dispersion around 0.4 pp plus a one-month shock allowance, giving 2.1 to 3.1 percent."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The resolver is the first Eurostat Euro indicators flash estimate for euro area all-items HICP annual inflation in July 2026, rounded to one decimal. The target stays tied to the catalog slug and dataPointId; later complete HICP data or revisions should not change resolution.","Tool call: Checked the Eurostat 1 July 2026 Euro indicators flash-estimate release for the latest official headline path and the next-release statement."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is the first Eurostat Euro indicators flash estimate for euro area all-items HICP annual inflation in July 2026, rounded to one decimal. The target stays tied to the catalog slug and dataPointId; later complete HICP data or revisions should not change resolution.","Tool call: Checked the Eurostat 1 July 2026 Euro indicators flash-estimate release for the latest official headline path and the next-release statement."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1, distribution present, forecast step count 1.","evidence":["Level, momentum, one-off, and policy mechanisms: the level is still above 2 percent, but June's momentum weakened in headline, energy, services, food, and core. Energy remains the main upside risk because 8.7 percent is high, while services at 3.2 percent makes a collapse below the low-2s less likely.","Prior/update/interval: prior model is persistence plus recent-change adjustment using the January-June 2026 official first-print reference class, anchored on June's 2.8 percent. Updates are -0.15 pp for the -0.1 monthly all-items print, -0.10 pp for broad component deceleration, and +0.05 pp for still-sticky services/core, implying 2.60 before one-decimal publication rounding. The 80 percent interval uses recent first-print change dispersion around 0.4 pp plus a one-month shock allowance, giving 2.1 to 3.1 percent."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and policy mechanisms: the level is still above 2 percent, but June's momentum weakened in headline, energy, services, food, and core. Energy remains the main upside risk because 8.7 percent is high, while services at 3.2 percent makes a collapse below the low-2s less likely.","Counter-consideration: upside risk outside the interval would come from renewed energy-price pressure, hot travel-services seasonality, or large-country national flash prints all surprising high enough to put the euro-area rate above 3.1 percent. Downside risk outside the interval would require stronger energy base effects plus weaker goods or food prices pulling the first print below 2.1 percent."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, one-off, and policy mechanisms: the level is still above 2 percent, but June's momentum weakened in headline, energy, services, food, and core. Energy remains the main upside risk because 8.7 percent is high, while services at 3.2 percent makes a collapse below the low-2s less likely.","Counter-consideration: upside risk outside the interval would come from renewed energy-price pressure, hot travel-services seasonality, or large-country national flash prints all surprising high enough to put the euro-area rate above 3.1 percent. Downside risk outside the interval would require stronger energy base effects plus weaker goods or food prices pulling the first print below 2.1 percent."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Euro area July 2026 flash HICP forecast","The resolver is the first Eurostat Euro indicators flash estimate for euro area all-items HICP annual inflation in July 2026, rounded to one decimal. The target stays tied to the catalog slug and dataPointId; later complete HICP data or revisions should not change resolution."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: euro-flash-hicp-july-2026\nrunLabel: Headline\nresolutionDate: 2026-07-31\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.canada-monthly-gdp-growth-may-2026.2026-07-04T21-32-02Z.6498de0f976fe845","runId":"run.canada-monthly-gdp-growth-may-2026.2026-07-04T21-32-02Z.6498de0f976fe845","predictionId":"canada-monthly-gdp-growth-may-2026","specId":"spec.canada-monthly-gdp-growth-may-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the recent official first-print reference class for the exact monthly all-industries GDP-by-industry series is low positive growth. The December-April prints of 0.2, 0.1, 0.2, -0.1, and 0.5 average 0.18 percent, while the median is 0.2 percent; including the official May advance estimate pulls the center toward 0.1 percent.","Prior/update/interval: prior model is latest-advance/persistence blended with the recent official first-print reference class from December 2025 through April 2026. I start from the 0.1 May advance estimate, add +0.05 percentage point for finance and real estate support, subtract -0.05 for wholesale/agriculture weakness and April payback, and keep the rounded point at 0.1. The 80% interval method uses realized recent first-print dispersion plus advance-estimate miss risk, widened for one-decimal rounding and sector payback, producing -0.2 to 0.4."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 7 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this targets Statistics Canada's first print for seasonally adjusted real GDP by industry, all industries, at basic prices, month-over-month percent change for May 2026. The target is the official July 31, 2026 May release, not the June 30 advance estimate and not later revised history.","Tool result: Fetched April 2026 official context: real GDP by industry increased 0.5% in April after March -0.1%; goods-producing industries rose 1.2%, services-producing industries rose 0.3%, and 14 of 20 industrial sectors grew."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this targets Statistics Canada's first print for seasonally adjusted real GDP by industry, all industries, at basic prices, month-over-month percent change for May 2026. The target is the official July 31, 2026 May release, not the June 30 advance estimate and not later revised history.","Tool call: Checked Statistics Canada 2026-2027 major economic release dates PDF for Gross domestic product by industry."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.6, distribution present, forecast step count 1.","evidence":["Level, momentum, one-off, and policy mechanisms: the level signal improved sharply in April, but April's 0.5 percent gain had catch-up elements in oil and gas, manufacturing, transportation, and construction. May momentum is still positive but clearly slower in the official advance estimate. The one-off risk is payback after April's rebound. Policy and external mechanisms remain mixed: trade and tariff uncertainty drag on wholesale and goods activity, while finance, real estate, and public-facing services support a modest positive print.","Prior/update/interval: prior model is latest-advance/persistence blended with the recent official first-print reference class from December 2025 through April 2026. I start from the 0.1 May advance estimate, add +0.05 percentage point for finance and real estate support, subtract -0.05 for wholesale/agriculture weakness and April payback, and keep the rounded point at 0.1. The 80% interval method uses realized recent first-print dispersion plus advance-estimate miss risk, widened for one-decimal rounding and sector payback, producing -0.2 to 0.4."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and policy mechanisms: the level signal improved sharply in April, but April's 0.5 percent gain had catch-up elements in oil and gas, manufacturing, transportation, and construction. May momentum is still positive but clearly slower in the official advance estimate. The one-off risk is payback after April's rebound. Policy and external mechanisms remain mixed: trade and tariff uncertainty drag on wholesale and goods activity, while finance, real estate, and public-facing services support a modest positive print."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, one-off, and policy mechanisms: the level signal improved sharply in April, but April's 0.5 percent gain had catch-up elements in oil and gas, manufacturing, transportation, and construction. May momentum is still positive but clearly slower in the official advance estimate. The one-off risk is payback after April's rebound. Policy and external mechanisms remain mixed: trade and tariff uncertainty drag on wholesale and goods activity, while finance, real estate, and public-facing services support a modest positive print.","Prior/update/interval: prior model is latest-advance/persistence blended with the recent official first-print reference class from December 2025 through April 2026. I start from the 0.1 May advance estimate, add +0.05 percentage point for finance and real estate support, subtract -0.05 for wholesale/agriculture weakness and April payback, and keep the rounded point at 0.1. The 80% interval method uses realized recent first-print dispersion plus advance-estimate miss risk, widened for one-decimal rounding and sector payback, producing -0.2 to 0.4."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for Canada May 2026 real GDP by industry monthly growth","Prior/update/interval: prior model is latest-advance/persistence blended with the recent official first-print reference class from December 2025 through April 2026. I start from the 0.1 May advance estimate, add +0.05 percentage point for finance and real estate support, subtract -0.05 for wholesale/agriculture weakness and April payback, and keep the rounded point at 0.1. The 80% interval method uses realized recent first-print dispersion plus advance-estimate miss risk, widened for one-decimal rounding and sector payback, producing -0.2 to 0.4."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: canada-monthly-gdp-growth-may-2026\nrunLabel: Headline\nresolutionDate: 2026-07-31\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.japan-tokyo-cpi-annual-rate-july-2026-prelim.2026-07-05T13-48-51Z.deb0362cac173dda","runId":"run.japan-tokyo-cpi-annual-rate-july-2026-prelim.2026-07-05T13-48-51Z.deb0362cac173dda","predictionId":"japan-tokyo-cpi-annual-rate-july-2026-prelim","specId":"spec.japan-tokyo-cpi-annual-rate-july-2026-prelim","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool result: Fetched official release schedule last updated 23 January 2026: Japan June 2026 CPI releases July 24, 2026; Ku-area of Tokyo July 2026 preliminary releases July 31, 2026; August 2026 line notes revision to 2025-base Consumer Price Index.","Tool call: Checked the Statistics Bureau CPI landing and latest-results pages for official target source and base-revision context."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Tool result: Fetched official release schedule last updated 23 January 2026: Japan June 2026 CPI releases July 24, 2026; Ku-area of Tokyo July 2026 preliminary releases July 31, 2026; August 2026 line notes revision to 2025-base Consumer Price Index.","Tool call: Checked the Statistics Bureau CPI landing and latest-results pages for official target source and base-revision context."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is the first preliminary Statistics Bureau of Japan/e-Stat Ku-area of Tokyo CPI print for July 2026, all items, change over the year, rounded to one decimal percent. This uses the same all-items, non-seasonally-adjusted, change-over-year variant for the target, anchors, and history.","Tool call: Checked the Statistics Bureau of Japan CPI schedule page for the July 2026 Ku-area of Tokyo preliminary release date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.4, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior from recent official Tokyo all-items YoY prints uses Feb-Jun 2026 values 2.9, 2.9, 3.5, 3.4, 3.4; latest-value prior = 3.4 and five-month average = 3.22, so I keep the point at 3.4 after a small food/services upside offset to flat momentum. Successive changes are 0.0, +0.6, -0.1, 0.0, so sample sigma = 0.32 percentage point; 1.28*sigma = 0.41. I widen to a 0.7-point half-width because headline all-items CPI has fresh-food and energy/subsidy risk beyond the tiny five-print sample, giving 2.7 to 4.1.","Counter-consideration and scenarios: downside risk outside the interval would be a sharp energy-subsidy or gasoline-base-effect drop plus softer fresh food, pushing July below 2.7. Upside risk outside the interval would be renewed rice/food acceleration or utility pass-through pushing the first print above 4.1. The central case is persistence near 3.4."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, and mechanism split: the level is elevated by Japan's pre-2022 standards, but momentum is roughly flat after April-June held near 3.4 to 3.5. Food and rice inflation are the main upside mechanism, while energy, gasoline, and utility subsidy/base effects are the main downside mechanism.","Prior/update/interval: persistence prior from recent official Tokyo all-items YoY prints uses Feb-Jun 2026 values 2.9, 2.9, 3.5, 3.4, 3.4; latest-value prior = 3.4 and five-month average = 3.22, so I keep the point at 3.4 after a small food/services upside offset to flat momentum. Successive changes are 0.0, +0.6, -0.1, 0.0, so sample sigma = 0.32 percentage point; 1.28*sigma = 0.41. I widen to a 0.7-point half-width because headline all-items CPI has fresh-food and energy/subsidy risk beyond the tiny five-print sample, giving 2.7 to 4.1."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, and mechanism split: the level is elevated by Japan's pre-2022 standards, but momentum is roughly flat after April-June held near 3.4 to 3.5. Food and rice inflation are the main upside mechanism, while energy, gasoline, and utility subsidy/base effects are the main downside mechanism.","Prior/update/interval: persistence prior from recent official Tokyo all-items YoY prints uses Feb-Jun 2026 values 2.9, 2.9, 3.5, 3.4, 3.4; latest-value prior = 3.4 and five-month average = 3.22, so I keep the point at 3.4 after a small food/services upside offset to flat momentum. Successive changes are 0.0, +0.6, -0.1, 0.0, so sample sigma = 0.32 percentage point; 1.28*sigma = 0.41. I widen to a 0.7-point half-width because headline all-items CPI has fresh-food and energy/subsidy risk beyond the tiny five-print sample, giving 2.7 to 4.1."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast Tokyo all-items CPI YoY for July 2026","Prior/update/interval: persistence prior from recent official Tokyo all-items YoY prints uses Feb-Jun 2026 values 2.9, 2.9, 3.5, 3.4, 3.4; latest-value prior = 3.4 and five-month average = 3.22, so I keep the point at 3.4 after a small food/services upside offset to flat momentum. Successive changes are 0.0, +0.6, -0.1, 0.0, so sample sigma = 0.32 percentage point; 1.28*sigma = 0.41. I widen to a 0.7-point half-width because headline all-items CPI has fresh-food and energy/subsidy risk beyond the tiny five-print sample, giving 2.7 to 4.1."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: japan-tokyo-cpi-annual-rate-july-2026-prelim\nrunLabel: Headline\nresolutionDate: 2026-07-31\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.jolts-openings-june-2026.2026-07-04T21-18-39Z.e9b7a1465dc3b96a","runId":"run.jolts-openings-june-2026.2026-07-04T21-18-39Z.e9b7a1465dc3b96a","predictionId":"jolts-openings-june-2026","specId":"spec.jolts-openings-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base-rate/reference-class anchor: for a one-month-ahead JOLTS openings first print, persistence around the latest official openings level is the base rate because monthly openings changes are noisy and weak payroll data often affects hires before posted vacancies.","Prior/update/interval: persistence prior uses latest official May 2026 openings of 7.594 million; adjustment components are -0.14 million for weak June payrolls/revisions, -0.01 million for lower May hires, and +0.01 million for still-low unemployment, giving 7.45 million after rounding. Interval method uses realized JOLTS first-print monthly dispersion around 0.35 to 0.40 million, widened to about +/-0.60 million for survey noise and the elevated May level, implying 6.85 to 8.05 million."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: the target is the first BLS-published seasonally adjusted total nonfarm job openings level for June 2026 in the JOLTS release, expressed in millions. The first print governs; later revisions are excluded.","Tool call: Checked the BLS JOLTS release calendar for the June 2026 reference month."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: the target is the first BLS-published seasonally adjusted total nonfarm job openings level for June 2026 in the JOLTS release, expressed in millions. The first print governs; later revisions are excluded.","Tool call: Checked the BLS JOLTS release calendar for the June 2026 reference month."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.2, distribution present, forecast step count 1.","evidence":["Tool call: Read BLS JOLTS industry details from Table A to identify sector concentration in the latest openings print.","Prior/update/interval: persistence prior uses latest official May 2026 openings of 7.594 million; adjustment components are -0.14 million for weak June payrolls/revisions, -0.01 million for lower May hires, and +0.01 million for still-low unemployment, giving 7.45 million after rounding. Interval method uses realized JOLTS first-print monthly dispersion around 0.35 to 0.40 million, widened to about +/-0.60 million for survey noise and the elevated May level, implying 6.85 to 8.05 million."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base-rate/reference-class anchor: for a one-month-ahead JOLTS openings first print, persistence around the latest official openings level is the base rate because monthly openings changes are noisy and weak payroll data often affects hires before posted vacancies.","Level and momentum split: May's 7.594 million was essentially flat versus April's 7.585 million and above May 2025's 7.310 million, so the level signal starts high. Momentum is not strongly positive because hires slipped from 5.215 million in April to 5.170 million in May."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-consideration and falsification: upside risk is that employers keep vacancies posted even while slowing fills, which could keep openings above 7.9 million. Downside risk is that the weak June payroll print reflects a broad pullback in postings, pulling openings toward 6.9 million. A shock or survey-noise print below 6.85 million or above 8.05 million would land outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["JOLTS June 2026 job openings forecast","Current-release adjustment: June payroll growth of +57,000 and -74,000 in April-May revisions point to softer labor demand, so I subtract about 0.14 to 0.15 million from pure May persistence. The 4.2 percent unemployment rate and 7.1 million unemployed count keep the adjustment moderate rather than recession-sized."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: jolts-openings-june-2026\nrunLabel: Headline\nresolutionDate: 2026-08-04\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.unemployment-rate-july-2026.2026-07-04T19-09-56Z.bc2560c9f3dbbe73","runId":"run.unemployment-rate-july-2026.2026-07-04T19-09-56Z.bc2560c9f3dbbe73","predictionId":"unemployment-rate-july-2026","specId":"spec.unemployment-rate-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base-rate/reference class: the immediate official BLS reference class is month-ahead rounded U-3 from recent CPS first prints. The last five seasonally adjusted readings are 4.4, 4.3, 4.3, 4.3, and 4.2 percent, so a persistence prior is centered a little above the latest 4.2 because June's rounded decline came with a participation drop.","Level, momentum, one-off, and policy mechanisms: the level is low by historical standards but not accelerating lower; payroll momentum weakened sharply in June with only +57,000 jobs; the one-off risk is household-survey and participation noise after a 0.3 percentage point participation-rate drop; there is no direct policy rule that mechanically fixes July U-3 before the CPS survey."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this is the BLS Current Population Survey seasonally adjusted civilian unemployment rate, U-3, for July 2026, as first printed in the Employment Situation release. The ledger target slug unemployment-rate-july-2026 is consistent with a July reference month and August 2026 BLS release date.","Tool call: Opened the BLS Schedule of Releases for the Employment Situation and checked the July 2026 reference-month row."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast for July 2026 U.S. unemployment rate first print","Framing and exact resolver: this is the BLS Current Population Survey seasonally adjusted civilian unemployment rate, U-3, for July 2026, as first printed in the Employment Situation release. The ledger target slug unemployment-rate-july-2026 is consistent with a July reference month and August 2026 BLS release date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.4, distribution present, forecast step count 1.","evidence":["Level, momentum, one-off, and policy mechanisms: the level is low by historical standards but not accelerating lower; payroll momentum weakened sharply in June with only +57,000 jobs; the one-off risk is household-survey and participation noise after a 0.3 percentage point participation-rate drop; there is no direct policy rule that mechanically fixes July U-3 before the CPS survey.","Prior/update/interval: prior model is rounded latest-value persistence with a five-month BLS first-print sample of Feb-Jun 2026 unemployment rates at 4.4, 4.3, 4.3, 4.3, and 4.2. I start at latest 4.2, add +0.05 pp because the June improvement was helped by lower participation, add +0.04 pp for weak June payroll momentum, and add +0.01 pp for mean reversion toward the five-month average near 4.3. The interval method uses recent one-month rounded-rate dispersion, where typical moves are 0.0 to 0.1 pp, then widens to +/-0.2 pp for CPS sampling and labor-force participation uncertainty, giving final implied bounds of 4.1 to 4.5 around a 4.3 rounded point."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base-rate/reference class: the immediate official BLS reference class is month-ahead rounded U-3 from recent CPS first prints. The last five seasonally adjusted readings are 4.4, 4.3, 4.3, 4.3, and 4.2 percent, so a persistence prior is centered a little above the latest 4.2 because June's rounded decline came with a participation drop.","Level, momentum, one-off, and policy mechanisms: the level is low by historical standards but not accelerating lower; payroll momentum weakened sharply in June with only +57,000 jobs; the one-off risk is household-survey and participation noise after a 0.3 percentage point participation-rate drop; there is no direct policy rule that mechanically fixes July U-3 before the CPS survey."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, one-off, and policy mechanisms: the level is low by historical standards but not accelerating lower; payroll momentum weakened sharply in June with only +57,000 jobs; the one-off risk is household-survey and participation noise after a 0.3 percentage point participation-rate drop; there is no direct policy rule that mechanically fixes July U-3 before the CPS survey.","Prior/update/interval: prior model is rounded latest-value persistence with a five-month BLS first-print sample of Feb-Jun 2026 unemployment rates at 4.4, 4.3, 4.3, 4.3, and 4.2. I start at latest 4.2, add +0.05 pp because the June improvement was helped by lower participation, add +0.04 pp for weak June payroll momentum, and add +0.01 pp for mean reversion toward the five-month average near 4.3. The interval method uses recent one-month rounded-rate dispersion, where typical moves are 0.0 to 0.1 pp, then widens to +/-0.2 pp for CPS sampling and labor-force participation uncertainty, giving final implied bounds of 4.1 to 4.5 around a 4.3 rounded point."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for July 2026 U.S. unemployment rate first print","Level, momentum, one-off, and policy mechanisms: the level is low by historical standards but not accelerating lower; payroll momentum weakened sharply in June with only +57,000 jobs; the one-off risk is household-survey and participation noise after a 0.3 percentage point participation-rate drop; there is no direct policy rule that mechanically fixes July U-3 before the CPS survey."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: unemployment-rate-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-07\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.nonfarm-payrolls-july-2026.2026-07-04T21-39-07Z.d70fc3c3cb39628e","runId":"run.nonfarm-payrolls-july-2026.2026-07-04T21-39-07Z.d70fc3c3cb39628e","predictionId":"nonfarm-payrolls-july-2026","specId":"spec.nonfarm-payrolls-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool result: The June 2026 release reported total nonfarm payroll employment +57,000, unemployment rate 4.2 percent, unemployed people 7.1 million, prior-12-month average payroll change +36,000, April revised from +179,000 to +148,000, May revised from +172,000 to +129,000, and the July 2026 release scheduled for Aug. 07, 2026.","Base rate/reference class: the recent official first-print reference class from February through June is -92, +178, +115, +172, and +57 thousand, averaging +86 thousand. The latest revised three-month average is about +111 thousand, while the BLS prior-12-month average of +36 thousand argues for keeping the outside-view anchor below the spring pace."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 7 source-context item(s), activity log present.","evidence":["The resolver is the first BLS Employment Situation print for July 2026 total nonfarm payroll employment, seasonally adjusted, measured as the over-the-month change in thousands. Later revisions and benchmark updates do not count.","Tool call: Checked the official BLS Employment Situation release calendar for the July 2026 reference month."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["July 2026 first-print nonfarm payroll forecast","The resolver is the first BLS Employment Situation print for July 2026 total nonfarm payroll employment, seasonally adjusted, measured as the over-the-month change in thousands. Later revisions and benchmark updates do not count."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 300, distribution present, forecast step count 1.","evidence":["Counter-consideration: upside risk is a rebound from June's weak leisure and hospitality seasonal adjustment plus still-low claims, which could put July above 235 thousand. Downside risk is that the June slowdown and negative revisions mark a broader hiring stall, which could push the first print below -65 thousand. A strike, government-counting surprise, or seasonal-adjustment miss would be the most likely outside the interval scenario.","Prior/update/interval: I use a persistence plus short-moving-average model prior built from the February-June first-print sample, then adjust for latest revised momentum, low claims, the June one-off leisure weakness, and the softer 12-month BLS average; the 80% interval is sized from the BLS stated establishment-survey monthly-change sampling uncertainty of roughly +/-122 thousand at 90 percent, widened to +/-150 thousand for first-print and turning-point risk."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Read the current BLS Employment Situation Summary for June 2026 payroll momentum, unemployment, revisions, and the next-release notice.","Tool call: Read the latest official DOL unemployment insurance weekly claims release for layoff pressure near the July survey month."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, one-off, and policy split: the June +57 thousand print and downward revisions point to slower hiring, but claims at 215 thousand and a 1.2 percent insured unemployment rate do not show a layoff shock. June leisure and hospitality employment fell by 61 thousand in the BLS summary, which could partly reverse in July, while no policy mechanism directly forces a large July payroll discontinuity.","Counter-consideration: upside risk is a rebound from June's weak leisure and hospitality seasonal adjustment plus still-low claims, which could put July above 235 thousand. Downside risk is that the June slowdown and negative revisions mark a broader hiring stall, which could push the first print below -65 thousand. A strike, government-counting surprise, or seasonal-adjustment miss would be the most likely outside the interval scenario."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["July 2026 first-print nonfarm payroll forecast","Tool call: Read recent archived BLS Employment Situation releases for first-print payroll reference points."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: nonfarm-payrolls-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-07\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-cpi-u-mom-july-2026.2026-07-04T19-03-43Z.5407416a091f84a3","runId":"run.us-cpi-u-mom-july-2026.2026-07-04T19-03-43Z.5407416a091f84a3","predictionId":"us-cpi-u-mom-july-2026","specId":"spec.us-cpi-u-mom-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool call: BLS April 2026 CPI archive for prior first-print composition","Base-rate/reference-class anchor: the recent official first-print headline sequence is February 0.3, March 0.9, April 0.6, and May 0.5 percent, with the high prints heavily energy-driven. A simple recent median anchor is about 0.55 percent, but that reference class is contaminated by a March-May energy shock."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Forecast July 2026 BLS CPI-U headline monthly first print","The target is BLS CPI-U all items, U.S. city average, seasonally adjusted percent change from the preceding month for July 2026. The first print is the August CPI news release, not a FRED mirror or later revised seasonal-adjustment vintage."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Forecast July 2026 BLS CPI-U headline monthly first print","The target is BLS CPI-U all items, U.S. city average, seasonally adjusted percent change from the preceding month for July 2026. The first print is the August CPI news release, not a FRED mirror or later revised seasonal-adjustment vintage."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.9, distribution present, forecast step count 1.","evidence":["Tool call: BLS May 2026 CPI news release headline, core, food, and energy details","Counter-consideration: this is still a forecast made before the June CPI first print and before most July price collection is observable. Upside outside the interval would come from renewed Middle East energy disruption, gasoline rebounding sharply in July, or broad tariff pass-through lifting core goods; downside outside the interval would require a larger gasoline retracement plus soft airfares, vehicles, and lodging."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, and mechanism split: core momentum cooled to 0.2 percent in May from 0.4 percent in April, shelter slowed to 0.3 percent from 0.6 percent, and food was 0.2 percent. Energy is still the main upside mechanism, but EIA gasoline prices were falling into late June, making a repeat of March-April gasoline-driven headline spikes less likely for July.","Prior/update/interval: use a persistence/recent-first-print prior from the February-May headline sample with median about 0.55 percent and realized range 0.3 to 0.9. Update by -0.15 percentage points for late-June gasoline declines, -0.05 for cooler May core/shelter momentum, and -0.05 for mean reversion from unusually energy-heavy March-May prints, giving 0.30 percent. Size the 80 percent interval from recent first-print dispersion, widened for missing June and July information: 0.30 minus 0.40 to 0.30 plus 0.50, rounded to [-0.1, 0.8]."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base-rate/reference-class anchor: the recent official first-print headline sequence is February 0.3, March 0.9, April 0.6, and May 0.5 percent, with the high prints heavily energy-driven. A simple recent median anchor is about 0.55 percent, but that reference class is contaminated by a March-May energy shock.","Level, momentum, and mechanism split: core momentum cooled to 0.2 percent in May from 0.4 percent in April, shelter slowed to 0.3 percent from 0.6 percent, and food was 0.2 percent. Energy is still the main upside mechanism, but EIA gasoline prices were falling into late June, making a repeat of March-April gasoline-driven headline spikes less likely for July."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast July 2026 BLS CPI-U headline monthly first print","Counter-consideration: this is still a forecast made before the June CPI first print and before most July price collection is observable. Upside outside the interval would come from renewed Middle East energy disruption, gasoline rebounding sharply in July, or broad tariff pass-through lifting core goods; downside outside the interval would require a larger gasoline retracement plus soft airfares, vehicles, and lodging."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-cpi-u-mom-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-12\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-core-cpi-mom-july-2026.2026-07-04T21-37-45Z.212246a87180ffa3","runId":"run.us-core-cpi-mom-july-2026.2026-07-04T21-37-45Z.212246a87180ffa3","predictionId":"us-core-cpi-mom-july-2026","specId":"spec.us-core-cpi-mom-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the recent official first-print reference class for core CPI is tightly centered: the six available monthly changes from Dec. 2025 through May 2026 are 0.2, 0.3, 0.2, 0.2, 0.4, and 0.2, with median 0.2 and mean 0.25. That makes a 0.2 to 0.3 percent prior more defensible than extrapolating from headline energy volatility.","Prior/update/interval: use a persistence/recent-first-print prior from the Dec. 2025-May 2026 BLS core CPI sample, centered at about 0.25 percent. Update by +0.05 percentage point for sticky shelter/services and possible indirect energy pass-through, and by 0.00 for core goods because May softness offsets tariff/supply risks, giving a rounded point forecast of 0.3 percent. Size the 80 percent interval from realized first-print dispersion in the recent sample, where observations ran 0.2 to 0.4, then widen for missing June and July information and unresolved pass-through risk to 0.1 to 0.5 percent."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The target is the first official BLS print for CPI-U all items less food and energy, seasonally adjusted monthly percent change for July 2026. The local catalog slug matches the requested target; I used local context only to confirm slug and dataPointId, not as forecast evidence.","Tool call: BLS CPI release calendar for July 2026 reference month"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is the first official BLS print for CPI-U all items less food and energy, seasonally adjusted monthly percent change for July 2026. The local catalog slug matches the requested target; I used local context only to confirm slug and dataPointId, not as forecast evidence.","Tool call: BLS CPI release calendar for July 2026 reference month"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.4, distribution present, forecast step count 1.","evidence":["Tool call: BLS Table 1 May 2026 expenditure category details for core components","Prior/update/interval: use a persistence/recent-first-print prior from the Dec. 2025-May 2026 BLS core CPI sample, centered at about 0.25 percent. Update by +0.05 percentage point for sticky shelter/services and possible indirect energy pass-through, and by 0.00 for core goods because May softness offsets tariff/supply risks, giving a rounded point forecast of 0.3 percent. Size the 80 percent interval from realized first-print dispersion in the recent sample, where observations ran 0.2 to 0.4, then widen for missing June and July information and unresolved pass-through risk to 0.1 to 0.5 percent."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level and momentum split: May core slowed back to 0.2 after April's 0.4, while the 12-month core rate was 2.9. That says underlying core inflation is still above a 2 percent annualized target pace but not accelerating sharply in the latest official print.","Prior/update/interval: use a persistence/recent-first-print prior from the Dec. 2025-May 2026 BLS core CPI sample, centered at about 0.25 percent. Update by +0.05 percentage point for sticky shelter/services and possible indirect energy pass-through, and by 0.00 for core goods because May softness offsets tariff/supply risks, giving a rounded point forecast of 0.3 percent. Size the 80 percent interval from realized first-print dispersion in the recent sample, where observations ran 0.2 to 0.4, then widen for missing June and July information and unresolved pass-through risk to 0.1 to 0.5 percent."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level and momentum split: May core slowed back to 0.2 after April's 0.4, while the 12-month core rate was 2.9. That says underlying core inflation is still above a 2 percent annualized target pace but not accelerating sharply in the latest official print.","Mechanism split: shelter and core services provide a sticky positive floor, while May core goods softness, lower new vehicle prices, and falling motor vehicle insurance reduce the chance of a broad July breakout. Energy is excluded from core, but the March-May energy shock can still leak into airfares, delivery-sensitive goods, and expectations with a lag."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast July 2026 US core CPI month-over-month","The target is the first official BLS print for CPI-U all items less food and energy, seasonally adjusted monthly percent change for July 2026. The local catalog slug matches the requested target; I used local context only to confirm slug and dataPointId, not as forecast evidence."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-core-cpi-mom-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-12\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.belgium-consumer-confidence-july-2026.2026-07-04T23-50-10Z.d62b67d07ec5e7aa","runId":"run.belgium-consumer-confidence-july-2026.2026-07-04T23-50-10Z.d62b67d07ec5e7aa","predictionId":"belgium-consumer-confidence-july-2026","specId":"spec.belgium-consumer-confidence-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: for this monthly survey-balance target, the outside-view anchor is persistence plus a short moving average. The last five official NBB values average -9.0, the last three average -10.0, and the latest print is -8.0, so the base rate points to a July reading still negative and close to -9.","Prior/update/interval: Use a persistence prior of -8.0 from the June 2026 official print and a short-sample mean of -9.0 from February-June 2026; adjustment components are +0.3 points for the June rebound, +0.2 points for easing headline inflation, and -0.9 points for still-high services costs and fragile euro-area sentiment, giving -8.4. The 80% interval uses realized recent month-to-month first-print dispersion, widened for survey volatility, giving -8.4 - 6.6 = -15.0 and -8.4 + 6.4 = -2.0."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Belgium July 2026 NBB Consumer Confidence Forecast","Framing and exact resolver: the target is the National Bank of Belgium's first published July 2026 consumer confidence indicator, seasonally adjusted, in signed index points. The local country enum does not include BE, so this Belgium target is encoded as EA while keeping the resolver tied to NBB."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: the target is the National Bank of Belgium's first published July 2026 consumer confidence indicator, seasonally adjusted, in signed index points. The local country enum does not include BE, so this Belgium target is encoded as EA while keeping the resolver tied to NBB.","Tool call: Checked the official NBB release calendar for the July 2026 consumer survey publication date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 13, distribution present, forecast step count 1.","evidence":["Level, momentum, one-off, and policy mechanisms: the level is weak but not crisis-like; momentum improved from April's -12.0 trough to -8.0 in June; one-off sentiment risk remains tied to energy and geopolitical shocks; the policy and price mechanism is mixed because lower headline inflation supports purchasing power while high services inflation restrains households.","Prior/update/interval: Use a persistence prior of -8.0 from the June 2026 official print and a short-sample mean of -9.0 from February-June 2026; adjustment components are +0.3 points for the June rebound, +0.2 points for easing headline inflation, and -0.9 points for still-high services costs and fragile euro-area sentiment, giving -8.4. The 80% interval uses realized recent month-to-month first-print dispersion, widened for survey volatility, giving -8.4 - 6.6 = -15.0 and -8.4 + 6.4 = -2.0."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and policy mechanisms: the level is weak but not crisis-like; momentum improved from April's -12.0 trough to -8.0 in June; one-off sentiment risk remains tied to energy and geopolitical shocks; the policy and price mechanism is mixed because lower headline inflation supports purchasing power while high services inflation restrains households."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, one-off, and policy mechanisms: the level is weak but not crisis-like; momentum improved from April's -12.0 trough to -8.0 in June; one-off sentiment risk remains tied to energy and geopolitical shocks; the policy and price mechanism is mixed because lower headline inflation supports purchasing power while high services inflation restrains households.","Counter-consideration and falsification: upside risk is a stronger household sentiment rebound from lower energy prices and better real-income expectations, which would land above the interval if July prints -1.9 or higher. Downside risk is renewed inflation, unemployment, or geopolitical concern, which would land below the interval if the first print is -15.1 or lower. Outside the interval would imply a sharper regime shift than the recent NBB reference class."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Belgium July 2026 NBB Consumer Confidence Forecast","Framing and exact resolver: the target is the National Bank of Belgium's first published July 2026 consumer confidence indicator, seasonally adjusted, in signed index points. The local country enum does not include BE, so this Belgium target is encoded as EA while keeping the resolver tied to NBB."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: belgium-consumer-confidence-july-2026\nrunLabel: Headline\nresolutionDate: 2026-07-20\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.belgium-nbb-business-barometer-july-2026.2026-07-04T23-47-58Z.326b388f22a2d0d3","runId":"run.belgium-nbb-business-barometer-july-2026.2026-07-04T23-47-58Z.326b388f22a2d0d3","predictionId":"belgium-nbb-business-barometer-july-2026","specId":"spec.belgium-nbb-business-barometer-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: for this monthly survey-balance target, persistence plus a short moving average is the outside-view anchor. The last five official NBB values average -13.1, the last three average -13.9, and the latest print is -12.6, so the base rate points to a July reading still negative and near -13 rather than a return to neutral.","Prior/update/interval: Use a persistence prior of -12.6 from the June 2026 official print and a short-sample mean of -13.1 from February-June 2026; adjustment components are +0.4 points for post-April recovery momentum, +0.2 points for easing euro-area inflation, and -0.2 points for Belgian services-cost pressure, giving an unrounded center near -12.2. The 80% interval uses realized monthly first-print dispersion in the recent NBB sample, widened for survey volatility and geopolitical/energy uncertainty, giving -17.5 to -7.0."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: the target is the National Bank of Belgium's first published July 2026 overall business barometer synthetic curve, seasonally adjusted, in signed index points. The ledger target is Belgian even though the local country enum uses EA for Belgium-linked public releases, so this forecast keeps the source and resolver tied to NBB.","Tool call: Checked the official NBB release calendar for the July 2026 business survey publication date."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: the target is the National Bank of Belgium's first published July 2026 overall business barometer synthetic curve, seasonally adjusted, in signed index points. The ledger target is Belgian even though the local country enum uses EA for Belgium-linked public releases, so this forecast keeps the source and resolver tied to NBB.","Tool call: Checked the official NBB release calendar for the July 2026 business survey publication date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 10.5, distribution present, forecast step count 1.","evidence":["Level, momentum, one-off, and policy mechanisms: the level is weak but not collapsing; momentum improved from the April trough of -15.4 to -12.6 in June; the main one-off risk is survey sentiment around energy/geopolitical conditions; policy and price mechanisms are mixed, with easing euro-area inflation helping but Belgian services inflation and high costs still restraining firms.","Prior/update/interval: Use a persistence prior of -12.6 from the June 2026 official print and a short-sample mean of -13.1 from February-June 2026; adjustment components are +0.4 points for post-April recovery momentum, +0.2 points for easing euro-area inflation, and -0.2 points for Belgian services-cost pressure, giving an unrounded center near -12.2. The 80% interval uses realized monthly first-print dispersion in the recent NBB sample, widened for survey volatility and geopolitical/energy uncertainty, giving -17.5 to -7.0."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and policy mechanisms: the level is weak but not collapsing; momentum improved from the April trough of -15.4 to -12.6 in June; the main one-off risk is survey sentiment around energy/geopolitical conditions; policy and price mechanisms are mixed, with easing euro-area inflation helping but Belgian services inflation and high costs still restraining firms.","Prior/update/interval: Use a persistence prior of -12.6 from the June 2026 official print and a short-sample mean of -13.1 from February-June 2026; adjustment components are +0.4 points for post-April recovery momentum, +0.2 points for easing euro-area inflation, and -0.2 points for Belgian services-cost pressure, giving an unrounded center near -12.2. The 80% interval uses realized monthly first-print dispersion in the recent NBB sample, widened for survey volatility and geopolitical/energy uncertainty, giving -17.5 to -7.0."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, one-off, and policy mechanisms: the level is weak but not collapsing; momentum improved from the April trough of -15.4 to -12.6 in June; the main one-off risk is survey sentiment around energy/geopolitical conditions; policy and price mechanisms are mixed, with easing euro-area inflation helping but Belgian services inflation and high costs still restraining firms.","Prior/update/interval: Use a persistence prior of -12.6 from the June 2026 official print and a short-sample mean of -13.1 from February-June 2026; adjustment components are +0.4 points for post-April recovery momentum, +0.2 points for easing euro-area inflation, and -0.2 points for Belgian services-cost pressure, giving an unrounded center near -12.2. The 80% interval uses realized monthly first-print dispersion in the recent NBB sample, widened for survey volatility and geopolitical/energy uncertainty, giving -17.5 to -7.0."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Belgium July 2026 NBB Business Barometer Forecast","Framing and exact resolver: the target is the National Bank of Belgium's first published July 2026 overall business barometer synthetic curve, seasonally adjusted, in signed index points. The ledger target is Belgian even though the local country enum uses EA for Belgium-linked public releases, so this forecast keeps the source and resolver tied to NBB."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: belgium-nbb-business-barometer-july-2026\nrunLabel: Headline\nresolutionDate: 2026-07-24\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.belgium-cpi-annual-rate-july-2026.2026-07-04T23-31-20Z.8a5effcf512c82d6","runId":"run.belgium-cpi-annual-rate-july-2026.2026-07-04T23-31-20Z.8a5effcf512c82d6","predictionId":"belgium-cpi-annual-rate-july-2026","specId":"spec.belgium-cpi-annual-rate-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.51,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The resolver is the first Statbel print for Belgian headline CPI annual inflation for July 2026, not a HICP flash estimate and not a revised database value. Statbel defines inflation as the ratio of the CPI for a month to the CPI for the same month one year earlier.","The base rate/reference class from the last 13 official monthly headline prints averages about 2.33%, but the latest 3 prints average about 3.83%. I weight the near-term state more heavily because the April-June regime includes the current energy and services configuration, while keeping the longer reference class as a pull toward lower inflation."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Tool result: The official calendar lists Consumer Price Index - Health Index for m-2026-07 on 30 July 2026.","Tool call: Read the official be.STAT table for the 13-month annual-inflation reference class."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The resolver is the first Statbel print for Belgian headline CPI annual inflation for July 2026, not a HICP flash estimate and not a revised database value. Statbel defines inflation as the ratio of the CPI for a month to the CPI for the same month one year earlier.","Tool call: Checked Statbel release calendar for the target month and publication date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.7, distribution present, forecast step count 1.","evidence":["Tool call: Read the latest Statbel release details for components and monthly movements.","Prior/update/interval: Start with a June persistence prior of 3.40% and a latest-3-month state anchor of 3.83% against a 13-month historical sample mean of 2.33%; update by -0.25 pp for easing energy from 11.20% in May to 10.31% in June and by -0.10 pp for food at 0.06%, offset by +0.10 pp for services at 5.10%, rents at 3.38%, and July travel seasonality. Rounded point = 3.20%. The 80% interval uses recent first-print monthly volatility around persistence, widened for July energy/travel swings, giving 2.40% to 4.10%."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["The base rate/reference class from the last 13 official monthly headline prints averages about 2.33%, but the latest 3 prints average about 3.83%. I weight the near-term state more heavily because the April-June regime includes the current energy and services configuration, while keeping the longer reference class as a pull toward lower inflation."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The base rate/reference class from the last 13 official monthly headline prints averages about 2.33%, but the latest 3 prints average about 3.83%. I weight the near-term state more heavily because the April-June regime includes the current energy and services configuration, while keeping the longer reference class as a pull toward lower inflation.","Prior/update/interval: Start with a June persistence prior of 3.40% and a latest-3-month state anchor of 3.83% against a 13-month historical sample mean of 2.33%; update by -0.25 pp for easing energy from 11.20% in May to 10.31% in June and by -0.10 pp for food at 0.06%, offset by +0.10 pp for services at 5.10%, rents at 3.38%, and July travel seasonality. Rounded point = 3.20%. The 80% interval uses recent first-print monthly volatility around persistence, widened for July energy/travel swings, giving 2.40% to 4.10%."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Belgium July 2026 Headline CPI Inflation Forecast","Tool result: June 2026 CPI fell by 0.31 points or 0.30% month on month; health-index inflation was 2.99%, core inflation was 3.04%, energy inflation was 10.31%, food inflation was 0.06%, services inflation was 5.10%, and rent inflation was 3.38%."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: belgium-cpi-annual-rate-july-2026\nrunLabel: Headline\nresolutionDate: 2026-07-30\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.belgium-health-index-annual-rate-july-2026.2026-07-04T23-32-35Z.cb5f43459577bf6e","runId":"run.belgium-health-index-annual-rate-july-2026.2026-07-04T23-32-35Z.cb5f43459577bf6e","predictionId":"belgium-health-index-annual-rate-july-2026","specId":"spec.belgium-health-index-annual-rate-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The target is Statbel's first July 2026 annual inflation rate based on the Belgian health index. The ledger target is Belgian even though the catalog country enum has no Belgium code, so I use EA consistently with nearby Thesis Statbel cells and keep the resolver tied to Statbel.","Tool result: Statbel reported inflation based on the health index at 2.99% in June 2026, 3.48% in May 2026, and 3.38% in April 2026."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The target is Statbel's first July 2026 annual inflation rate based on the Belgian health index. The ledger target is Belgian even though the catalog country enum has no Belgium code, so I use EA consistently with nearby Thesis Statbel cells and keep the resolver tied to Statbel.","Tool call: Checked the official Statbel release calendar for Consumer Price Index - Health Index, m-2026-07."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The target is Statbel's first July 2026 annual inflation rate based on the Belgian health index. The ledger target is Belgian even though the catalog country enum has no Belgium code, so I use EA consistently with nearby Thesis Statbel cells and keep the resolver tied to Statbel.","Tool call: Checked the official Statbel release calendar for Consumer Price Index - Health Index, m-2026-07."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.5, distribution present, forecast step count 1.","evidence":["Prior/update/interval: Start with a June persistence prior of 2.99% and an April-June reference-class mean of 3.28%; update by +0.10 pp for July package-holiday and travel-service seasonality, +0.05 pp for electricity and natural-gas pressure, -0.05 pp for near-zero food inflation, and no direct motor-fuel pass-through because the health index excludes most motor fuels. Rounded point = 3.10%. The 80% interval uses recent one-month first-print dispersion around health-index persistence, widened for July travel and energy uncertainty, giving 2.40% to 3.90%.","Upside risk: stronger July package holidays, air travel, rents, electricity or natural gas could push health-index inflation toward May's 3.48% or would land above the interval if several components rise together. Downside risk: another monthly decline in the health index, weaker food prices, or a reversal in energy service components could push the first print below 2.40% outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Read Statbel component commentary relevant to July health-index pressure.","The base rate/reference class is recent official health-index inflation: the April-June 2026 average is 3.28%, while the latest print is 2.99%. I anchor near June persistence because this is a one-month-ahead first-print target, but I do not fully extrapolate the June drop because July often has travel and holiday-price volatility."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The base rate/reference class is recent official health-index inflation: the April-June 2026 average is 3.28%, while the latest print is 2.99%. I anchor near June persistence because this is a one-month-ahead first-print target, but I do not fully extrapolate the June drop because July often has travel and holiday-price volatility.","Prior/update/interval: Start with a June persistence prior of 2.99% and an April-June reference-class mean of 3.28%; update by +0.10 pp for July package-holiday and travel-service seasonality, +0.05 pp for electricity and natural-gas pressure, -0.05 pp for near-zero food inflation, and no direct motor-fuel pass-through because the health index excludes most motor fuels. Rounded point = 3.10%. The 80% interval uses recent one-month first-print dispersion around health-index persistence, widened for July travel and energy uncertainty, giving 2.40% to 3.90%."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Belgium July 2026 Health-Index Inflation Forecast","Tool result: The health index decreased by 0.10 points in June 2026 to 102.59, down from 102.69 in May 2026; the smoothed health index was 100.37 in June."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: belgium-health-index-annual-rate-july-2026\nrunLabel: Headline\nresolutionDate: 2026-07-30\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.belgium-gdp-flash-q2-2026.2026-07-04T23-46-53Z.2d6389919d3f121b","runId":"run.belgium-gdp-flash-q2-2026.2026-07-04T23-46-53Z.2d6389919d3f121b","predictionId":"belgium-gdp-flash-q2-2026","specId":"spec.belgium-gdp-flash-q2-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the recent official first-print reference class for this exact qoq GDP-flash target is tightly centered around modest positive growth: 0.3, 0.2, 0.3, and 0.3 average 0.275%. That supports an outside-view prior near +0.3 rather than a contraction or acceleration.","Prior/update/interval: Start with a persistence prior of +0.3% from the recent official first-print historical sample of 2025-Q2 through 2026-Q1; update by -0.05 pp for high inflation and soft real-income pressure, -0.03 pp for external-demand/export risk, and +0.02 pp for continued low positive euro-area growth momentum, giving an unrounded center near +0.24%, rounded to +0.2%. The 80% interval uses recent first-print dispersion plus one-decimal rounding risk and a wider macro-shock allowance, giving -0.1% to +0.5%."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this targets the first official NBB/Institute for National Accounts flash estimate for Belgian real GDP growth in 2026-Q2, seasonally adjusted quarter-on-quarter percent growth. The ledger target is Belgian even though the local country enum lacks Belgium, so I use EA while keeping the source and resolver tied to NBB.","Tool call: Checked the official NBB release calendar for the 2026-Q2 GDP flash-estimate publication date."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this targets the first official NBB/Institute for National Accounts flash estimate for Belgian real GDP growth in 2026-Q2, seasonally adjusted quarter-on-quarter percent growth. The ledger target is Belgian even though the local country enum lacks Belgium, so I use EA while keeping the source and resolver tied to NBB.","Tool call: Checked the official NBB release calendar for the 2026-Q2 GDP flash-estimate publication date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.6, distribution present, forecast step count 1.","evidence":["Prior/update/interval: Start with a persistence prior of +0.3% from the recent official first-print historical sample of 2025-Q2 through 2026-Q1; update by -0.05 pp for high inflation and soft real-income pressure, -0.03 pp for external-demand/export risk, and +0.02 pp for continued low positive euro-area growth momentum, giving an unrounded center near +0.24%, rounded to +0.2%. The 80% interval uses recent first-print dispersion plus one-decimal rounding risk and a wider macro-shock allowance, giving -0.1% to +0.5%.","Counter-consideration and falsification: upside risk is a stronger services quarter or export rebound that would land above the interval if the flash print reaches +0.6% or more. Downside risk is a manufacturing/export stall or household-demand pullback that would land below the interval if the first print is -0.2% or weaker. The central case is continued slow positive growth."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and policy mechanisms: level growth is positive but not strong; momentum from Q1 is stable rather than accelerating; there is no clear one-off Q2 reopening or shutdown effect; policy and price mechanisms lean mildly restrictive because inflation and services costs remain high, while euro-area demand provides only limited support.","Prior/update/interval: Start with a persistence prior of +0.3% from the recent official first-print historical sample of 2025-Q2 through 2026-Q1; update by -0.05 pp for high inflation and soft real-income pressure, -0.03 pp for external-demand/export risk, and +0.02 pp for continued low positive euro-area growth momentum, giving an unrounded center near +0.24%, rounded to +0.2%. The 80% interval uses recent first-print dispersion plus one-decimal rounding risk and a wider macro-shock allowance, giving -0.1% to +0.5%."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, one-off, and policy mechanisms: level growth is positive but not strong; momentum from Q1 is stable rather than accelerating; there is no clear one-off Q2 reopening or shutdown effect; policy and price mechanisms lean mildly restrictive because inflation and services costs remain high, while euro-area demand provides only limited support.","Prior/update/interval: Start with a persistence prior of +0.3% from the recent official first-print historical sample of 2025-Q2 through 2026-Q1; update by -0.05 pp for high inflation and soft real-income pressure, -0.03 pp for external-demand/export risk, and +0.02 pp for continued low positive euro-area growth momentum, giving an unrounded center near +0.24%, rounded to +0.2%. The 80% interval uses recent first-print dispersion plus one-decimal rounding risk and a wider macro-shock allowance, giving -0.1% to +0.5%."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Belgium 2026-Q2 GDP flash forecast","Tool result: Fetched recent official-source reference points: 2026-Q1 GDP flash qoq growth was 0.3%, 2025-Q4 was 0.2%, 2025-Q3 was 0.3%, and 2025-Q2 was 0.3%, all in one-decimal percent growth terms."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: belgium-gdp-flash-q2-2026\nrunLabel: Headline\nresolutionDate: 2026-07-30\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.belgium-unemployment-rate-june-2026.2026-07-04T23-52-25Z.4d3a6442fbef0b23","runId":"run.belgium-unemployment-rate-june-2026.2026-07-04T23-52-25Z.4d3a6442fbef0b23","predictionId":"belgium-unemployment-rate-june-2026","specId":"spec.belgium-unemployment-rate-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the best outside-view base rate is latest-value persistence on Eurostat's one-decimal country unemployment series. Belgium's recent official sequence is 6.3, 6.2, 6.2, 6.3 from February through May 2026, so the reference class starts around 6.25 to 6.30 rather than extrapolating the 2025-to-2026 rise aggressively.","Prior/update/interval: persistence prior is the latest official rounded Belgium print of 6.3 from the February-May 2026 Eurostat sample {6.3, 6.2, 6.2, 6.3}; adjustment components are +0.05pp for the May unemployed-person rise, -0.02pp for stable euro-area context, and 0.00pp for inflation-policy context, leaving a rounded point of 6.3. Interval method uses recent one-month first-print dispersion on the one-decimal country series, widened for Belgium sampling and country-level volatility to about +/-0.4pp, implying final bounds of 5.9 to 6.7."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The target is Eurostat's first official June 2026 Belgium seasonally adjusted unemployment rate, total sex and age 15-74, in percent of the active population. The 2 July 2026 Eurostat unemployment release for May says the next release is 30 July 2026, so I use 2026-07-30 as the verified resolution date.","Tool result: Fetched Belgium rates: May-25 6.0%, Feb-26 6.3%, Mar-26 6.2%, Apr-26 6.2%, May-26 6.3%; fetched Belgium unemployed persons: May-25 333 thousand, Feb-26 345 thousand, Mar-26 343 thousand, Apr-26 343 thousand, May-26 347 thousand."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Belgium June 2026 unemployment-rate first print","The target is Eurostat's first official June 2026 Belgium seasonally adjusted unemployment rate, total sex and age 15-74, in percent of the active population. The 2 July 2026 Eurostat unemployment release for May says the next release is 30 July 2026, so I use 2026-07-30 as the verified resolution date."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.8, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is the latest official rounded Belgium print of 6.3 from the February-May 2026 Eurostat sample {6.3, 6.2, 6.2, 6.3}; adjustment components are +0.05pp for the May unemployed-person rise, -0.02pp for stable euro-area context, and 0.00pp for inflation-policy context, leaving a rounded point of 6.3. Interval method uses recent one-month first-print dispersion on the one-decimal country series, widened for Belgium sampling and country-level volatility to about +/-0.4pp, implying final bounds of 5.9 to 6.7.","Counter-consideration: upside risk is a broader June weakening in Belgian hiring or participation that pushes the rounded rate to 6.5-6.7. Downside risk is a reversal of May's unemployed-person rise that returns the rate to 6.1-6.2. Outside the interval, a print above 6.7 would require a sharp country-specific deterioration or major first-print instability; a print below 5.9 would require an unusually strong employment surprise."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level and momentum: the level is slightly above its May 2025 value of 6.0%, but the recent month-to-month path is flat to mildly higher. The rise in unemployed persons from 343 thousand to 347 thousand in May supports holding the rounded central forecast at 6.3 rather than dropping back to 6.2."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level and momentum: the level is slightly above its May 2025 value of 6.0%, but the recent month-to-month path is flat to mildly higher. The rise in unemployed persons from 343 thousand to 347 thousand in May supports holding the rounded central forecast at 6.3 rather than dropping back to 6.2.","Counter-consideration: upside risk is a broader June weakening in Belgian hiring or participation that pushes the rounded rate to 6.5-6.7. Downside risk is a reversal of May's unemployed-person rise that returns the rate to 6.1-6.2. Outside the interval, a print above 6.7 would require a sharp country-specific deterioration or major first-print instability; a print below 5.9 would require an unusually strong employment surprise."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Level and momentum: the level is slightly above its May 2025 value of 6.0%, but the recent month-to-month path is flat to mildly higher. The rise in unemployed persons from 343 thousand to 347 thousand in May supports holding the rounded central forecast at 6.3 rather than dropping back to 6.2.","Prior/update/interval: persistence prior is the latest official rounded Belgium print of 6.3 from the February-May 2026 Eurostat sample {6.3, 6.2, 6.2, 6.3}; adjustment components are +0.05pp for the May unemployed-person rise, -0.02pp for stable euro-area context, and 0.00pp for inflation-policy context, leaving a rounded point of 6.3. Interval method uses recent one-month first-print dispersion on the one-decimal country series, widened for Belgium sampling and country-level volatility to about +/-0.4pp, implying final bounds of 5.9 to 6.7."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: belgium-unemployment-rate-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-30\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.continued-claims-week-2026-06-27.2026-07-07T14-59-12Z.a47526b614599fcc","runId":"run.continued-claims-week-2026-06-27.2026-07-07T14-59-12Z.a47526b614599fcc","predictionId":"continued-claims-week-2026-06-27","specId":"spec.continued-claims-week-2026-06-27","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["The resolver is the national seasonally adjusted insured unemployment count, also called continued claims, for the week ending June 27, 2026. All anchors use the same DOL/ETA seasonally adjusted insured-unemployment variant, not initial claims, unadjusted claims, or FRED as the resolution source. The point and interval are derived independently from the cited official DOL and BLS evidence, not from any catalog forecast, prior point estimate, prior interval, or prior Thesis run.","Tool result: Fetched latest same-variant values: seasonally adjusted insured unemployment for week ending June 20, 2026 was 1,814,000; the prior week was revised to 1,812,000; the insured unemployment rate was 1.2 percent; the insured-unemployment four-week average was 1,803,000, up 10,750."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["The resolver is the national seasonally adjusted insured unemployment count, also called continued claims, for the week ending June 27, 2026. All anchors use the same DOL/ETA seasonally adjusted insured-unemployment variant, not initial claims, unadjusted claims, or FRED as the resolution source. The point and interval are derived independently from the cited official DOL and BLS evidence, not from any catalog forecast, prior point estimate, prior interval, or prior Thesis run.","Tool result: Fetched official schedule evidence: the UI Weekly Claims News Release is published Thursday at 8:30 AM Eastern; the archive page was updated July 2, 2026; the only listed 2026 non-Thursday exception is Wednesday, November 25, 2026; therefore the first release containing continued claims for week ending June 27, 2026 is Thursday, July 9, 2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Tool result: Fetched official schedule evidence: the UI Weekly Claims News Release is published Thursday at 8:30 AM Eastern; the archive page was updated July 2, 2026; the only listed 2026 non-Thursday exception is Wednesday, November 25, 2026; therefore the first release containing continued claims for week ending June 27, 2026 is Thursday, July 9, 2026.","Tool call: Checked the July 2, 2026 DOL UI Weekly Claims release values for latest same-series continued claims."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.02, distribution present, forecast step count 1.","evidence":["The resolver is the national seasonally adjusted insured unemployment count, also called continued claims, for the week ending June 27, 2026. All anchors use the same DOL/ETA seasonally adjusted insured-unemployment variant, not initial claims, unadjusted claims, or FRED as the resolution source. The point and interval are derived independently from the cited official DOL and BLS evidence, not from any catalog forecast, prior point estimate, prior interval, or prior Thesis run.","Level, momentum, one-off, and policy split: the level is not recessionary but is drifting higher. Momentum from May 23 through June 13 was clearly upward, while the latest weekly increase slowed to 0.002 million. Low initial claims reduce upside inflow, but weak payroll growth and downward revisions increase the risk that claimants remain insured longer. I found no policy mechanism in the checked public release context that would create a discrete level break for this week."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and policy split: the level is not recessionary but is drifting higher. Momentum from May 23 through June 13 was clearly upward, while the latest weekly increase slowed to 0.002 million. Low initial claims reduce upside inflow, but weak payroll growth and downward revisions increase the risk that claimants remain insured longer. I found no policy mechanism in the checked public release context that would create a discrete level break for this week.","Prior/update/interval: persistence prior is latest-value persistence at 1.814 million, with a reference class of the five fetched same-variant DOL values from May 23 through June 20. I add +0.004 million for recent upward continued-claims momentum, +0.003 million for weak hiring/longer-duration risk, and -0.001 million for low initial-claims inflow, giving 1.820 million. Interval method uses realized dispersion of successive same-variant changes; sigma = 0.006 million from changes +0.015, +0.014, +0.012, and +0.002, so 1.28*sigma = 0.008 million. I widen modestly to about 0.010 million because the target week follows a holiday-adjacent labor market period, weak payroll revisions raise duration risk, and the volatility sample is only four weekly changes."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: the tightest reference class is recent DOL first-release-adjacent seasonally adjusted insured-unemployment levels. The latest five same-variant values rose from 1.771 million to 1.814 million, with adjacent changes of +0.015, +0.014, +0.012, and +0.002 million. A persistence prior therefore starts near 1.814 million but allows a small continued increase.","Level, momentum, one-off, and policy split: the level is not recessionary but is drifting higher. Momentum from May 23 through June 13 was clearly upward, while the latest weekly increase slowed to 0.002 million. Low initial claims reduce upside inflow, but weak payroll growth and downward revisions increase the risk that claimants remain insured longer. I found no policy mechanism in the checked public release context that would create a discrete level break for this week."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["The resolver is the national seasonally adjusted insured unemployment count, also called continued claims, for the week ending June 27, 2026. All anchors use the same DOL/ETA seasonally adjusted insured-unemployment variant, not initial claims, unadjusted claims, or FRED as the resolution source. The point and interval are derived independently from the cited official DOL and BLS evidence, not from any catalog forecast, prior point estimate, prior interval, or prior Thesis run.","Prior/update/interval: persistence prior is latest-value persistence at 1.814 million, with a reference class of the five fetched same-variant DOL values from May 23 through June 20. I add +0.004 million for recent upward continued-claims momentum, +0.003 million for weak hiring/longer-duration risk, and -0.001 million for low initial-claims inflow, giving 1.820 million. Interval method uses realized dispersion of successive same-variant changes; sigma = 0.006 million from changes +0.015, +0.014, +0.012, and +0.002, so 1.28*sigma = 0.008 million. I widen modestly to about 0.010 million because the target week follows a holiday-adjacent labor market period, weak payroll revisions raise duration risk, and the volatility sample is only four weekly changes."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: continued-claims-week-2026-06-27\nrunLabel: Headline\nresolutionDate: 2026-07-09\ntraceLineCount: 19\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.continued-claims-week-2026-06-27.2026-07-08T02-45-44Z.continued-claims-week-2026-06-27-thesis-analyst-fast-2026-07-08t02-45-44z.aab97ccfd632f145","runId":"run.continued-claims-week-2026-06-27.2026-07-08T02-45-44Z.continued-claims-week-2026-06-27-thesis-analyst-fast-2026-07-08t02-45-44z.aab97ccfd632f145","predictionId":"continued-claims-week-2026-06-27","specId":"spec.continued-claims-week-2026-06-27","runLabel":"Fast rollout 1 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the tightest reference class is recent DOL first-release-adjacent weekly changes in seasonally adjusted insured unemployment. A local-random-walk or latest-value persistence prior is appropriate because this is a one-week-ahead level target with substantial weekly noise but no identified policy break.","Prior local Thesis run check: a prior public repository run for the same target used a 1.820 million point with a much tighter 1.810 to 1.830 million interval. I keep the point direction but widen the interval because the prompt requires sizing from realized dispersion of successive changes rather than a rounded hedged band."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Counter-considerations: upside risk is that duration pressure and state-level seasonal layoffs keep more claimants on insured unemployment rolls, which would land above the interval if the July 9 first print exceeds 1.847 million. Downside risk is that lower recent initial claims feed through quickly or the prior increase reverses, which would land below the interval if the first print is under 1.793 million. Outside the interval would most likely require a weekly move larger than about 27 thousand away from the 1.820 million point."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this forecasts the DOL ETA first-print regular-state-program seasonally adjusted insured unemployment series, also called continued claims, for the week ending June 27, 2026. All anchors use the same SA insured-unemployment variant, not NSA continued weeks claimed or all-program continued claims.","Tool result: Fetched schedule evidence: the archive page was updated July 7, 2026; the UI Weekly Claims News Release is published Thursdays at 8:30 AM Eastern; the only listed 2026 non-Thursday exception is Wednesday November 25, 2026; July 9, 2026 is the Thursday release date for the week ending June 27, 2026 continued-claims first print."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.05, distribution present, forecast step count 1.","evidence":["Prior local Thesis run check: a prior public repository run for the same target used a 1.820 million point with a much tighter 1.810 to 1.830 million interval. I keep the point direction but widen the interval because the prompt requires sizing from realized dispersion of successive changes rather than a rounded hedged band.","Prior/update/interval: persistence prior = latest same-variant level of 1.814 million. Historical sample = last 13 one-week SA insured-unemployment changes ending June 20, 2026 from the DOL table: -45, +22, -1, -32, -18, +18, -5, +14, -14, +15, +14, +12, +2 thousand. Adjustment components: recent upward momentum +0.005 million, low initial-claims inflow -0.001 million, weaker-duration/continuation pressure +0.002 million, no policy mechanism +0.000 million, giving 1.814 + 0.006 = 1.820 million. Interval method uses realized dispersion of those successive changes; sigma = 0.0207 million, and 1.28*sigma = 0.0265 million, so the 80% interval is 1.820 +/- 0.027 = [1.793, 1.847] million."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate/reference class: the tightest reference class is recent DOL first-release-adjacent weekly changes in seasonally adjusted insured unemployment. A local-random-walk or latest-value persistence prior is appropriate because this is a one-week-ahead level target with substantial weekly noise but no identified policy break.","Prior local Thesis run check: a prior public repository run for the same target used a 1.820 million point with a much tighter 1.810 to 1.830 million interval. I keep the point direction but widen the interval because the prompt requires sizing from realized dispersion of successive changes rather than a rounded hedged band."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: the tightest reference class is recent DOL first-release-adjacent weekly changes in seasonally adjusted insured unemployment. A local-random-walk or latest-value persistence prior is appropriate because this is a one-week-ahead level target with substantial weekly noise but no identified policy break.","Prior local Thesis run check: a prior public repository run for the same target used a 1.820 million point with a much tighter 1.810 to 1.830 million interval. I keep the point direction but widen the interval because the prompt requires sizing from realized dispersion of successive changes rather than a rounded hedged band."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for DOL ETA SA continued claims, week ending June 27, 2026","Framing and exact resolver: this forecasts the DOL ETA first-print regular-state-program seasonally adjusted insured unemployment series, also called continued claims, for the week ending June 27, 2026. All anchors use the same SA insured-unemployment variant, not NSA continued weeks claimed or all-program continued claims."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: continued-claims-week-2026-06-27\nrunLabel: Fast rollout 1 of 3\nresolutionDate: 2026-07-09\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.continued-claims-week-2026-06-27.2026-07-08T02-45-58Z.continued-claims-week-2026-06-27-thesis-analyst-fast-2026-07-08t02-45-58z.a47526b614599fcc","runId":"run.continued-claims-week-2026-06-27.2026-07-08T02-45-58Z.continued-claims-week-2026-06-27-thesis-analyst-fast-2026-07-08t02-45-58z.a47526b614599fcc","predictionId":"continued-claims-week-2026-06-27","specId":"spec.continued-claims-week-2026-06-27","runLabel":"Fast rollout 2 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Framing and exact resolver: this forecasts the DOL ETA first-print regular-state-program seasonally adjusted insured unemployment series, also called continued claims, for the week ending June 27, 2026. The target is in millions; the DOL release prose reports persons and the historical table reports thousands for the same SA variant, so all anchors here are converted to millions.","Tool result: Fetched latest same-variant values: seasonally adjusted insured unemployment for week ending June 20, 2026 was 1,814,000; the prior week was revised to 1,812,000; the insured unemployment rate was 1.2 percent; the insured-unemployment four-week average was 1,803,000, up 10,750."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this forecasts the DOL ETA first-print regular-state-program seasonally adjusted insured unemployment series, also called continued claims, for the week ending June 27, 2026. The target is in millions; the DOL release prose reports persons and the historical table reports thousands for the same SA variant, so all anchors here are converted to millions.","Tool result: Fetched official schedule evidence: the UI Weekly Claims News Release is published each Thursday at 8:30 AM Eastern; the archive page was updated July 7, 2026; the listed 2026 non-Thursday exception is Wednesday, November 25, 2026; July 9, 2026 is the Thursday release date for the next UI Weekly Claims release covering the June 27, 2026 continued-claims target."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this forecasts the DOL ETA first-print regular-state-program seasonally adjusted insured unemployment series, also called continued claims, for the week ending June 27, 2026. The target is in millions; the DOL release prose reports persons and the historical table reports thousands for the same SA variant, so all anchors here are converted to millions.","Tool result: Fetched official schedule evidence: the UI Weekly Claims News Release is published each Thursday at 8:30 AM Eastern; the archive page was updated July 7, 2026; the listed 2026 non-Thursday exception is Wednesday, November 25, 2026; July 9, 2026 is the Thursday release date for the next UI Weekly Claims release covering the June 27, 2026 continued-claims target."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.02, distribution present, forecast step count 1.","evidence":["Level, momentum, one-off, and policy split: the level is elevated relative to spring 2026 but not jumping. Momentum from late May through mid-June was upward, while the latest weekly increase slowed sharply. Low initial claims reduce near-term inflow pressure, but soft payroll growth and downward revisions raise duration risk. I found no policy mechanism in the checked public release context that would create a discrete break for this week.","Prior/update/interval: persistence prior is latest-value persistence at 1.814 million, with a reference class of the five fetched same-variant DOL values from May 23 through June 20. I add +0.004 million for recent upward continued-claims momentum, +0.003 million for weak hiring/longer-duration risk, and -0.001 million for low initial-claims inflow, giving 1.820 million. Interval method uses realized dispersion of successive same-variant changes; sigma = 0.006 million from changes +0.015, +0.014, +0.012, and +0.002, so 1.28*sigma = 0.008 million. I widen modestly to about 0.010 million because the target week is near the July 4 seasonal-adjustment period and because weak payroll revisions raise duration risk."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and policy split: the level is elevated relative to spring 2026 but not jumping. Momentum from late May through mid-June was upward, while the latest weekly increase slowed sharply. Low initial claims reduce near-term inflow pressure, but soft payroll growth and downward revisions raise duration risk. I found no policy mechanism in the checked public release context that would create a discrete break for this week.","Prior/update/interval: persistence prior is latest-value persistence at 1.814 million, with a reference class of the five fetched same-variant DOL values from May 23 through June 20. I add +0.004 million for recent upward continued-claims momentum, +0.003 million for weak hiring/longer-duration risk, and -0.001 million for low initial-claims inflow, giving 1.820 million. Interval method uses realized dispersion of successive same-variant changes; sigma = 0.006 million from changes +0.015, +0.014, +0.012, and +0.002, so 1.28*sigma = 0.008 million. I widen modestly to about 0.010 million because the target week is near the July 4 seasonal-adjustment period and because weak payroll revisions raise duration risk."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: the tightest reference class is recent DOL first-release-adjacent seasonally adjusted insured-unemployment levels. The latest five same-variant values rose from 1.771 million to 1.814 million, with adjacent changes of +0.015, +0.014, +0.012, and +0.002 million. A persistence prior therefore starts near 1.814 million but allows a small continued increase.","Level, momentum, one-off, and policy split: the level is elevated relative to spring 2026 but not jumping. Momentum from late May through mid-June was upward, while the latest weekly increase slowed sharply. Low initial claims reduce near-term inflow pressure, but soft payroll growth and downward revisions raise duration risk. I found no policy mechanism in the checked public release context that would create a discrete break for this week."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Framing and exact resolver: this forecasts the DOL ETA first-print regular-state-program seasonally adjusted insured unemployment series, also called continued claims, for the week ending June 27, 2026. The target is in millions; the DOL release prose reports persons and the historical table reports thousands for the same SA variant, so all anchors here are converted to millions.","Prior/update/interval: persistence prior is latest-value persistence at 1.814 million, with a reference class of the five fetched same-variant DOL values from May 23 through June 20. I add +0.004 million for recent upward continued-claims momentum, +0.003 million for weak hiring/longer-duration risk, and -0.001 million for low initial-claims inflow, giving 1.820 million. Interval method uses realized dispersion of successive same-variant changes; sigma = 0.006 million from changes +0.015, +0.014, +0.012, and +0.002, so 1.28*sigma = 0.008 million. I widen modestly to about 0.010 million because the target week is near the July 4 seasonal-adjustment period and because weak payroll revisions raise duration risk."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: continued-claims-week-2026-06-27\nrunLabel: Fast rollout 2 of 3\nresolutionDate: 2026-07-09\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.continued-claims-week-2026-06-27.2026-07-08T02-46-42Z.continued-claims-week-2026-06-27-thesis-analyst-fast-2026-07-08t02-46-42z.c6cbfb6e8e6b00ba","runId":"run.continued-claims-week-2026-06-27.2026-07-08T02-46-42Z.continued-claims-week-2026-06-27-thesis-analyst-fast-2026-07-08t02-46-42z.c6cbfb6e8e6b00ba","predictionId":"continued-claims-week-2026-06-27","specId":"spec.continued-claims-week-2026-06-27","runLabel":"Fast rollout 3 of 3","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool result: The release reports advance seasonally adjusted insured unemployment of 1,814,000 for week ending June 20, 2026, up 2,000 from the revised June 13 level of 1,812,000; the prior week was revised down from 1,821,000 to 1,812,000.","Tool call: Read the DOL historical table 'Seasonally Adjusted US Weekly UI Claims (in thousands)' for the recent reference class and initial-claims context."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this targets the DOL ETA weekly claims release variant labeled seasonally adjusted Insured Unemployment, not unadjusted continued weeks claimed in all programs. The target week is week ending June 27, 2026, first print, converted from thousands to millions.","Tool result: The official archive page says the UI Weekly Claims News Release is published each week on Thursday morning at 8:30 AM EST, lists only Wednesday November 25, 2026 as a 2026 non-Thursday exception, and was updated July 7, 2026; therefore the Thursday release for this target is July 9, 2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this targets the DOL ETA weekly claims release variant labeled seasonally adjusted Insured Unemployment, not unadjusted continued weeks claimed in all programs. The target week is week ending June 27, 2026, first print, converted from thousands to millions.","Tool call: Checked the DOL ETA weekly claims archive and publication schedule page for release timing."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.05, distribution present, forecast step count 1.","evidence":["Base rate and reference class: for one-week-ahead level forecasts in this DOL series, the strongest base rate is persistence from the latest first-print/revised official level, with recent successive weekly changes used to size uncertainty. The last four observed same-variant SA continued-claims changes were +15,000, +14,000, +12,000, and +2,000, so momentum is positive but decelerating.","Prior/update/interval: persistence prior = 1.814 million from the latest DOL SA insured unemployment print; historical sample = 52 weekly same-variant changes from June 28, 2025 through June 20, 2026 in the DOL table; adjustment components = +0.004 million for recent positive continued-claims momentum, -0.001 million for softer same-week initial claims and the slowing +2,000 latest move, giving point 1.814 + 0.004 - 0.001 = 1.817 million; interval method = one-week change dispersion, sigma = 0.02099 million, half-width = 1.28*sigma = 1.28*0.02099 = 0.0269 million, rounded to about 0.027 million; final implied bounds are 1.817 - 0.028 = 1.789 and 1.817 + 0.026 = 1.843 million."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate and reference class: for one-week-ahead level forecasts in this DOL series, the strongest base rate is persistence from the latest first-print/revised official level, with recent successive weekly changes used to size uncertainty. The last four observed same-variant SA continued-claims changes were +15,000, +14,000, +12,000, and +2,000, so momentum is positive but decelerating.","Prior/update/interval: persistence prior = 1.814 million from the latest DOL SA insured unemployment print; historical sample = 52 weekly same-variant changes from June 28, 2025 through June 20, 2026 in the DOL table; adjustment components = +0.004 million for recent positive continued-claims momentum, -0.001 million for softer same-week initial claims and the slowing +2,000 latest move, giving point 1.814 + 0.004 - 0.001 = 1.817 million; interval method = one-week change dispersion, sigma = 0.02099 million, half-width = 1.28*sigma = 1.28*0.02099 = 0.0269 million, rounded to about 0.027 million; final implied bounds are 1.817 - 0.028 = 1.789 and 1.817 + 0.026 = 1.843 million."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate and reference class: for one-week-ahead level forecasts in this DOL series, the strongest base rate is persistence from the latest first-print/revised official level, with recent successive weekly changes used to size uncertainty. The last four observed same-variant SA continued-claims changes were +15,000, +14,000, +12,000, and +2,000, so momentum is positive but decelerating.","Upside risk is that late-June continuing unemployment reflects delayed separations or benefit-duration persistence not visible in initial claims, which would land above the interval if SA insured unemployment jumps by more than about 29,000 to above 1.843 million. Downside risk is a sharper reversal in continuing claims after the latest initial-claims easing, which would land below the interval if the level falls under 1.789 million. An outside the interval result would most likely come from a state-level reporting swing or seasonal-adjustment miss in the holiday-adjacent summer weeks."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for DOL seasonally adjusted continued claims, week ending June 27 2026","Base rate and reference class: for one-week-ahead level forecasts in this DOL series, the strongest base rate is persistence from the latest first-print/revised official level, with recent successive weekly changes used to size uncertainty. The last four observed same-variant SA continued-claims changes were +15,000, +14,000, +12,000, and +2,000, so momentum is positive but decelerating."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: continued-claims-week-2026-06-27\nrunLabel: Fast rollout 3 of 3\nresolutionDate: 2026-07-09\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.continued-claims-week-2026-06-27.2026-07-08T02-47-27Z.continued-claims-week-2026-06-27-thesis-analyst-ladder-2026-07-08t02-47-27z.d8f1c046ad4b5a9e","runId":"run.continued-claims-week-2026-06-27.2026-07-08T02-47-27Z.continued-claims-week-2026-06-27-thesis-analyst-ladder-2026-07-08t02-47-27z.d8f1c046ad4b5a9e","predictionId":"continued-claims-week-2026-06-27","specId":"spec.continued-claims-week-2026-06-27","runLabel":"Threshold-ladder elicitation","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: for a one-week-ahead continued-claims level forecast, the best outside-view anchor is persistence from the latest first-print/revised DOL SA insured unemployment level plus the empirical distribution of recent weekly changes in the same DOL variant. The latest level is 1.814 million, and the last three weekly changes were +0.014, +0.012, and +0.002 million.","Prior/update/interval: persistence prior = 1.814 million from the latest DOL same-variant print; historical sample = 52 successive weekly changes from the June 21, 2025 to June 20, 2026 DOL table; adjustment components = +0.004 million for recent upward continued-claims momentum, -0.001 million because initial claims for June 27 were only 215,000 and down 1,000, +0.000 million for policy mechanism because no UI rule change is needed for the first print; point before ladder = 1.817 million. From the fetched history, sigma = 0.020987 million for successive SA insured-unemployment changes, so 1.28*sigma = 0.026863 million. The ladder-implied 80% half-width is about 0.030 million, 1.12x the 1.28*sigma half-width, modestly wider because holiday/seasonal adjustment around late June can move continued claims even when initial claims are flat."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Framing and exact resolver: the target is the DOL ETA regular state programs seasonally adjusted insured unemployment series, also called continued claims, for the week ending June 27, 2026. The resolution is the advance first print in the weekly claims release, in millions of persons, ignoring later revisions.","Tool result: The official schedule says the UI Weekly Claims News Release is published each week on Thursday at 8:30 AM EST, with 1 listed 2026 exception: Wednesday, November 25, 2026 at 8:30 AM EST; therefore Thursday, July 9, 2026 is the verified release date for the June 27 continued-claims first print."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: the target is the DOL ETA regular state programs seasonally adjusted insured unemployment series, also called continued claims, for the week ending June 27, 2026. The resolution is the advance first print in the weekly claims release, in millions of persons, ignoring later revisions.","Tool result: The official schedule says the UI Weekly Claims News Release is published each week on Thursday at 8:30 AM EST, with 1 listed 2026 exception: Wednesday, November 25, 2026 at 8:30 AM EST; therefore Thursday, July 9, 2026 is the verified release date for the June 27 continued-claims first print."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.06, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = 1.814 million from the latest DOL same-variant print; historical sample = 52 successive weekly changes from the June 21, 2025 to June 20, 2026 DOL table; adjustment components = +0.004 million for recent upward continued-claims momentum, -0.001 million because initial claims for June 27 were only 215,000 and down 1,000, +0.000 million for policy mechanism because no UI rule change is needed for the first print; point before ladder = 1.817 million. From the fetched history, sigma = 0.020987 million for successive SA insured-unemployment changes, so 1.28*sigma = 0.026863 million. The ladder-implied 80% half-width is about 0.030 million, 1.12x the 1.28*sigma half-width, modestly wider because holiday/seasonal adjustment around late June can move continued claims even when initial claims are flat.","Counter-considerations: upside risk would be a repeat of broad unadjusted insured-unemployment increases like the +34,778 NSA move in the latest release, which could lift the SA print toward or above 1.850 million. Downside risk would be a reversal in benefit duration after initial claims held at 215,000, which could pull the SA level below 1.790 million. A sudden state reporting distortion or seasonal-factor miss would land outside the interval."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence prior = 1.814 million from the latest DOL same-variant print; historical sample = 52 successive weekly changes from the June 21, 2025 to June 20, 2026 DOL table; adjustment components = +0.004 million for recent upward continued-claims momentum, -0.001 million because initial claims for June 27 were only 215,000 and down 1,000, +0.000 million for policy mechanism because no UI rule change is needed for the first print; point before ladder = 1.817 million. From the fetched history, sigma = 0.020987 million for successive SA insured-unemployment changes, so 1.28*sigma = 0.026863 million. The ladder-implied 80% half-width is about 0.030 million, 1.12x the 1.28*sigma half-width, modestly wider because holiday/seasonal adjustment around late June can move continued claims even when initial claims are flat."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: for a one-week-ahead continued-claims level forecast, the best outside-view anchor is persistence from the latest first-print/revised DOL SA insured unemployment level plus the empirical distribution of recent weekly changes in the same DOL variant. The latest level is 1.814 million, and the last three weekly changes were +0.014, +0.012, and +0.002 million.","Counter-considerations: upside risk would be a repeat of broad unadjusted insured-unemployment increases like the +34,778 NSA move in the latest release, which could lift the SA print toward or above 1.850 million. Downside risk would be a reversal in benefit duration after initial claims held at 215,000, which could pull the SA level below 1.790 million. A sudden state reporting distortion or seasonal-factor miss would land outside the interval."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for DOL ETA continued claims, week ending June 27, 2026","Base rate/reference class: for a one-week-ahead continued-claims level forecast, the best outside-view anchor is persistence from the latest first-print/revised DOL SA insured unemployment level plus the empirical distribution of recent weekly changes in the same DOL variant. The latest level is 1.814 million, and the last three weekly changes were +0.014, +0.012, and +0.002 million."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: continued-claims-week-2026-06-27\nrunLabel: Threshold-ladder elicitation\nresolutionDate: 2026-07-09\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.continued-claims-week-2026-06-27.2026-07-08T03-03-42Z.continued-claims-week-2026-06-27-thesis-analyst-median3-2026-07-08t03-03-42z.80a76b0e1a95ed7b","runId":"run.continued-claims-week-2026-06-27.2026-07-08T03-03-42Z.continued-claims-week-2026-06-27-thesis-analyst-median3-2026-07-08t03-03-42z.80a76b0e1a95ed7b","predictionId":"continued-claims-week-2026-06-27","specId":"spec.continued-claims-week-2026-06-27","runLabel":"Median of 3 rollouts","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.11,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 5 historical point(s) and implicit outside-view language.","evidence":["Median-of-3 rollout ensemble","Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-08T02:45:44Z, 2026-07-08T02:45:58Z, 2026-07-08T02:46:42Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 1 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["Median CDF quantiles: q10 = 1.793, q50 = 1.82, q90 = 1.843. Constituent points [1.82, 1.82, 1.817] with 80% widths [0.054, 0.02, 0.054]; the median interval inherits the central rollout mass rather than averaging tails."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.05, distribution present, forecast step count 1.","evidence":["Median CDF quantiles: q10 = 1.793, q50 = 1.82, q90 = 1.843. Constituent points [1.82, 1.82, 1.817] with 80% widths [0.054, 0.02, 0.054]; the median interval inherits the central rollout mass rather than averaging tails.","Forecast: point 1.82, 80% interval [1.793, 1.843]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-08T02:45:44Z, 2026-07-08T02:45:58Z, 2026-07-08T02:46:42Z. Drivers and resolver fields mirror the rollout closest to the median."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":1,"rationale":"Score 1/4: offsetting-evidence language is present.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Derived run: the pointwise median of the CDFs of 3 independent thesis.analyst fast rollouts on this target — median prediction sampling per Turtel et al. 2025 (arXiv:2505.17989). No new model call; this run is a deterministic aggregate of the recorded rollouts at 2026-07-08T02:45:44Z, 2026-07-08T02:45:58Z, 2026-07-08T02:46:42Z. Drivers and resolver fields mirror the rollout closest to the median.","Tool result: {rollout_points: [1.82, 1.82, 1.817], rollout_widths: [0.054, 0.02, 0.054], q10: 1.793, q50: 1.82, q90: 1.843}"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: continued-claims-week-2026-06-27\nrunLabel: Median of 3 rollouts\nresolutionDate: 2026-07-09\ntraceLineCount: 6\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: counterarguments (1/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.wic-participation-april-2026.2026-07-07T13-52-34Z.c1639922773fdd43","runId":"run.wic-participation-april-2026.2026-07-07T13-52-34Z.c1639922773fdd43","predictionId":"wic-participation-april-2026","specId":"spec.wic-participation-april-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool result: Fetched prior monthly vintage evidence: 37wic-monthly-6.pdf is Data as of June 12, 2026 and includes Mar 2026 but not Apr 2026; 37wic-monthly-7.pdf is Data as of July 11, 2025 and includes Apr 2025, which is historical timing evidence but not direct verification of the April 2026 first-print date.","Base rate/reference class: recent March-to-April changes in the same official Total Participants column were -0.008692 million in 2023, +0.041068 million in 2024, and +0.026379 million in 2025, an average April seasonal increment of +0.019585 million. The latest level is lower than FY2025, so I use a level-adjusted seasonal prior rather than the raw April average of 6.737 million across 2023-2025."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 3 source-context item(s), activity log present.","evidence":["Tool call: Opened the USDA FNS WIC Data Tables page to verify the official source family and linked resource structure.","Tool result: Fetched official WIC Data Tables page showing Monthly Data - National Level as FY 2022 through November 2025, Monthly Data - State Level FY 2026 preliminary, Latest Available Month resource links, and Page updated February 24, 2026."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool result: Fetched prior monthly vintage evidence: 37wic-monthly-6.pdf is Data as of June 12, 2026 and includes Mar 2026 but not Apr 2026; 37wic-monthly-7.pdf is Data as of July 11, 2025 and includes Apr 2025, which is historical timing evidence but not direct verification of the April 2026 first-print date.","Counter-consideration: upside risk would be a stronger administrative catch-up or broader spring recertification rebound, putting the first print above 6.800 million. Downside risk would be continued FY2026 participation erosion, weak infant/women counts, or reporting delays that leave April near March or below, which would land below the interval."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.15, distribution present, forecast step count 1.","evidence":["Framing and exact resolver: this targets USDA FNS WIC Participation and Costs national monthly data, preliminary FY2026, Total Participants for April 2026. This is the monthly national total-participants variant, not annual average participation, state-level category detail, or costs; all anchors below use the same Total Participants column.","Prior/update/interval: model is seasonal persistence using official Total Participants history. Historical sample mixes FY2026 Oct-Mar successive changes for near-term trend with 2023-2025 March-to-April changes for seasonality: -0.138204, -0.059123, -0.016311, -0.031720, +0.037081, -0.008692, +0.041068, +0.026379 million. Adjustment components: March 2026 level 6.701661 + average March-to-April seasonal increment 0.019585 = 6.721246; year-over-year ratio anchor is Apr 2025 6.877215 * (Mar 2026 6.701661 / Mar 2025 6.850836) = 6.727466. Averaging gives 6.724356, rounded to 6.724. Interval method uses realized successive-change dispersion: sigma = 0.059650 million, so 1.28*sigma = 0.076352 million; 6.724 +/- 0.076 gives final implied bounds 6.648 to 6.800 million."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, and mechanism: the level anchor is Mar 2026 at 6.701661 million. Momentum improved from Feb to Mar by +0.037081 million after declines from Oct through Feb, but Mar 2026 remained 0.149175 million below Mar 2025. Mechanically, children remain the largest component and rose from 3,808,769 in Feb 2026 to 3,824,372 in Mar 2026, while infant and women counts remain below 2025 levels.","Review disposition: accepted the critique that the 2026-07-11 resolver date was not directly verified by the cited 2026 evidence and noted that discrepancy while keeping the ledger target date unchanged; accepted the resolver-clarity and mixed-sample interval notes; rejected changing the point estimate or interval because the public numeric anchors and arithmetic remain coherent."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Tool result: Fetched prior monthly vintage evidence: 37wic-monthly-6.pdf is Data as of June 12, 2026 and includes Mar 2026 but not Apr 2026; 37wic-monthly-7.pdf is Data as of July 11, 2025 and includes Apr 2025, which is historical timing evidence but not direct verification of the April 2026 first-print date.","Level, momentum, and mechanism: the level anchor is Mar 2026 at 6.701661 million. Momentum improved from Feb to Mar by +0.037081 million after declines from Oct through Feb, but Mar 2026 remained 0.149175 million below Mar 2025. Mechanically, children remain the largest component and rose from 3,808,769 in Feb 2026 to 3,824,372 in Mar 2026, while infant and women counts remain below 2025 levels."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast USDA FNS WIC total participation for April 2026","Prior/update/interval: model is seasonal persistence using official Total Participants history. Historical sample mixes FY2026 Oct-Mar successive changes for near-term trend with 2023-2025 March-to-April changes for seasonality: -0.138204, -0.059123, -0.016311, -0.031720, +0.037081, -0.008692, +0.041068, +0.026379 million. Adjustment components: March 2026 level 6.701661 + average March-to-April seasonal increment 0.019585 = 6.721246; year-over-year ratio anchor is Apr 2025 6.877215 * (Mar 2026 6.701661 / Mar 2025 6.850836) = 6.727466. Averaging gives 6.724356, rounded to 6.724. Interval method uses realized successive-change dispersion: sigma = 0.059650 million, so 1.28*sigma = 0.076352 million; 6.724 +/- 0.076 gives final implied bounds 6.648 to 6.800 million."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: wic-participation-april-2026\nrunLabel: Headline\nresolutionDate: 2026-07-11\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-real-avg-hourly-earnings-mom-june-2026.2026-07-07T14-05-24Z.a568db54594929de","runId":"run.us-real-avg-hourly-earnings-mom-june-2026.2026-07-07T14-05-24Z.a568db54594929de","predictionId":"us-real-avg-hourly-earnings-mom-june-2026","specId":"spec.us-real-avg-hourly-earnings-mom-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 4 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the fetched recent official target history is weakly negative, with Mar-May 2026 real hourly earnings changes of -0.6, -0.5, and -0.1 percent after energy-driven CPI pressure; the four fetched target observations including May 2025 average -0.2 percent. Current-release information should move above that base rate because June nominal AHE is already known to be stronger than May and the CPI energy impulse is unlikely to repeat at May's 3.9 percent energy pace.","Prior/update/interval: persistence prior is the recent official Table A-1 target-value reference class [0.4, -0.6, -0.5, -0.1], mean = -0.2; update components are +0.3466 percent known nominal AHE, about -0.25 percent assumed June CPI-U, and no separate hours effect because the target is hourly earnings; interval method is realized dispersion of the fetched change-series values, sigma = 0.4546, so 1.28*sigma = 0.5819 percentage point. Centering the final at +0.1 gives mechanical 80 percent bounds near -0.48 to +0.68, rounded to -0.5 to +0.7."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["June 2026 BLS Real Average Hourly Earnings MoM Forecast","Framing and exact resolver: this targets BLS Real Earnings Table A-1, real average hourly earnings for all employees on private nonfarm payrolls, seasonally adjusted, over-the-month percent change for June 2026 first print. The variant is the BLS Real Earnings SA all-employees private nonfarm series deflated by CPI-U, not production-worker earnings, weekly earnings, NSA CPI, or a later revised vintage."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this targets BLS Real Earnings Table A-1, real average hourly earnings for all employees on private nonfarm payrolls, seasonally adjusted, over-the-month percent change for June 2026 first print. The variant is the BLS Real Earnings SA all-employees private nonfarm series deflated by CPI-U, not production-worker earnings, weekly earnings, NSA CPI, or a later revised vintage.","Tool call: Checked BLS Real Earnings release schedule for June 2026 reference month."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 1.2, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior is the recent official Table A-1 target-value reference class [0.4, -0.6, -0.5, -0.1], mean = -0.2; update components are +0.3466 percent known nominal AHE, about -0.25 percent assumed June CPI-U, and no separate hours effect because the target is hourly earnings; interval method is realized dispersion of the fetched change-series values, sigma = 0.4546, so 1.28*sigma = 0.5819 percentage point. Centering the final at +0.1 gives mechanical 80 percent bounds near -0.48 to +0.68, rounded to -0.5 to +0.7.","Counter-consideration: upside risk is a soft or negative June CPI print combined with unchanged nominal wage data, which would land above the interval if CPI fell sharply enough to put real hourly earnings above +0.7 percent. Downside risk is another energy-led CPI jump around May's magnitude or a BLS nominal earnings correction, which would land below the interval if real hourly earnings fell under -0.5 percent. An outside the interval result would mainly falsify the assumed June CPI moderation, not the already-published nominal wage anchor."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Read BLS CPI May 2026 release for current CPI momentum before the June CPI print.","Base rate/reference class: the fetched recent official target history is weakly negative, with Mar-May 2026 real hourly earnings changes of -0.6, -0.5, and -0.1 percent after energy-driven CPI pressure; the four fetched target observations including May 2025 average -0.2 percent. Current-release information should move above that base rate because June nominal AHE is already known to be stronger than May and the CPI energy impulse is unlikely to repeat at May's 3.9 percent energy pace."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Counter-consideration: upside risk is a soft or negative June CPI print combined with unchanged nominal wage data, which would land above the interval if CPI fell sharply enough to put real hourly earnings above +0.7 percent. Downside risk is another energy-led CPI jump around May's magnitude or a BLS nominal earnings correction, which would land below the interval if real hourly earnings fell under -0.5 percent. An outside the interval result would mainly falsify the assumed June CPI moderation, not the already-published nominal wage anchor."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["June 2026 BLS Real Average Hourly Earnings MoM Forecast","Prior/update/interval: persistence prior is the recent official Table A-1 target-value reference class [0.4, -0.6, -0.5, -0.1], mean = -0.2; update components are +0.3466 percent known nominal AHE, about -0.25 percent assumed June CPI-U, and no separate hours effect because the target is hourly earnings; interval method is realized dispersion of the fetched change-series values, sigma = 0.4546, so 1.28*sigma = 0.5819 percentage point. Centering the final at +0.1 gives mechanical 80 percent bounds near -0.48 to +0.68, rounded to -0.5 to +0.7."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-real-avg-hourly-earnings-mom-june-2026\nrunLabel: Headline\nresolutionDate: 2026-07-14\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.jolts-quits-rate-june-2026.2026-07-07T14-01-13Z.bac4204c43b3f2a9","runId":"run.jolts-quits-rate-june-2026.2026-07-07T14-01-13Z.bac4204c43b3f2a9","predictionId":"jolts-quits-rate-june-2026","specId":"spec.jolts-quits-rate-june-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base-rate/reference class: for the one-month-ahead first print of a rounded JOLTS rate, persistence is the base rate. The recent official-source reference class is the early-2026 total nonfarm quits-rate run of 2.0, 1.9, 2.0, 1.9, and 1.9 percent, which averages 1.94 percent and rounds to 1.9 percent.","Prior/update/interval: persistence prior uses the latest official May 2026 quits rate of 1.9 percent and the Jan-May reference-class mean of (2.0 + 1.9 + 2.0 + 1.9 + 1.9) / 5 = 1.94 percent; adjustment components are -0.03 point for slower June payroll growth, +0.01 point for still-low 4.2 percent unemployment, and -0.02 point for flat May hires and quits, leaving 1.90 percent after rounding. Interval method uses successive changes from fetched Jan-May history: -0.1, +0.1, -0.1, 0.0, so sample sigma = 0.096 percentage point and 1.28*sigma = 0.123. This is a short rounded recent-volatility sample, but for a one-month-ahead rounded rate in a stable 1.9-2.0 regime, the 80% central interval is kept near the realized one-decimal grid rather than widened mechanically. Applying 1.90 +/- 0.123 gives 1.78 to 2.02, rounded to the BLS one-decimal reporting grid as 1.8 to 2.0."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Forecast for June 2026 BLS JOLTS quits rate","Framing and exact resolver: the target is the BLS JOLTS Table 4 seasonally adjusted total nonfarm quits rate for June 2026, not the quits level, not total private, and not a not-seasonally-adjusted variant. The first print in the August 4, 2026 release governs, with FRED used only as a history mirror and not as the resolver."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: the target is the BLS JOLTS Table 4 seasonally adjusted total nonfarm quits rate for June 2026, not the quits level, not total private, and not a not-seasonally-adjusted variant. The first print in the August 4, 2026 release governs, with FRED used only as a history mirror and not as the resolver.","Tool call: Checked the BLS JOLTS release calendar for the June 2026 reference month."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.2, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior uses the latest official May 2026 quits rate of 1.9 percent and the Jan-May reference-class mean of (2.0 + 1.9 + 2.0 + 1.9 + 1.9) / 5 = 1.94 percent; adjustment components are -0.03 point for slower June payroll growth, +0.01 point for still-low 4.2 percent unemployment, and -0.02 point for flat May hires and quits, leaving 1.90 percent after rounding. Interval method uses successive changes from fetched Jan-May history: -0.1, +0.1, -0.1, 0.0, so sample sigma = 0.096 percentage point and 1.28*sigma = 0.123. This is a short rounded recent-volatility sample, but for a one-month-ahead rounded rate in a stable 1.9-2.0 regime, the 80% central interval is kept near the realized one-decimal grid rather than widened mechanically. Applying 1.90 +/- 0.123 gives 1.78 to 2.02, rounded to the BLS one-decimal reporting grid as 1.8 to 2.0.","Counter-consideration and falsification: upside risk is a June rebound in accommodation, retail, or professional-services quits that would land above the interval at 2.1 percent or higher. Downside risk is a broader cooling in worker confidence after weak payroll growth that would land below the interval at 1.7 percent or lower. Central case is another 1.9 percent print because BLS rounding absorbs small latent changes."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool call: Read BLS JOLTS Table 2 for hires-rate context relevant to quits momentum.","Level, momentum, and mechanism split: the level effect is stable because May quits were 3,065 thousand and the total quits rate stayed at 1.9 percent. Momentum is flat after Apr-May showed 0.0 rate change. The policy and labor-market mechanism is mixed: June payroll growth and unemployment are contextual inputs, not direct components of the JOLTS release; payroll growth softened, but unemployment remained low enough that voluntary quits should not collapse."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, and mechanism split: the level effect is stable because May quits were 3,065 thousand and the total quits rate stayed at 1.9 percent. Momentum is flat after Apr-May showed 0.0 rate change. The policy and labor-market mechanism is mixed: June payroll growth and unemployment are contextual inputs, not direct components of the JOLTS release; payroll growth softened, but unemployment remained low enough that voluntary quits should not collapse.","Prior/update/interval: persistence prior uses the latest official May 2026 quits rate of 1.9 percent and the Jan-May reference-class mean of (2.0 + 1.9 + 2.0 + 1.9 + 1.9) / 5 = 1.94 percent; adjustment components are -0.03 point for slower June payroll growth, +0.01 point for still-low 4.2 percent unemployment, and -0.02 point for flat May hires and quits, leaving 1.90 percent after rounding. Interval method uses successive changes from fetched Jan-May history: -0.1, +0.1, -0.1, 0.0, so sample sigma = 0.096 percentage point and 1.28*sigma = 0.123. This is a short rounded recent-volatility sample, but for a one-month-ahead rounded rate in a stable 1.9-2.0 regime, the 80% central interval is kept near the realized one-decimal grid rather than widened mechanically. Applying 1.90 +/- 0.123 gives 1.78 to 2.02, rounded to the BLS one-decimal reporting grid as 1.8 to 2.0."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for June 2026 BLS JOLTS quits rate","Prior/update/interval: persistence prior uses the latest official May 2026 quits rate of 1.9 percent and the Jan-May reference-class mean of (2.0 + 1.9 + 2.0 + 1.9 + 1.9) / 5 = 1.94 percent; adjustment components are -0.03 point for slower June payroll growth, +0.01 point for still-low 4.2 percent unemployment, and -0.02 point for flat May hires and quits, leaving 1.90 percent after rounding. Interval method uses successive changes from fetched Jan-May history: -0.1, +0.1, -0.1, 0.0, so sample sigma = 0.096 percentage point and 1.28*sigma = 0.123. This is a short rounded recent-volatility sample, but for a one-month-ahead rounded rate in a stable 1.9-2.0 regime, the 80% central interval is kept near the realized one-decimal grid rather than widened mechanically. Applying 1.90 +/- 0.123 gives 1.78 to 2.02, rounded to the BLS one-decimal reporting grid as 1.8 to 2.0."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: jolts-quits-rate-june-2026\nrunLabel: Headline\nresolutionDate: 2026-08-04\ntraceLineCount: 18\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-nonfarm-productivity-q2-2026-prelim.2026-07-07T14-11-49Z.746314ef37dc258f","runId":"run.us-nonfarm-productivity-q2-2026-prelim.2026-07-07T14-11-49Z.746314ef37dc258f","predictionId":"us-nonfarm-productivity-q2-2026-prelim","specId":"spec.us-nonfarm-productivity-q2-2026-prelim","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate / reference class: recent nonfarm business productivity prints remain volatile around a positive center. The last twelve annualized changes computed from the official PRS85006093 index are 4.07, 5.06, 3.94, 0.23, 3.71, 3.68, 1.42, -0.88, 4.19, 5.21, 1.58, and 0.29 percent, with an average of 2.71 percent; the last eight average 2.40 percent.","Prior/update/interval: persistence/reference-class prior is the recent-eight PRS85006093 annualized productivity-growth mean of 2.40 from 2024 Q2 through 2026 Q1. Adjustment components: Q1 revised productivity at 0.3 argues -0.5 from the prior because the most recent output-hours balance was much weaker than the eight-quarter mean; soft June payrolls and low aggregate-hours growth argue +0.2 through the hours denominator; and a judgmental -0.7 is applied for Q2 output risk because the available labor-market evidence shows slower hiring while no official Q2 output print is available to confirm that output growth held near the 2025 pace. This gives 2.40 - 0.5 + 0.2 - 0.7 = 1.4. Interval method: use realized dispersion of the eight same-variant annualized values; sigma = 2.11, so 80 percent half-width is roughly 1.28*sigma = 1.28*2.11 = 2.70, rounded to 2.7. The eight-quarter volatility sample is small, so this is an approximate dispersion interval, not a fully calibrated model interval. Final implied bounds are 1.4 - 2.7 = -1.3 and 1.4 + 2.7 = 4.1."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing and exact resolver: the target is BLS Productivity and Costs Table 2, nonfarm business sector labor productivity, seasonally adjusted percent change from previous quarter at an annual rate, 2026 Q2 preliminary first print. The release variant is nonfarm business, not total business, and all productivity anchors below use the same BLS nonfarm business Table 2 or PRS85006093 index variant.","Tool call: BLS release calendar lookup for Productivity and Costs 2026 Q2 preliminary"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: the target is BLS Productivity and Costs Table 2, nonfarm business sector labor productivity, seasonally adjusted percent change from previous quarter at an annual rate, 2026 Q2 preliminary first print. The release variant is nonfarm business, not total business, and all productivity anchors below use the same BLS nonfarm business Table 2 or PRS85006093 index variant.","Tool call: BLS release calendar lookup for Productivity and Costs 2026 Q2 preliminary"]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5.4, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence/reference-class prior is the recent-eight PRS85006093 annualized productivity-growth mean of 2.40 from 2024 Q2 through 2026 Q1. Adjustment components: Q1 revised productivity at 0.3 argues -0.5 from the prior because the most recent output-hours balance was much weaker than the eight-quarter mean; soft June payrolls and low aggregate-hours growth argue +0.2 through the hours denominator; and a judgmental -0.7 is applied for Q2 output risk because the available labor-market evidence shows slower hiring while no official Q2 output print is available to confirm that output growth held near the 2025 pace. This gives 2.40 - 0.5 + 0.2 - 0.7 = 1.4. Interval method: use realized dispersion of the eight same-variant annualized values; sigma = 2.11, so 80 percent half-width is roughly 1.28*sigma = 1.28*2.11 = 2.70, rounded to 2.7. The eight-quarter volatility sample is small, so this is an approximate dispersion interval, not a fully calibrated model interval. Final implied bounds are 1.4 - 2.7 = -1.3 and 1.4 + 2.7 = 4.1.","Counter-considerations: upside risk is a Q2 output print near or above 3 percent annualized paired with flat or falling nonfarm business hours, which would land above the interval if productivity exceeds 4.1. Downside risk is output around zero or negative while hours rise more than 1 percent annualized, which would land below the interval if productivity is below -1.3. An outside the interval outcome is plausible because quarterly productivity has frequent output and hours revisions, but the interval is anchored to the observed same-series dispersion."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Prior/update/interval: persistence/reference-class prior is the recent-eight PRS85006093 annualized productivity-growth mean of 2.40 from 2024 Q2 through 2026 Q1. Adjustment components: Q1 revised productivity at 0.3 argues -0.5 from the prior because the most recent output-hours balance was much weaker than the eight-quarter mean; soft June payrolls and low aggregate-hours growth argue +0.2 through the hours denominator; and a judgmental -0.7 is applied for Q2 output risk because the available labor-market evidence shows slower hiring while no official Q2 output print is available to confirm that output growth held near the 2025 pace. This gives 2.40 - 0.5 + 0.2 - 0.7 = 1.4. Interval method: use realized dispersion of the eight same-variant annualized values; sigma = 2.11, so 80 percent half-width is roughly 1.28*sigma = 1.28*2.11 = 2.70, rounded to 2.7. The eight-quarter volatility sample is small, so this is an approximate dispersion interval, not a fully calibrated model interval. Final implied bounds are 1.4 - 2.7 = -1.3 and 1.4 + 2.7 = 4.1.","Counter-considerations: upside risk is a Q2 output print near or above 3 percent annualized paired with flat or falling nonfarm business hours, which would land above the interval if productivity exceeds 4.1. Downside risk is output around zero or negative while hours rise more than 1 percent annualized, which would land below the interval if productivity is below -1.3. An outside the interval outcome is plausible because quarterly productivity has frequent output and hours revisions, but the interval is anchored to the observed same-series dispersion."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Prior/update/interval: persistence/reference-class prior is the recent-eight PRS85006093 annualized productivity-growth mean of 2.40 from 2024 Q2 through 2026 Q1. Adjustment components: Q1 revised productivity at 0.3 argues -0.5 from the prior because the most recent output-hours balance was much weaker than the eight-quarter mean; soft June payrolls and low aggregate-hours growth argue +0.2 through the hours denominator; and a judgmental -0.7 is applied for Q2 output risk because the available labor-market evidence shows slower hiring while no official Q2 output print is available to confirm that output growth held near the 2025 pace. This gives 2.40 - 0.5 + 0.2 - 0.7 = 1.4. Interval method: use realized dispersion of the eight same-variant annualized values; sigma = 2.11, so 80 percent half-width is roughly 1.28*sigma = 1.28*2.11 = 2.70, rounded to 2.7. The eight-quarter volatility sample is small, so this is an approximate dispersion interval, not a fully calibrated model interval. Final implied bounds are 1.4 - 2.7 = -1.3 and 1.4 + 2.7 = 4.1.","Counter-considerations: upside risk is a Q2 output print near or above 3 percent annualized paired with flat or falling nonfarm business hours, which would land above the interval if productivity exceeds 4.1. Downside risk is output around zero or negative while hours rise more than 1 percent annualized, which would land below the interval if productivity is below -1.3. An outside the interval outcome is plausible because quarterly productivity has frequent output and hours revisions, but the interval is anchored to the observed same-series dispersion."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["US nonfarm business productivity Q2 2026 preliminary forecast","Prior/update/interval: persistence/reference-class prior is the recent-eight PRS85006093 annualized productivity-growth mean of 2.40 from 2024 Q2 through 2026 Q1. Adjustment components: Q1 revised productivity at 0.3 argues -0.5 from the prior because the most recent output-hours balance was much weaker than the eight-quarter mean; soft June payrolls and low aggregate-hours growth argue +0.2 through the hours denominator; and a judgmental -0.7 is applied for Q2 output risk because the available labor-market evidence shows slower hiring while no official Q2 output print is available to confirm that output growth held near the 2025 pace. This gives 2.40 - 0.5 + 0.2 - 0.7 = 1.4. Interval method: use realized dispersion of the eight same-variant annualized values; sigma = 2.11, so 80 percent half-width is roughly 1.28*sigma = 1.28*2.11 = 2.70, rounded to 2.7. The eight-quarter volatility sample is small, so this is an approximate dispersion interval, not a fully calibrated model interval. Final implied bounds are 1.4 - 2.7 = -1.3 and 1.4 + 2.7 = 4.1."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-nonfarm-productivity-q2-2026-prelim\nrunLabel: Headline\nresolutionDate: 2026-08-06\ntraceLineCount: 15\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.us-telework-rate-july-2026.2026-07-07T14-07-57Z.eeb1dd97d996cbf7","runId":"run.us-telework-rate-july-2026.2026-07-07T14-07-57Z.eeb1dd97d996cbf7","predictionId":"us-telework-rate-july-2026","specId":"spec.us-telework-rate-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 3 historical point(s) and explicit outside-view language.","evidence":["Tool call: Checked a public report quoting BLS telework-rate values from the August 2024 jobs report and prior-year comparison.","Reference class/base rate: post-2023 BLS CPS telework shares appear centered in the low-20s percent range. The latest official A-41 value, 21.7 percent in June 2026, is below the August 2024 public report of 22.8 percent but above the August 2023 19.5 percent level, so persistence near 22 percent is a stronger prior than a pandemic-style trend extrapolation."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["The resolver is BLS CPS Table A-41, not seasonally adjusted, row Total, 16 years and over, percent distribution column for people who teleworked or worked at home for pay. This is the share of people at work, not the share of all employed people, and the table id is A-41.","Tool call: Opened BLS Employment Situation release schedule for 2026 and checked the July 2026 reference-month row."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["Tool call: Opened BLS Employment Situation release schedule for 2026 and checked the July 2026 reference-month row.","Tool result: BLS schedule lists July 2026 Employment Situation release date as Aug. 07, 2026 at 08:30 AM; June 2026 was Jul. 02, 2026 and August 2026 is Sep. 04, 2026."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 8, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior uses latest BLS A-41 June 2026 = 21.7, with sparse fetched reference-class values Aug 2023 = 19.5, Aug 2024 = 22.8, Jun 2026 = 21.7. Successive changes are +3.3 and -1.1 percentage points; sigma = 3.11 from the sample standard deviation of those sparse proxy changes, not a full monthly volatility history. I add a judgmental +0.1 point for mild July/hybrid persistence, giving 21.8. The 80% half-width is roughly 1.28*sigma = 1.28*3.11 = 3.98, rounded to 4.0, so the interval is 21.8 +/- 4.0 = 17.8 to 25.8; this width is retained because the target is not seasonally adjusted and the fetched official/public reference points already span several post-2023 points.","Counter-consideration and falsification: upside risk would be a July jump in remote-capable professional work or summer scheduling that pushes the A-41 share above 25.8. Downside risk would be broad return-to-office enforcement or a July shift toward onsite service work that pulls the print below 17.8. Values outside the interval would exceed the limited fetched reference-class variation, rather than a full official monthly volatility sample."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, and mechanism split: the level anchor is 21.7. Momentum is weakly flat to slightly positive because June is not unusually high relative to the 2024 reference. One-off effects are limited; July vacations and school schedules can move not-seasonally-adjusted work-at-home status, but the target is broad enough that occupational composition and hybrid policies dominate. Labor-market softening is a mild downside mechanism if employers enforce office attendance more aggressively.","Prior/update/interval: persistence prior uses latest BLS A-41 June 2026 = 21.7, with sparse fetched reference-class values Aug 2023 = 19.5, Aug 2024 = 22.8, Jun 2026 = 21.7. Successive changes are +3.3 and -1.1 percentage points; sigma = 3.11 from the sample standard deviation of those sparse proxy changes, not a full monthly volatility history. I add a judgmental +0.1 point for mild July/hybrid persistence, giving 21.8. The 80% half-width is roughly 1.28*sigma = 1.28*3.11 = 3.98, rounded to 4.0, so the interval is 21.8 +/- 4.0 = 17.8 to 25.8; this width is retained because the target is not seasonally adjusted and the fetched official/public reference points already span several post-2023 points."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["The resolver is BLS CPS Table A-41, not seasonally adjusted, row Total, 16 years and over, percent distribution column for people who teleworked or worked at home for pay. This is the share of people at work, not the share of all employed people, and the table id is A-41.","Tool result: BLS A-41 June 2026 reports total people at work 155,218 thousand, people who teleworked or worked at home for pay 33,701 thousand, teleworked some hours 17,161 thousand, teleworked all hours 16,540 thousand, and percent distribution 21.7 total, 11.1 some hours, 10.7 all hours, 78.3 did not telework."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Prior/update/interval: persistence prior uses latest BLS A-41 June 2026 = 21.7, with sparse fetched reference-class values Aug 2023 = 19.5, Aug 2024 = 22.8, Jun 2026 = 21.7. Successive changes are +3.3 and -1.1 percentage points; sigma = 3.11 from the sample standard deviation of those sparse proxy changes, not a full monthly volatility history. I add a judgmental +0.1 point for mild July/hybrid persistence, giving 21.8. The 80% half-width is roughly 1.28*sigma = 1.28*3.11 = 3.98, rounded to 4.0, so the interval is 21.8 +/- 4.0 = 17.8 to 25.8; this width is retained because the target is not seasonally adjusted and the fetched official/public reference points already span several post-2023 points.","Counter-consideration and falsification: upside risk would be a July jump in remote-capable professional work or summer scheduling that pushes the A-41 share above 25.8. Downside risk would be broad return-to-office enforcement or a July shift toward onsite service work that pulls the print below 17.8. Values outside the interval would exceed the limited fetched reference-class variation, rather than a full official monthly volatility sample."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: us-telework-rate-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-07\ntraceLineCount: 16\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.ssi-recipients-july-2026.2026-07-07T14-15-30Z.3087b22656bab1d6","runId":"run.ssi-recipients-july-2026.2026-07-07T14-15-30Z.3087b22656bab1d6","predictionId":"ssi-recipients-july-2026","specId":"spec.ssi-recipients-july-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 6 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the reference class is recent first-print SSA SSI Monthly Statistics total-recipient levels from May 2025 through May 2026. The last print is 7.322937 million, while the 2026 sequence has declined every month from 7.369510 million in January to 7.322937 million in May, so a pure persistence prior is too high unless current evidence points to a rebound.","Prior/update/interval: persistence prior is last-print persistence at 7.322937 million, but the reference class of fetched SSA total-recipient values supports a two-month trend update because the July target is two months after the May latest print. The two-month changes in the fetched sample are -0.014291, -0.006823, +0.041812, -0.012329, -0.045513, -0.001205, -0.021666, -0.033288, -0.017685, -0.020781, and -0.028888 million; their mean is -0.014605 million, so the point is 7.322937 - 0.014605 = 7.308332 million, rounded to 7.309. Interval method uses realized dispersion of those two-month changes; sigma = 0.022437 million, and an 80% interval is approximately +/-1.28 standard deviations, so 1.28*sigma = 0.028719 million, giving implied bounds 7.279613 to 7.337051, rounded to 7.280 and 7.338."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 4 typed tool call(s), 4 source-context item(s), activity log present.","evidence":["Tool call: Opened SSA publishing schedule and current SSI publications to verify release timing and target source family.","Tool result: Fetched official timing evidence on July 7, 2026: SSA Publishing Schedule lists SSI Monthly Statistics with frequency Monthly; current SSI Monthly Statistics page is May 2026 and says released June 2026; current Monthly Statistical Snapshot is May 2026 and says released June 2026. The July 2026 SSI monthly first print is therefore tied to the SSA monthly publication expected by August 2026; 2026-08-31 is used as the catalog latest expected resolution by-date because the public schedule provides month-level, not day-level, timing."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Tool call: Opened SSA publishing schedule and current SSI publications to verify release timing and target source family.","Tool result: Fetched official timing evidence on July 7, 2026: SSA Publishing Schedule lists SSI Monthly Statistics with frequency Monthly; current SSI Monthly Statistics page is May 2026 and says released June 2026; current Monthly Statistical Snapshot is May 2026 and says released June 2026. The July 2026 SSI monthly first print is therefore tied to the SSA monthly publication expected by August 2026; 2026-08-31 is used as the catalog latest expected resolution by-date because the public schedule provides month-level, not day-level, timing."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 0.06, distribution present, forecast step count 1.","evidence":["Level, momentum, one-off, and policy split: the level is a mature administrative caseload near 7.3 million, not a fast cyclical series. Momentum is downward: January-May 2026 fell by 0.046573 million, and March-May fell by 0.028888 million. I found no official public evidence in the checked SSA release context of a July 2026 policy mechanism that would abruptly expand or contract SSI eligibility; the main one-off risk is administrative timing and returned-check adjustment in the first two months after release.","Prior/update/interval: persistence prior is last-print persistence at 7.322937 million, but the reference class of fetched SSA total-recipient values supports a two-month trend update because the July target is two months after the May latest print. The two-month changes in the fetched sample are -0.014291, -0.006823, +0.041812, -0.012329, -0.045513, -0.001205, -0.021666, -0.033288, -0.017685, -0.020781, and -0.028888 million; their mean is -0.014605 million, so the point is 7.322937 - 0.014605 = 7.308332 million, rounded to 7.309. Interval method uses realized dispersion of those two-month changes; sigma = 0.022437 million, and an 80% interval is approximately +/-1.28 standard deviations, so 1.28*sigma = 0.028719 million, giving implied bounds 7.279613 to 7.337051, rounded to 7.280 and 7.338."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Tool result: Fetched official timing evidence on July 7, 2026: SSA Publishing Schedule lists SSI Monthly Statistics with frequency Monthly; current SSI Monthly Statistics page is May 2026 and says released June 2026; current Monthly Statistical Snapshot is May 2026 and says released June 2026. The July 2026 SSI monthly first print is therefore tied to the SSA monthly publication expected by August 2026; 2026-08-31 is used as the catalog latest expected resolution by-date because the public schedule provides month-level, not day-level, timing.","Level, momentum, one-off, and policy split: the level is a mature administrative caseload near 7.3 million, not a fast cyclical series. Momentum is downward: January-May 2026 fell by 0.046573 million, and March-May fell by 0.028888 million. I found no official public evidence in the checked SSA release context of a July 2026 policy mechanism that would abruptly expand or contract SSI eligibility; the main one-off risk is administrative timing and returned-check adjustment in the first two months after release."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Level, momentum, one-off, and policy split: the level is a mature administrative caseload near 7.3 million, not a fast cyclical series. Momentum is downward: January-May 2026 fell by 0.046573 million, and March-May fell by 0.028888 million. I found no official public evidence in the checked SSA release context of a July 2026 policy mechanism that would abruptly expand or contract SSI eligibility; the main one-off risk is administrative timing and returned-check adjustment in the first two months after release.","Prior/update/interval: persistence prior is last-print persistence at 7.322937 million, but the reference class of fetched SSA total-recipient values supports a two-month trend update because the July target is two months after the May latest print. The two-month changes in the fetched sample are -0.014291, -0.006823, +0.041812, -0.012329, -0.045513, -0.001205, -0.021666, -0.033288, -0.017685, -0.020781, and -0.028888 million; their mean is -0.014605 million, so the point is 7.322937 - 0.014605 = 7.308332 million, rounded to 7.309. Interval method uses realized dispersion of those two-month changes; sigma = 0.022437 million, and an 80% interval is approximately +/-1.28 standard deviations, so 1.28*sigma = 0.028719 million, giving implied bounds 7.279613 to 7.337051, rounded to 7.280 and 7.338."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Base rate/reference class: the reference class is recent first-print SSA SSI Monthly Statistics total-recipient levels from May 2025 through May 2026. The last print is 7.322937 million, while the 2026 sequence has declined every month from 7.369510 million in January to 7.322937 million in May, so a pure persistence prior is too high unless current evidence points to a rebound.","Prior/update/interval: persistence prior is last-print persistence at 7.322937 million, but the reference class of fetched SSA total-recipient values supports a two-month trend update because the July target is two months after the May latest print. The two-month changes in the fetched sample are -0.014291, -0.006823, +0.041812, -0.012329, -0.045513, -0.001205, -0.021666, -0.033288, -0.017685, -0.020781, and -0.028888 million; their mean is -0.014605 million, so the point is 7.322937 - 0.014605 = 7.308332 million, rounded to 7.309. Interval method uses realized dispersion of those two-month changes; sigma = 0.022437 million, and an 80% interval is approximately +/-1.28 standard deviations, so 1.28*sigma = 0.028719 million, giving implied bounds 7.279613 to 7.337051, rounded to 7.280 and 7.338."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: ssi-recipients-july-2026\nrunLabel: Headline\nresolutionDate: 2026-08-31\ntraceLineCount: 17\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-enrollment-april-2027-work-req-deadline-delayed.2026-07-07T16-14-56Z.d53e2d845ea6fe8a","runId":"run.medicaid-enrollment-april-2027-work-req-deadline-delayed.2026-07-07T16-14-56Z.d53e2d845ea6fe8a","predictionId":"medicaid-enrollment-april-2027-work-req-deadline-delayed","specId":"spec.medicaid-enrollment-april-2027-work-req-deadline-delayed","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base rate/reference class: the closest reference class is the CMS monthly national Total Medicaid and CHIP Enrollment series. The November 2025 through February 2026 preliminary sequence is smooth at 78.620, 78.468, 78.312, and 78.184 million. The March 2026 CMS highlight value of 74.294361 million is the latest official level; because it is a highlight-page total rather than the same extracted preliminary table row used for the historical sequence, I treat it as the current official anchor but allow extra interval width for possible comparability or reporting discontinuity.","Prior/update/interval: prior model is latest-official-level persistence with delayed-policy baseline drift, using comparable preliminary fetched history of 78.620, 78.468, 78.312, and 78.184 million for ordinary month-to-month dispersion and the March 2026 official highlight level of 74.294361 million as the current anchor. Comparable successive changes are -0.152, -0.156, and -0.128 million; sample sigma = 0.015 million, so the mechanical 80% half-width is 1.28*sigma = 0.02 million. The -1.15 million drift is roughly the recent ordinary attrition pace annualized over the 13-month horizon with some post-unwinding slowing; the +0.25 million policy component reflects avoided early work-requirement disenrollment under the condition; the -0.49 million component allows for non-work-requirement eligibility, income, and reporting risks from the 2025 law. I widen far beyond the 0.02 million monthly-volatility half-width to 3.00 million by using a horizon-scaled persistence model plus explicit discontinuity and policy-shock allowance: ordinary monthly noise is tiny, but first-print state reporting, a possible March 2026 comparability break, and implementation uncertainty can plausibly move national enrollment by low single-digit millions. Point update is 74.294361 - 1.15 + 0.25 - 0.49 = 72.904361."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 6 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Framing and exact resolver: the target is the preliminary April 2027 first-print national Total Medicaid and CHIP Enrollment field in CMS monthly Medicaid and CHIP enrollment data, converted from persons to millions. The catalog series name says Medicaid total enrollment, but the official resolver is CMS Total Medicaid and CHIP Enrollment, not Medicaid-only enrollment, unless the ledger is corrected.","Tool call: Opened Medicaid.gov March 2026 Medicaid and CHIP Enrollment Data Highlights for the current official level and series definition."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: the target is the preliminary April 2027 first-print national Total Medicaid and CHIP Enrollment field in CMS monthly Medicaid and CHIP enrollment data, converted from persons to millions. The catalog series name says Medicaid total enrollment, but the official resolver is CMS Total Medicaid and CHIP Enrollment, not Medicaid-only enrollment, unless the ledger is corrected.","Tool call: Opened the Medicaid.gov monthly enrollment reports page for release vehicle and current first-print availability evidence."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6, distribution present, forecast step count 1.","evidence":["Tool call: Inspected a public generated Thesis artifact derived from official CMS data only to recover recent preliminary-reference-class observations, excluding any catalog forecast point estimates or intervals.","Base rate/reference class: the closest reference class is the CMS monthly national Total Medicaid and CHIP Enrollment series. The November 2025 through February 2026 preliminary sequence is smooth at 78.620, 78.468, 78.312, and 78.184 million. The March 2026 CMS highlight value of 74.294361 million is the latest official level; because it is a highlight-page total rather than the same extracted preliminary table row used for the historical sequence, I treat it as the current official anchor but allow extra interval width for possible comparability or reporting discontinuity."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base rate/reference class: the closest reference class is the CMS monthly national Total Medicaid and CHIP Enrollment series. The November 2025 through February 2026 preliminary sequence is smooth at 78.620, 78.468, 78.312, and 78.184 million. The March 2026 CMS highlight value of 74.294361 million is the latest official level; because it is a highlight-page total rather than the same extracted preliminary table row used for the historical sequence, I treat it as the current official anchor but allow extra interval width for possible comparability or reporting discontinuity.","Level, momentum, one-off, and policy-mechanism split: level starts at 74.294361 million. Momentum is modestly negative after unwinding and normal renewal churn. The conditional delay removes the direct January-April 2027 community-engagement compliance shock, so I do not subtract a large work-requirement disenrollment pulse. Remaining downside comes from routine redeterminations, income churn, other law-driven eligibility changes, and state reporting cleanups; support comes from child continuous eligibility, retroactive or late processing, and ordinary population inflow."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Framing and exact resolver: the target is the preliminary April 2027 first-print national Total Medicaid and CHIP Enrollment field in CMS monthly Medicaid and CHIP enrollment data, converted from persons to millions. The catalog series name says Medicaid total enrollment, but the official resolver is CMS Total Medicaid and CHIP Enrollment, not Medicaid-only enrollment, unless the ledger is corrected.","Base rate/reference class: the closest reference class is the CMS monthly national Total Medicaid and CHIP Enrollment series. The November 2025 through February 2026 preliminary sequence is smooth at 78.620, 78.468, 78.312, and 78.184 million. The March 2026 CMS highlight value of 74.294361 million is the latest official level; because it is a highlight-page total rather than the same extracted preliminary table row used for the historical sequence, I treat it as the current official anchor but allow extra interval width for possible comparability or reporting discontinuity."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast April 2027 CMS Medicaid and CHIP enrollment under delayed work requirement","Tool call: Inspected a public generated Thesis artifact derived from official CMS data only to recover recent preliminary-reference-class observations, excluding any catalog forecast point estimates or intervals."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-enrollment-april-2027-work-req-deadline-delayed\nrunLabel: Headline\nresolutionDate: 2027-07-31\ntraceLineCount: 21\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.medicaid-enrollment-april-2027-work-req-deadline-holds.2026-07-07T16-10-34Z.5c6890a140d95e55","runId":"run.medicaid-enrollment-april-2027-work-req-deadline-holds.2026-07-07T16-10-34Z.5c6890a140d95e55","predictionId":"medicaid-enrollment-april-2027-work-req-deadline-holds","specId":"spec.medicaid-enrollment-april-2027-work-req-deadline-holds","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool call: Checked the CMS monthly snapshot index for release timing and the historical April reporting-period example.","Base rate/reference class: the recent official-source reference class is the post-unwinding monthly CMS Performance Indicator Data series from October 2025 through March 2026. It fell from 76.8 million in October 2025 to 74.294 million in March 2026, a five-month drop of about 2.5 million, but the series is still transitioning and includes the March 2026 California reporting revision noted by CMS."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 6 source-context item(s), activity log present.","evidence":["Framing and exact resolver: this is the CMS preliminary Performance Indicator Data national Total Medicaid and CHIP Enrollment count for April 2027, converted to millions. I treat the ledger target as resolving to CMS national Total Medicaid and CHIP Enrollment despite the cms.medicaid.total_enrollment slug; that is a ledger-label discrepancy, not an independent change to the target. The target is a national total for the 50 states and DC, not a weighted average, state row, BHP count, or T-MSIS separate CHIP variant. I use the fixed-vintage first monthly print and ignore later revisions.","Tool call: Checked CMS February 2026 and January 2026 Eligibility Operations and Enrollment Snapshot PDFs for recent monthly levels and renewal conditions."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["Framing and exact resolver: this is the CMS preliminary Performance Indicator Data national Total Medicaid and CHIP Enrollment count for April 2027, converted to millions. I treat the ledger target as resolving to CMS national Total Medicaid and CHIP Enrollment despite the cms.medicaid.total_enrollment slug; that is a ledger-label discrepancy, not an independent change to the target. The target is a national total for the 50 states and DC, not a weighted average, state row, BHP count, or T-MSIS separate CHIP variant. I use the fixed-vintage first monthly print and ignore later revisions.","Tool call: Checked the CMS monthly snapshot index for release timing and the historical April reporting-period example."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 5.8, distribution present, forecast step count 1.","evidence":["Prior/update/interval: persistence prior = March 2026 level 74.294 with a simple time-series prior, not a formal fitted model, using the October 2025-March 2026 historical sample. Adjustment components are -3.7 million ordinary drift through April 2027, equal to about -0.285 million per month and damped from the recent -0.50 million per month post-unwinding decline; -1.4 million early community-engagement net disenrollment; and -0.4 million reporting/administrative noise, giving 74.294 - 3.7 - 1.4 - 0.4 = 68.8 million. Interval method starts with successive monthly changes from rounded official levels: Oct-Nov -0.8, Nov-Dec -0.3, Dec-Jan -0.4, Jan-Feb -0.4, Feb-Mar -0.606 million, so sigma = 0.20 million and 1.28*sigma = 0.26 million for one-month noise. I widen far beyond that to +/-2.9 million because the target is 13 months ahead and conditioned on a new national eligibility-compliance regime: the +/-1.5 million drift error is a judgmental stress component for whether post-unwinding attrition stalls or persists, the +/-2.0 million implementation error reflects uncertainty in how fast large states process community-engagement compliance by the fourth month, and the +/-0.8 million first-print/reporting risk reflects preliminary-state reporting and one-off revisions like the California reporting issue. Root-sum-square of 1.5, 2.0, and 0.8 is about 2.6 million, rounded up to a symmetric +/-2.9 million interval for asymmetric state timing risk.","Counter-consideration: upside risk is that implementation is administratively slow, many adults qualify for exemptions, and late-2026 Medicaid losses stabilize, which would land above the interval near 72 million or more. Downside risk is that several large expansion states enforce compliance aggressively from January 2027 while ordinary renewal churn continues, which would land below the interval near 65 million or less. Outside the interval would likely require either broad implementation failure/delay without triggering the condition, or a sharper-than-expected early disenrollment wave concentrated in large states."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Level, momentum, one-off, and policy effects: the latest level is 74.294 million. The October 2025 to March 2026 drop implies about -0.50 million per month; extending that mechanically for 13 months would imply roughly -6.5 million and a level near 67.8 million before explicit policy effects, so I damp the ordinary drift to about -0.285 million per month, or -3.7 million total, because unwinding attrition should slow and the March California limited-benefit reporting revision is a level shift rather than a recurring trend. The community-engagement mechanism adds adult Medicaid losses after January 1, 2027, but April 2027 is an early reporting period, so state notices, exemptions, appeals, and system timing limit the full effect in the first print.","Prior/update/interval: persistence prior = March 2026 level 74.294 with a simple time-series prior, not a formal fitted model, using the October 2025-March 2026 historical sample. Adjustment components are -3.7 million ordinary drift through April 2027, equal to about -0.285 million per month and damped from the recent -0.50 million per month post-unwinding decline; -1.4 million early community-engagement net disenrollment; and -0.4 million reporting/administrative noise, giving 74.294 - 3.7 - 1.4 - 0.4 = 68.8 million. Interval method starts with successive monthly changes from rounded official levels: Oct-Nov -0.8, Nov-Dec -0.3, Dec-Jan -0.4, Jan-Feb -0.4, Feb-Mar -0.606 million, so sigma = 0.20 million and 1.28*sigma = 0.26 million for one-month noise. I widen far beyond that to +/-2.9 million because the target is 13 months ahead and conditioned on a new national eligibility-compliance regime: the +/-1.5 million drift error is a judgmental stress component for whether post-unwinding attrition stalls or persists, the +/-2.0 million implementation error reflects uncertainty in how fast large states process community-engagement compliance by the fourth month, and the +/-0.8 million first-print/reporting risk reflects preliminary-state reporting and one-off revisions like the California reporting issue. Root-sum-square of 1.5, 2.0, and 0.8 is about 2.6 million, rounded up to a symmetric +/-2.9 million interval for asymmetric state timing risk."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Base rate/reference class: the recent official-source reference class is the post-unwinding monthly CMS Performance Indicator Data series from October 2025 through March 2026. It fell from 76.8 million in October 2025 to 74.294 million in March 2026, a five-month drop of about 2.5 million, but the series is still transitioning and includes the March 2026 California reporting revision noted by CMS.","Level, momentum, one-off, and policy effects: the latest level is 74.294 million. The October 2025 to March 2026 drop implies about -0.50 million per month; extending that mechanically for 13 months would imply roughly -6.5 million and a level near 67.8 million before explicit policy effects, so I damp the ordinary drift to about -0.285 million per month, or -3.7 million total, because unwinding attrition should slow and the March California limited-benefit reporting revision is a level shift rather than a recurring trend. The community-engagement mechanism adds adult Medicaid losses after January 1, 2027, but April 2027 is an early reporting period, so state notices, exemptions, appeals, and system timing limit the full effect in the first print."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for April 2027 Medicaid and CHIP enrollment if the work-requirement deadline holds","Prior/update/interval: persistence prior = March 2026 level 74.294 with a simple time-series prior, not a formal fitted model, using the October 2025-March 2026 historical sample. Adjustment components are -3.7 million ordinary drift through April 2027, equal to about -0.285 million per month and damped from the recent -0.50 million per month post-unwinding decline; -1.4 million early community-engagement net disenrollment; and -0.4 million reporting/administrative noise, giving 74.294 - 3.7 - 1.4 - 0.4 = 68.8 million. Interval method starts with successive monthly changes from rounded official levels: Oct-Nov -0.8, Nov-Dec -0.3, Dec-Jan -0.4, Jan-Feb -0.4, Feb-Mar -0.606 million, so sigma = 0.20 million and 1.28*sigma = 0.26 million for one-month noise. I widen far beyond that to +/-2.9 million because the target is 13 months ahead and conditioned on a new national eligibility-compliance regime: the +/-1.5 million drift error is a judgmental stress component for whether post-unwinding attrition stalls or persists, the +/-2.0 million implementation error reflects uncertainty in how fast large states process community-engagement compliance by the fourth month, and the +/-0.8 million first-print/reporting risk reflects preliminary-state reporting and one-off revisions like the California reporting issue. Root-sum-square of 1.5, 2.0, and 0.8 is about 2.6 million, rounded up to a symmetric +/-2.9 million interval for asymmetric state timing risk."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: medicaid-enrollment-april-2027-work-req-deadline-holds\nrunLabel: Headline\nresolutionDate: 2027-09-30\ntraceLineCount: 20\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.child-poverty-2028-given-tcja-extended-q2-2026.2026-06-08T00-00-00-02-00.9231738c6db10a04","runId":"run.child-poverty-2028-given-tcja-extended-q2-2026.2026-06-08T00-00-00-02-00.9231738c6db10a04","predictionId":"child-poverty-2028-given-tcja-extended-q2-2026","specId":"spec.child-poverty-2028-given-tcja-extended-q2-2026","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.05,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool call: policyengine.simulate({ scenario: \"tcja_extended_full\", year: 2028, output: \"spm_child_poverty_rate\", population: \"microplex.us.2028\", macro: \"cbo_baseline_2028\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 3 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.5, distribution present, forecast step count 1.","evidence":["Residual uncertainty","The conditioning event removes most policy uncertainty but does not remove macro uncertainty (labor market, food/shelter inflation in SPM thresholds). CI reflects macro distribution only."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Two years of stable policy compound modestly: real-wage growth at the lower end of the distribution lifts roughly 0.2pp of children out of measured poverty. Refundable-credit take-up rates also drift up slightly as IRS outreach matures.","Residual uncertainty"]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 11.3, ci80: [10.4, 12.3] }","Tool result: { point: 11.5, ci80: [10.3, 12.7] }"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: child-poverty-2028-given-tcja-extended-q2-2026\nrunLabel: Headline\nresolutionDate: 2029-09-15\ntraceLineCount: 14\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: resolution clarity (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.child-poverty-2028-given-tcja-extended-q2-2026.2026-06-27T14-25-13Z.child-poverty-2028-given-tcja-extended-q2-2026-thesis-analyst-fast-2026-06-27t14-25-13z.39e8f877c2f064c7","runId":"run.child-poverty-2028-given-tcja-extended-q2-2026.2026-06-27T14-25-13Z.child-poverty-2028-given-tcja-extended-q2-2026-thesis-analyst-fast-2026-06-27t14-25-13z.39e8f877c2f064c7","predictionId":"child-poverty-2028-given-tcja-extended-q2-2026","specId":"spec.child-poverty-2028-given-tcja-extended-q2-2026","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.78,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Tool call: Checked Census 2024 poverty report table list for the SPM age table and historical table identity.","Base-rate/reference-class anchor: the relevant prior is not a 2022-2024 child series because the draft evidence did not fetch the 2024 child value. I use 2022 and 2023 child SPM values plus the 2024 overall SPM signal. After the 2021 refundable-credit expansion expired, child SPM returned to low-to-mid teens, with 2021 at 5.2% treated as an exceptional policy year."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["Forecast for 2028 Census child SPM poverty under a TCJA House-framework extension","The resolver is the Census Bureau first-print Supplemental Poverty Measure poverty rate for people under 18 in calendar year 2028. This is not the official poverty measure: SPM resources include taxes and credits, in-kind transfers such as SNAP and housing assistance, and subtract work, child care, child support paid, and medical out-of-pocket expenses while applying housing-cost adjustments."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":4,"rationale":"Score 4/4 under the resolution clarity rubric.","evidence":["The resolver is the Census Bureau first-print Supplemental Poverty Measure poverty rate for people under 18 in calendar year 2028. This is not the official poverty measure: SPM resources include taxes and credits, in-kind transfers such as SNAP and housing assistance, and subtract work, child care, child support paid, and medical out-of-pocket expenses while applying housing-cost adjustments.","Tool call: Opened Census Poverty in the United States: 2024 publication page and press release."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 7.2, distribution present, forecast step count 1.","evidence":["Start with a post-expansion base of 13.0% to 13.3% from 12.4% in 2022, 13.7% in 2023, and the 12.9% overall SPM signal for 2024. Add about 0.4 percentage point for partial-refundable-credit limits versus a stronger anti-poverty design and about 0.5 point for likely transfer and expense headwinds under the House framework by 2028, giving 14.2%. The interval 10.8% to 18.0% allows roughly -3.4 to +3.8 points around the point, wider than the observed 2022-to-2023 child SPM move of 1.3 points because the horizon is four years, the target is conditional on fiscal legislation, and labor, housing, and medical-expense shocks can compound.","Review disposition: accepted the critique to avoid using the 2024 report URL as if it were the 2028 source, to rephrase the base rate as 2022-2023 child evidence plus a 2024 overall signal, to state a persistence prior instead of implying a formal model, and to tie the interval to observed movement plus policy uncertainty. I retained the same point forecast because the critique did not materially change the central evidence."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Base-rate/reference-class anchor: the relevant prior is not a 2022-2024 child series because the draft evidence did not fetch the 2024 child value. I use 2022 and 2023 child SPM values plus the 2024 overall SPM signal. After the 2021 refundable-credit expansion expired, child SPM returned to low-to-mid teens, with 2021 at 5.2% treated as an exceptional policy year.","Model prior: I am using a persistence/random-walk prior rather than a formal time-series model because the child SPM history is short, mechanically altered by large tax-credit changes, and the target is conditional on a major fiscal package. A persistence prior around the recent post-expansion level is more transparent than fitting a trend through policy breaks."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Policy mechanism: under the condition, a House-style TCJA extension prevents the child credit from falling back toward the pre-TCJA $1,000 structure, which is poverty-reducing versus expiration. But the extension is not the 2021 fully refundable CTC and therefore does much less for the lowest-income children than the ARPA design that produced the 5.2% child SPM rate.","Review disposition: accepted the critique to avoid using the 2024 report URL as if it were the 2028 source, to rephrase the base rate as 2022-2023 child evidence plus a 2024 overall signal, to state a persistence prior instead of implying a formal model, and to tie the interval to observed movement plus policy uncertainty. I retained the same point forecast because the critique did not materially change the central evidence."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for 2028 Census child SPM poverty under a TCJA House-framework extension","Tool result: Fetched 2023 publication date September 10, 2024; 2023 overall SPM rate 12.9%; 2023 child SPM poverty rate 13.7%; 2023 child SPM increase 1.3 percentage points from 2022."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: child-poverty-2028-given-tcja-extended-q2-2026\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2029-09-15\ntraceLineCount: 20\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.child-poverty-2026-given-ctc-3000-refundable.2026-06-08T00-00-00-02-00.0276d2627790a0e1","runId":"run.child-poverty-2026-given-ctc-3000-refundable.2026-06-08T00-00-00-02-00.0276d2627790a0e1","predictionId":"child-poverty-2026-given-ctc-3000-refundable","specId":"spec.child-poverty-2026-given-ctc-3000-refundable","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.92,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 5 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 2 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Tool call: census.lookup({ series: \"spm_child_poverty_rate\", years: [2021, 2024], note: \"expanded CTC anchor\" })"]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 3.2, distribution present, forecast step count 1.","evidence":["This cell asks what the observed SPM child poverty rate would be if the $3,000 fully refundable CTC policy is actually in force for TY2026. Policy uncertainty is removed; macro and measurement uncertainty remain.","The 2021 expanded-CTC anchor prevents over-shrinking toward current-law poverty, while the 2026 macro path and take-up uncertainty keep the interval above the raw simulation lower tail."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["This cell asks what the observed SPM child poverty rate would be if the $3,000 fully refundable CTC policy is actually in force for TY2026. Policy uncertainty is removed; macro and measurement uncertainty remain.","The 2021 expanded-CTC anchor prevents over-shrinking toward current-law poverty, while the 2026 macro path and take-up uncertainty keep the interval above the raw simulation lower tail."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 6.9, ci80: [5.9, 8.3], poverty_reduction_pp_vs_current_law: -5.1 }","Forecast"]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: child-poverty-2026-given-ctc-3000-refundable\nrunLabel: Headline\nresolutionDate: 2027-09-15\ntraceLineCount: 10\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: source grounding (4/4). Weakest dimension: base-rate use (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.child-poverty-2026-given-ctc-3000-refundable.2026-06-27T14-21-25Z.child-poverty-2026-given-ctc-3000-refundable-thesis-analyst-fast-2026-06-27t14-21-25z.fcda2dc0dd540f16","runId":"run.child-poverty-2026-given-ctc-3000-refundable.2026-06-27T14-21-25Z.child-poverty-2026-given-ctc-3000-refundable-thesis-analyst-fast-2026-06-27t14-21-25z.fcda2dc0dd540f16","predictionId":"child-poverty-2026-given-ctc-3000-refundable","specId":"spec.child-poverty-2026-given-ctc-3000-refundable","runLabel":"Thesis analyst reviewed fast run","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":3.65,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":4,"rationale":"Score 4/4: 5 historical point(s) and explicit outside-view language.","evidence":["Base-rate/reference class: without the 2021 expanded credit and stimulus environment, recent child SPM poverty sits around 12.4 to 13.7 percent. I use 13.4 percent as the current-policy outside-view anchor before adding the conditional $3,000 fully refundable CTC.","Time-series prior: I do not extrapolate a simple linear trend because the child SPM series has large policy discontinuities from pandemic stimulus, expanded refundable credits, and their expiration; a persistence prior around the recent non-expanded-CTC level is more defensible."]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 5 typed tool call(s), 5 source-context item(s), activity log present.","evidence":["The resolver is the Census Bureau first print for the Supplemental Poverty Measure poverty rate among people under age 18 for calendar year 2026. This is not the official poverty measure: SPM resources include taxes, refundable credits, transfers and noncash benefits, and subtract medical, work, and child-care expenses while adjusting thresholds for housing costs.","Tool call: Opened Census Poverty in the United States: 2021 publication page."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":3,"rationale":"Score 3/4 under the resolution clarity rubric.","evidence":["The resolver is the Census Bureau first print for the Supplemental Poverty Measure poverty rate among people under age 18 for calendar year 2026. This is not the official poverty measure: SPM resources include taxes, refundable credits, transfers and noncash benefits, and subtract medical, work, and child-care expenses while adjusting thresholds for housing costs.","Tool call: Checked Census first-print publication pages for recent poverty reports."]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 6.3, distribution present, forecast step count 1.","evidence":["Anchor 13.4 percent. Subtract 4.7 percentage points for the $3,000 fully refundable CTC, smaller than the 7.2 point 2021-to-2022 child SPM reversal because this condition excludes stimulus and the $3,600 young-child amount. Point = 13.4 - 4.7 = 8.7. For the 80% interval, combine about 1.3 points of recent annual child-SPM movement, roughly 1.5-2.0 points of policy-effect uncertainty, and macro/SPM modeling risk, giving an asymmetric judgmental interval of 5.7 to 12.0.","Review disposition: accepted the critiques to clarify the first-print resolver, identify Table B-2 as the likely target table, state why a simple time-series prior is not used, justify the interval from volatility plus policy-effect uncertainty, and label the 2024 value as overall SPM context. The exact 2027 Census publication URL was not available in the public evidence fetched, so the rule specifies using the first posted Census page or successor table."]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":4,"rationale":"Score 4/4 under the mechanism reasoning rubric.","evidence":["Time-series prior: I do not extrapolate a simple linear trend because the child SPM series has large policy discontinuities from pandemic stimulus, expanded refundable credits, and their expiration; a persistence prior around the recent non-expanded-CTC level is more defensible.","Policy mechanism: a fully refundable $3,000 CTC would count in SPM tax-credit resources for eligible families and would matter most for children in low-earnings households who receive little or no current-law nonrefundable credit. It should not mechanically recreate the 2021 5.2 percent rate because the 2021 outcome also reflected larger under-age-6 credits, stimulus payments, and pandemic-era safety-net conditions."]},{"dimensionId":"counterarguments","label":"Counterarguments","score":2,"rationale":"Score 2/4: offsetting-evidence language is present.","evidence":["Anchor 13.4 percent. Subtract 4.7 percentage points for the $3,000 fully refundable CTC, smaller than the 7.2 point 2021-to-2022 child SPM reversal because this condition excludes stimulus and the $3,600 young-child amount. Point = 13.4 - 4.7 = 8.7. For the 80% interval, combine about 1.3 points of recent annual child-SPM movement, roughly 1.5-2.0 points of policy-effect uncertainty, and macro/SPM modeling risk, giving an asymmetric judgmental interval of 5.7 to 12.0.","Review disposition: accepted the critiques to clarify the first-print resolver, identify Table B-2 as the likely target table, state why a simple time-series prior is not used, justify the interval from volatility plus policy-effect uncertainty, and label the 2024 value as overall SPM context. The exact 2027 Census publication URL was not available in the public evidence fetched, so the rule specifies using the first posted Census page or successor table."]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Forecast for 2026 child SPM poverty conditional on a refundable $3,000 CTC","Tool result: Fetched 2023 overall SPM rate 12.9 percent and 2023 child SPM poverty rate 13.7 percent, an increase of 1.3 percentage points from 2022."]}],"flags":[],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: child-poverty-2026-given-ctc-3000-refundable\nrunLabel: Thesis analyst reviewed fast run\nresolutionDate: 2027-09-15\ntraceLineCount: 19\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: base-rate use (4/4). Weakest dimension: counterarguments (2/4). No major process flags."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.iit-revenue-fy2028-given-salt-fully-repealed.2026-06-08T00-00-00-02-00.f69cb7505ac7b981","runId":"run.iit-revenue-fy2028-given-salt-fully-repealed.2026-06-08T00-00-00-02-00.f69cb7505ac7b981","predictionId":"iit-revenue-fy2028-given-salt-fully-repealed","specId":"spec.iit-revenue-fy2028-given-salt-fully-repealed","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.68,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":2,"rationale":"Score 2/4: 4 historical point(s) and implicit outside-view language.","evidence":[]},{"dimensionId":"source_grounding","label":"Source grounding","score":3,"rationale":"Score 3/4: 3 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":[]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 330, distribution present, forecast step count 1.","evidence":["Forecast: point 2790, 80% interval [2630, 2960]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":3,"rationale":"Score 3/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 2785, ci80: [2620, 2960], static_revenue_loss_vs_10k_cap: -98 }","Tool result: { point: 2790, ci80: [2630, 2960] }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. Judge only the public trace and target contract. Do not reward a forecast for matching an unknown future; proper scoring happens after official resolution.","user":"Evaluate the linked prediction run using its Thesis run record, publicTrace, target contract, distribution summary, and the forecast trace judge rubric.\npredictionId: iit-revenue-fy2028-given-salt-fully-repealed\nrunLabel: Headline\nresolutionDate: 2028-10-20\ntraceLineCount: 13\nDo not duplicate hidden reasoning or re-score the outcome.","outputSchema":"{ overallScore: number, dimensions: [{ dimensionId, score, rationale, evidence }], flags: string[], summary: string }"},"summary":"Strongest dimension: uncertainty calibration (4/4). Weakest dimension: counterarguments (0/4). Flags: weak_counterarguments."},{"schemaVersion":"thesis_forecast_trace_judge_v1","judgeId":"judge.trace.run.uninsured-2028-given-ept-expire.2026-06-08T00-00-00-02-00.63fd78db55c486d6","runId":"run.uninsured-2028-given-ept-expire.2026-06-08T00-00-00-02-00.63fd78db55c486d6","predictionId":"uninsured-2028-given-ept-expire","specId":"spec.uninsured-2028-given-ept-expire","runLabel":"Headline","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"scoreScale":{"min":0,"max":4},"overallScore":2.86,"dimensions":[{"dimensionId":"base_rate_use","label":"Base-rate use","score":3,"rationale":"Score 3/4: 6 historical point(s) and explicit outside-view language.","evidence":["Tool call: cbo.lookup({ table: \"health_insurance_baseline_2026\", series: \"uninsured_rate_under_65\", year: 2028, policy: \"ept_permanent_expiration\" })"]},{"dimensionId":"source_grounding","label":"Source grounding","score":4,"rationale":"Score 4/4: 3 typed tool call(s), 0 source-context item(s), activity log absent.","evidence":["Two compounding factors push the 2028 number slightly above the 2026 conditional number: (a) marketplace plans become less attractive as some insurers exit subsidy-dependent regions, (b) underlying premium growth makes unsubsidized coverage less affordable for the 200-400% FPL population."]},{"dimensionId":"resolution_clarity","label":"Resolution clarity","score":2,"rationale":"Score 2/4 under the resolution clarity rubric.","evidence":[]},{"dimensionId":"uncertainty_calibration","label":"Uncertainty calibration","score":4,"rationale":"Score 4/4: interval width 2.2, distribution present, forecast step count 1.","evidence":["Forecast: point 11.3, 80% interval [10.2, 12.4]"]},{"dimensionId":"mechanism_reasoning","label":"Mechanism reasoning","score":2,"rationale":"Score 2/4 under the mechanism reasoning rubric.","evidence":[]},{"dimensionId":"counterarguments","label":"Counterarguments","score":0,"rationale":"Score 0/4: offsetting-evidence language is thin.","evidence":[]},{"dimensionId":"forecast_coherence","label":"Forecast coherence","score":4,"rationale":"Score 4/4 under the forecast coherence rubric.","evidence":["Tool result: { point: 11.2, ci80: [10.3, 12.2], coverage_loss_marketplace: -3.4M, medicaid_reabsorption: +0.8M, esi_pickup: +0.2M }","Tool result: { point: 11.3, ci80: [10.2, 12.4] }"]}],"flags":["weak_counterarguments"],"prompt":{"system":"You are an LLM-as-judge for forecast process quality. 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Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.retail-sales-mom-may-2026.2026-06-15T10-05-00-04-00.retail-control-no-packs.987df99045d5dcd8.resolution_event.retail-sales-mom-may-2026.census-marts-adv44x72-may-2026-monthly-change-advance.numeric_cdf_crps_v3_ledger_scale.1c3d5992f8c1117c","runId":"run.retail-sales-mom-may-2026.2026-06-15T10-05-00-04-00.retail-control-no-packs.987df99045d5dcd8","scoreId":"score.run.retail-sales-mom-may-2026.2026-06-15T10-05-00-04-00.retail-control-no-packs.987df99045d5dcd8.resolution_event.retail-sales-mom-may-2026.census-marts-adv44x72-may-2026-monthly-change-advance.numeric_cdf_crps_v3_ledger_scale.1c3d5992f8c1117c","predictionId":"retail-sales-mom-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 0.9 versus point 0.1; signed error 0.8, nCRPS unavailable (fewer than three pre-cutoff ledger observations). 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Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.core-pce-mom-may-2026.2026-06-20T09-12-00-04-00.core-pce-mom-may-2026-brier-shadow-no-packs.535cd429edf5344c.resolution_event.core-pce-mom-may-2026.bea-pce-core-mom-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.07332be51532b39c","runId":"run.core-pce-mom-may-2026.2026-06-20T09-12-00-04-00.core-pce-mom-may-2026-brier-shadow-no-packs.535cd429edf5344c","scoreId":"score.run.core-pce-mom-may-2026.2026-06-20T09-12-00-04-00.core-pce-mom-may-2026-brier-shadow-no-packs.535cd429edf5344c.resolution_event.core-pce-mom-may-2026.bea-pce-core-mom-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.07332be51532b39c","predictionId":"core-pce-mom-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 0.3 versus point 0.21; signed error 0.09, nCRPS unavailable (fewer than three pre-cutoff ledger observations). 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Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.jolts-hires-rate-june-2026.2026-07-26T01-11-27Z.392d9883e1d08cb2.resolution_event.jolts-hires-rate-june-2026.bls-jolts-hires-rate-2026-06-first-print.numeric_cdf_crps_v3_ledger_scale.b61c30fdf60a8535","runId":"run.jolts-hires-rate-june-2026.2026-07-26T01-11-27Z.392d9883e1d08cb2","scoreId":"score.run.jolts-hires-rate-june-2026.2026-07-26T01-11-27Z.392d9883e1d08cb2.resolution_event.jolts-hires-rate-june-2026.bls-jolts-hires-rate-2026-06-first-print.numeric_cdf_crps_v3_ledger_scale.b61c30fdf60a8535","predictionId":"jolts-hires-rate-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 3.4 versus point 3.3; signed error 0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.jolts-hires-rate-june-2026.2026-07-31T14-00-26Z.jolts-hires-rate-june-2026-challenge-github-pavelmakarchuk-2026-07-31t14-00-26z.fda2c307a15c1d96.resolution_event.jolts-hires-rate-june-2026.bls-jolts-hires-rate-2026-06-first-print.numeric_cdf_crps_v3_ledger_scale.2ad010fe6248c6fa","runId":"run.jolts-hires-rate-june-2026.2026-07-31T14-00-26Z.jolts-hires-rate-june-2026-challenge-github-pavelmakarchuk-2026-07-31t14-00-26z.fda2c307a15c1d96","scoreId":"score.run.jolts-hires-rate-june-2026.2026-07-31T14-00-26Z.jolts-hires-rate-june-2026-challenge-github-pavelmakarchuk-2026-07-31t14-00-26z.fda2c307a15c1d96.resolution_event.jolts-hires-rate-june-2026.bls-jolts-hires-rate-2026-06-first-print.numeric_cdf_crps_v3_ledger_scale.2ad010fe6248c6fa","predictionId":"jolts-hires-rate-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 3.4 versus point 3.3; signed error 0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.initial-claims-week-2026-07-25.2026-07-21T01-03-01Z.9676d5b12b26e120.resolution_event.initial-claims-week-2026-07-25.us-dol-initial-claims-sa-week-2026-07-25.numeric_cdf_crps_v3_ledger_scale.f4c4b669f4af9eec","runId":"run.initial-claims-week-2026-07-25.2026-07-21T01-03-01Z.9676d5b12b26e120","scoreId":"score.run.initial-claims-week-2026-07-25.2026-07-21T01-03-01Z.9676d5b12b26e120.resolution_event.initial-claims-week-2026-07-25.us-dol-initial-claims-sa-week-2026-07-25.numeric_cdf_crps_v3_ledger_scale.f4c4b669f4af9eec","predictionId":"initial-claims-week-2026-07-25","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","surprising_release"],"severity":"high","explanation":"Observed value 197 versus point 212; signed error -15, nCRPS 1.86. Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.initial-claims-week-2026-07-25.2026-07-21T01-03-01Z.time-series-prior.c99343ff097bed09.resolution_event.initial-claims-week-2026-07-25.us-dol-initial-claims-sa-week-2026-07-25.numeric_cdf_crps_v3_ledger_scale.20093bfe43075f53","runId":"run.initial-claims-week-2026-07-25.2026-07-21T01-03-01Z.time-series-prior.c99343ff097bed09","scoreId":"score.run.initial-claims-week-2026-07-25.2026-07-21T01-03-01Z.time-series-prior.c99343ff097bed09.resolution_event.initial-claims-week-2026-07-25.us-dol-initial-claims-sa-week-2026-07-25.numeric_cdf_crps_v3_ledger_scale.20093bfe43075f53","predictionId":"initial-claims-week-2026-07-25","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","surprising_release"],"severity":"high","explanation":"Observed value 197 versus point 208; signed error -11, nCRPS 1.27. Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.abs-labour-employment-change-australia-june-2026.2026-07-11T18-15-02Z.9a6ad231ebeda7fd.resolution_event.abs-labour-employment-change-australia-june-2026.abs-labour-employment-change-australia-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.bb0465f363cbf89f","runId":"run.abs-labour-employment-change-australia-june-2026.2026-07-11T18-15-02Z.9a6ad231ebeda7fd","scoreId":"score.run.abs-labour-employment-change-australia-june-2026.2026-07-11T18-15-02Z.9a6ad231ebeda7fd.resolution_event.abs-labour-employment-change-australia-june-2026.abs-labour-employment-change-australia-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.bb0465f363cbf89f","predictionId":"abs-labour-employment-change-australia-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow"],"severity":"medium","explanation":"Observed value 76.3 versus point 18; signed error 58.3, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.initial-claims-week-2026-07-18.2026-07-11T00-25-34Z.fbe3c2c3da579fd1.resolution_event.initial-claims-week-2026-07-18.us-dol-initial-claims-sa-week-2026-07-18.numeric_cdf_crps_v3_ledger_scale.58f2fe9541fbafdd","runId":"run.initial-claims-week-2026-07-18.2026-07-11T00-25-34Z.fbe3c2c3da579fd1","scoreId":"score.run.initial-claims-week-2026-07-18.2026-07-11T00-25-34Z.fbe3c2c3da579fd1.resolution_event.initial-claims-week-2026-07-18.us-dol-initial-claims-sa-week-2026-07-18.numeric_cdf_crps_v3_ledger_scale.58f2fe9541fbafdd","predictionId":"initial-claims-week-2026-07-18","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","surprising_release","overreacted_to_recent_data"],"severity":"high","explanation":"Observed value 187 versus point 216; signed error -29, nCRPS 2.85. Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.initial-claims-week-2026-07-18.2026-07-11T00-25-34Z.time-series-prior.a5dca327ff891db1.resolution_event.initial-claims-week-2026-07-18.us-dol-initial-claims-sa-week-2026-07-18.numeric_cdf_crps_v3_ledger_scale.f1d97be20df7d052","runId":"run.initial-claims-week-2026-07-18.2026-07-11T00-25-34Z.time-series-prior.a5dca327ff891db1","scoreId":"score.run.initial-claims-week-2026-07-18.2026-07-11T00-25-34Z.time-series-prior.a5dca327ff891db1.resolution_event.initial-claims-week-2026-07-18.us-dol-initial-claims-sa-week-2026-07-18.numeric_cdf_crps_v3_ledger_scale.f1d97be20df7d052","predictionId":"initial-claims-week-2026-07-18","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","surprising_release","overreacted_to_recent_data"],"severity":"high","explanation":"Observed value 187 versus point 215; signed error -28, nCRPS 3. Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.continued-claims-week-2026-07-18.2026-07-11T00-27-39Z.4810b7e1af46c0c8.resolution_event.continued-claims-week-2026-07-18.dol-eta-continued-claims-sa-week-2026-07-18-first-print.numeric_cdf_crps_v3_ledger_scale.6c6cc26fce78b70f","runId":"run.continued-claims-week-2026-07-18.2026-07-11T00-27-39Z.4810b7e1af46c0c8","scoreId":"score.run.continued-claims-week-2026-07-18.2026-07-11T00-27-39Z.4810b7e1af46c0c8.resolution_event.continued-claims-week-2026-07-18.dol-eta-continued-claims-sa-week-2026-07-18-first-print.numeric_cdf_crps_v3_ledger_scale.6c6cc26fce78b70f","predictionId":"continued-claims-week-2026-07-18","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","overreacted_to_recent_data"],"severity":"medium","explanation":"Observed value 1.782 versus point 1.828; signed error -0.05, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.initial-claims-week-2026-07-11.2026-07-10T03-41-05Z.fbe3c2c3da579fd1.resolution_event.initial-claims-week-2026-07-11.us-dol-initial-claims-sa-week-2026-07-11.numeric_cdf_crps_v3_ledger_scale.3dbffa0d5b5d1fba","runId":"run.initial-claims-week-2026-07-11.2026-07-10T03-41-05Z.fbe3c2c3da579fd1","scoreId":"score.run.initial-claims-week-2026-07-11.2026-07-10T03-41-05Z.fbe3c2c3da579fd1.resolution_event.initial-claims-week-2026-07-11.us-dol-initial-claims-sa-week-2026-07-11.numeric_cdf_crps_v3_ledger_scale.3dbffa0d5b5d1fba","predictionId":"initial-claims-week-2026-07-11","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"high","explanation":"Observed value 208 versus point 216; signed error -8, nCRPS 0.62. Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.initial-claims-week-2026-07-11.2026-07-10T03-41-05Z.time-series-prior.a5dca327ff891db1.resolution_event.initial-claims-week-2026-07-11.us-dol-initial-claims-sa-week-2026-07-11.numeric_cdf_crps_v3_ledger_scale.10f55f545ce0e6dd","runId":"run.initial-claims-week-2026-07-11.2026-07-10T03-41-05Z.time-series-prior.a5dca327ff891db1","scoreId":"score.run.initial-claims-week-2026-07-11.2026-07-10T03-41-05Z.time-series-prior.a5dca327ff891db1.resolution_event.initial-claims-week-2026-07-11.us-dol-initial-claims-sa-week-2026-07-11.numeric_cdf_crps_v3_ledger_scale.10f55f545ce0e6dd","predictionId":"initial-claims-week-2026-07-11","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"medium","explanation":"Observed value 208 versus point 215; signed error -7, nCRPS 0.53. Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.continued-claims-week-2026-07-11.2026-07-10T03-44-05Z.e060719c4b0f3387.resolution_event.continued-claims-week-2026-07-11.dol-eta-continued-claims-sa-week-2026-07-11-first-print.numeric_cdf_crps_v3_ledger_scale.ca0742ff7b2f070b","runId":"run.continued-claims-week-2026-07-11.2026-07-10T03-44-05Z.e060719c4b0f3387","scoreId":"score.run.continued-claims-week-2026-07-11.2026-07-10T03-44-05Z.e060719c4b0f3387.resolution_event.continued-claims-week-2026-07-11.dol-eta-continued-claims-sa-week-2026-07-11-first-print.numeric_cdf_crps_v3_ledger_scale.ca0742ff7b2f070b","predictionId":"continued-claims-week-2026-07-11","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 1.796 versus point 1.815; signed error -0.02, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.nursing-home-staffing-hprd-july-2026.2026-07-21T01-37-06Z.a9b578df6e152614.resolution_event.nursing-home-staffing-hprd-july-2026.cms-nursing-home-compare-reported-total-nurse-staffing-hprd-us-2026-07-first-print.numeric_cdf_crps_v3_ledger_scale.0030caad95a6f629","runId":"run.nursing-home-staffing-hprd-july-2026.2026-07-21T01-37-06Z.a9b578df6e152614","scoreId":"score.run.nursing-home-staffing-hprd-july-2026.2026-07-21T01-37-06Z.a9b578df6e152614.resolution_event.nursing-home-staffing-hprd-july-2026.cms-nursing-home-compare-reported-total-nurse-staffing-hprd-us-2026-07-first-print.numeric_cdf_crps_v3_ledger_scale.0030caad95a6f629","predictionId":"nursing-home-staffing-hprd-july-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 3.861 versus point 3.92; signed error -0.06, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-nursing-home-occupancy-july-2026.2026-07-21T08-43-54Z.378cf0ef5df37315.resolution_event.us-nursing-home-occupancy-july-2026.cms-care-compare-nursing-home-occupancy-pct-2026-07-first-print.numeric_cdf_crps_v3_ledger_scale.3d564d4e3c7c2e7a","runId":"run.us-nursing-home-occupancy-july-2026.2026-07-21T08-43-54Z.378cf0ef5df37315","scoreId":"score.run.us-nursing-home-occupancy-july-2026.2026-07-21T08-43-54Z.378cf0ef5df37315.resolution_event.us-nursing-home-occupancy-july-2026.cms-care-compare-nursing-home-occupancy-pct-2026-07-first-print.numeric_cdf_crps_v3_ledger_scale.3d564d4e3c7c2e7a","predictionId":"us-nursing-home-occupancy-july-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","bad_baseline"],"severity":"medium","explanation":"Observed value 80.45 versus point 79.82; signed error 0.63, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.fed-g17-capacity-utilization-total-industry-june-2026.2026-07-08T16-53-10Z.b1f4cd5d81defefb.resolution_event.fed-g17-capacity-utilization-total-industry-june-2026.fed-g17-capacity-utilization-total-industry-2026-06-first-print.numeric_cdf_crps_v3_ledger_scale.d5850eea54d3c306","runId":"run.fed-g17-capacity-utilization-total-industry-june-2026.2026-07-08T16-53-10Z.b1f4cd5d81defefb","scoreId":"score.run.fed-g17-capacity-utilization-total-industry-june-2026.2026-07-08T16-53-10Z.b1f4cd5d81defefb.resolution_event.fed-g17-capacity-utilization-total-industry-june-2026.fed-g17-capacity-utilization-total-industry-2026-06-first-print.numeric_cdf_crps_v3_ledger_scale.d5850eea54d3c306","predictionId":"fed-g17-capacity-utilization-total-industry-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 76.1 versus point 76.2; signed error -0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.fed-g17-industrial-production-total-index-mom-june-2026.2026-07-08T16-55-28Z.8ff89b7696efc334.resolution_event.fed-g17-industrial-production-total-index-mom-june-2026.fed-g17-industrial-production-total-index-mom-2026-06-first-print.numeric_cdf_crps_v3_ledger_scale.9b90f0f108c159a5","runId":"run.fed-g17-industrial-production-total-index-mom-june-2026.2026-07-08T16-55-28Z.8ff89b7696efc334","scoreId":"score.run.fed-g17-industrial-production-total-index-mom-june-2026.2026-07-08T16-55-28Z.8ff89b7696efc334.resolution_event.fed-g17-industrial-production-total-index-mom-june-2026.fed-g17-industrial-production-total-index-mom-2026-06-first-print.numeric_cdf_crps_v3_ledger_scale.9b90f0f108c159a5","predictionId":"fed-g17-industrial-production-total-index-mom-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 0.1 versus point 0.2; signed error -0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.bls-import-price-index-all-imports-mom-june-2026.2026-07-07T22-07-42Z.f8bd3dc28bf7e6b9.resolution_event.bls-import-price-index-all-imports-mom-june-2026.bls-import-price-index-all-imports-mom-2026-06-first-print.numeric_cdf_crps_v3_ledger_scale.4c9ef38c1c6a69cc","runId":"run.bls-import-price-index-all-imports-mom-june-2026.2026-07-07T22-07-42Z.f8bd3dc28bf7e6b9","scoreId":"score.run.bls-import-price-index-all-imports-mom-june-2026.2026-07-07T22-07-42Z.f8bd3dc28bf7e6b9.resolution_event.bls-import-price-index-all-imports-mom-june-2026.bls-import-price-index-all-imports-mom-2026-06-first-print.numeric_cdf_crps_v3_ledger_scale.4c9ef38c1c6a69cc","predictionId":"bls-import-price-index-all-imports-mom-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 0.3 versus point 1.1; signed error -0.8, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.census-housing-starts-saar-june-2026.2026-07-07T22-13-30Z.4a492053aefceab1.resolution_event.census-housing-starts-saar-june-2026.census-housing-starts-saar-2026-06-first-print.numeric_cdf_crps_v3_ledger_scale.f77918046c40fde1","runId":"run.census-housing-starts-saar-june-2026.2026-07-07T22-13-30Z.4a492053aefceab1","scoreId":"score.run.census-housing-starts-saar-june-2026.2026-07-07T22-13-30Z.4a492053aefceab1.resolution_event.census-housing-starts-saar-june-2026.census-housing-starts-saar-2026-06-first-print.numeric_cdf_crps_v3_ledger_scale.f77918046c40fde1","predictionId":"census-housing-starts-saar-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow"],"severity":"medium","explanation":"Observed value 1.427 versus point 1.237; signed error 0.19, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.census-housing-starts-saar-june-2026.2026-07-08T02-53-21Z.census-housing-starts-saar-june-2026-thesis-analyst-fast-2026-07-08t02-53-21z.7386e893808cd951.resolution_event.census-housing-starts-saar-june-2026.census-housing-starts-saar-2026-06-first-print.numeric_cdf_crps_v3_ledger_scale.f227e7278e36e674","runId":"run.census-housing-starts-saar-june-2026.2026-07-08T02-53-21Z.census-housing-starts-saar-june-2026-thesis-analyst-fast-2026-07-08t02-53-21z.7386e893808cd951","scoreId":"score.run.census-housing-starts-saar-june-2026.2026-07-08T02-53-21Z.census-housing-starts-saar-june-2026-thesis-analyst-fast-2026-07-08t02-53-21z.7386e893808cd951.resolution_event.census-housing-starts-saar-june-2026.census-housing-starts-saar-2026-06-first-print.numeric_cdf_crps_v3_ledger_scale.f227e7278e36e674","predictionId":"census-housing-starts-saar-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 1.427 versus point 1.3; signed error 0.13, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.census-housing-starts-saar-june-2026.2026-07-08T02-53-35Z.census-housing-starts-saar-june-2026-thesis-analyst-fast-2026-07-08t02-53-35z.b811c2845d9abc69.resolution_event.census-housing-starts-saar-june-2026.census-housing-starts-saar-2026-06-first-print.numeric_cdf_crps_v3_ledger_scale.922e85bea6cb3564","runId":"run.census-housing-starts-saar-june-2026.2026-07-08T02-53-35Z.census-housing-starts-saar-june-2026-thesis-analyst-fast-2026-07-08t02-53-35z.b811c2845d9abc69","scoreId":"score.run.census-housing-starts-saar-june-2026.2026-07-08T02-53-35Z.census-housing-starts-saar-june-2026-thesis-analyst-fast-2026-07-08t02-53-35z.b811c2845d9abc69.resolution_event.census-housing-starts-saar-june-2026.census-housing-starts-saar-2026-06-first-print.numeric_cdf_crps_v3_ledger_scale.922e85bea6cb3564","predictionId":"census-housing-starts-saar-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow"],"severity":"medium","explanation":"Observed value 1.427 versus point 1.237; signed error 0.19, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.census-housing-starts-saar-june-2026.2026-07-08T02-57-35Z.census-housing-starts-saar-june-2026-thesis-analyst-fast-2026-07-08t02-57-35z.b811c2845d9abc69.resolution_event.census-housing-starts-saar-june-2026.census-housing-starts-saar-2026-06-first-print.numeric_cdf_crps_v3_ledger_scale.b79be640c4db38eb","runId":"run.census-housing-starts-saar-june-2026.2026-07-08T02-57-35Z.census-housing-starts-saar-june-2026-thesis-analyst-fast-2026-07-08t02-57-35z.b811c2845d9abc69","scoreId":"score.run.census-housing-starts-saar-june-2026.2026-07-08T02-57-35Z.census-housing-starts-saar-june-2026-thesis-analyst-fast-2026-07-08t02-57-35z.b811c2845d9abc69.resolution_event.census-housing-starts-saar-june-2026.census-housing-starts-saar-2026-06-first-print.numeric_cdf_crps_v3_ledger_scale.b79be640c4db38eb","predictionId":"census-housing-starts-saar-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow"],"severity":"medium","explanation":"Observed value 1.427 versus point 1.237; signed error 0.19, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.census-housing-starts-saar-june-2026.2026-07-08T02-59-50Z.census-housing-starts-saar-june-2026-thesis-analyst-ladder-2026-07-08t02-59-50z.57eed62630309ed1.resolution_event.census-housing-starts-saar-june-2026.census-housing-starts-saar-2026-06-first-print.numeric_cdf_crps_v3_ledger_scale.1d9f6495b9c970f2","runId":"run.census-housing-starts-saar-june-2026.2026-07-08T02-59-50Z.census-housing-starts-saar-june-2026-thesis-analyst-ladder-2026-07-08t02-59-50z.57eed62630309ed1","scoreId":"score.run.census-housing-starts-saar-june-2026.2026-07-08T02-59-50Z.census-housing-starts-saar-june-2026-thesis-analyst-ladder-2026-07-08t02-59-50z.57eed62630309ed1.resolution_event.census-housing-starts-saar-june-2026.census-housing-starts-saar-2026-06-first-print.numeric_cdf_crps_v3_ledger_scale.1d9f6495b9c970f2","predictionId":"census-housing-starts-saar-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow"],"severity":"medium","explanation":"Observed value 1.427 versus point 1.237; signed error 0.19, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.census-housing-starts-saar-june-2026.2026-07-08T03-03-42Z.census-housing-starts-saar-june-2026-thesis-analyst-median3-2026-07-08t03-03-42z.6d245a66d73a7b35.resolution_event.census-housing-starts-saar-june-2026.census-housing-starts-saar-2026-06-first-print.numeric_cdf_crps_v3_ledger_scale.34e092a8305fdc67","runId":"run.census-housing-starts-saar-june-2026.2026-07-08T03-03-42Z.census-housing-starts-saar-june-2026-thesis-analyst-median3-2026-07-08t03-03-42z.6d245a66d73a7b35","scoreId":"score.run.census-housing-starts-saar-june-2026.2026-07-08T03-03-42Z.census-housing-starts-saar-june-2026-thesis-analyst-median3-2026-07-08t03-03-42z.6d245a66d73a7b35.resolution_event.census-housing-starts-saar-june-2026.census-housing-starts-saar-2026-06-first-print.numeric_cdf_crps_v3_ledger_scale.34e092a8305fdc67","predictionId":"census-housing-starts-saar-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow"],"severity":"medium","explanation":"Observed value 1.427 versus point 1.237; signed error 0.19, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.continued-claims-week-2026-07-04.2026-07-07T17-40-20Z.b034a6720f644aee.resolution_event.continued-claims-week-2026-07-04.dol-eta-continued-claims-sa-week-2026-07-04-first-print.numeric_cdf_crps_v3_ledger_scale.9727f660afdde23b","runId":"run.continued-claims-week-2026-07-04.2026-07-07T17-40-20Z.b034a6720f644aee","scoreId":"score.run.continued-claims-week-2026-07-04.2026-07-07T17-40-20Z.b034a6720f644aee.resolution_event.continued-claims-week-2026-07-04.dol-eta-continued-claims-sa-week-2026-07-04-first-print.numeric_cdf_crps_v3_ledger_scale.9727f660afdde23b","predictionId":"continued-claims-week-2026-07-04","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 1.805 versus point 1.82; signed error -0.02, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.core-cpi-mom-may-2026.2026-06-06T23-43-56-02-00.739543bf6e74a03a.resolution_event.core-cpi-mom-may-2026.bls-cpi-u-core-mom-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.0a0afea2e17c5f0f","runId":"run.core-cpi-mom-may-2026.2026-06-06T23-43-56-02-00.739543bf6e74a03a","scoreId":"score.run.core-cpi-mom-may-2026.2026-06-06T23-43-56-02-00.739543bf6e74a03a.resolution_event.core-cpi-mom-may-2026.bls-cpi-u-core-mom-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.0a0afea2e17c5f0f","predictionId":"core-cpi-mom-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 0.2 versus point 0.3; signed error -0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.jolts-job-openings-may-2026.2026-06-27T13-11-02Z.jolts-job-openings-may-2026-thesis-analyst-fast-2026-06-27t13-11-02z.a6575efa2a1f409c.resolution_event.jolts-job-openings-may-2026.bls-jolts-job-openings-total-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.f6d799b2a45436a5","runId":"run.jolts-job-openings-may-2026.2026-06-27T13-11-02Z.jolts-job-openings-may-2026-thesis-analyst-fast-2026-06-27t13-11-02z.a6575efa2a1f409c","scoreId":"score.run.jolts-job-openings-may-2026.2026-06-27T13-11-02Z.jolts-job-openings-may-2026-thesis-analyst-fast-2026-06-27t13-11-02z.a6575efa2a1f409c.resolution_event.jolts-job-openings-may-2026.bls-jolts-job-openings-total-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.f6d799b2a45436a5","predictionId":"jolts-job-openings-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 7594 versus point 7350; signed error 244, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.uk-monthly-gdp-growth-april-2026.2026-06-04T10-32-04-01-00.6141e6531669d1b8.resolution_event.uk-monthly-gdp-growth-april-2026.ons-gdp-monthly-growth-april-2026-first-print.numeric_cdf_crps_v3_ledger_scale.dc90578b6c75acda","runId":"run.uk-monthly-gdp-growth-april-2026.2026-06-04T10-32-04-01-00.6141e6531669d1b8","scoreId":"score.run.uk-monthly-gdp-growth-april-2026.2026-06-04T10-32-04-01-00.6141e6531669d1b8.resolution_event.uk-monthly-gdp-growth-april-2026.ons-gdp-monthly-growth-april-2026-first-print.numeric_cdf_crps_v3_ledger_scale.dc90578b6c75acda","predictionId":"uk-monthly-gdp-growth-april-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value -0.1 versus point -0.1; signed error 0, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.uk-cpi-annual-rate-may-2026.2026-06-04T10-32-04-01-00.19aff3c2df28c994.resolution_event.uk-cpi-annual-rate-may-2026.ons-cpi-annual-rate-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.02840f595582b445","runId":"run.uk-cpi-annual-rate-may-2026.2026-06-04T10-32-04-01-00.19aff3c2df28c994","scoreId":"score.run.uk-cpi-annual-rate-may-2026.2026-06-04T10-32-04-01-00.19aff3c2df28c994.resolution_event.uk-cpi-annual-rate-may-2026.ons-cpi-annual-rate-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.02840f595582b445","predictionId":"uk-cpi-annual-rate-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 2.8 versus point 2.9; signed error -0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.uk-unemployment-rate-feb-apr-2026.2026-06-04T10-32-04-01-00.e9e2e6b6909bc445.resolution_event.uk-unemployment-rate-feb-apr-2026.ons-labour-unemployment-rate-february-to-april-2026-first-print.numeric_cdf_crps_v3_ledger_scale.80a06f7f6b5944bd","runId":"run.uk-unemployment-rate-feb-apr-2026.2026-06-04T10-32-04-01-00.e9e2e6b6909bc445","scoreId":"score.run.uk-unemployment-rate-feb-apr-2026.2026-06-04T10-32-04-01-00.e9e2e6b6909bc445.resolution_event.uk-unemployment-rate-feb-apr-2026.ons-labour-unemployment-rate-february-to-april-2026-first-print.numeric_cdf_crps_v3_ledger_scale.80a06f7f6b5944bd","predictionId":"uk-unemployment-rate-feb-apr-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 4.9 versus point 5.1; signed error -0.2, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.uk-paye-payrolled-employees-may-2026.2026-06-04T10-32-04-01-00.92cfe71c26bcc65c.resolution_event.uk-paye-payrolled-employees-may-2026.ons-hmrc-paye-payrolled-employees-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.4255684c5cfbdb23","runId":"run.uk-paye-payrolled-employees-may-2026.2026-06-04T10-32-04-01-00.92cfe71c26bcc65c","scoreId":"score.run.uk-paye-payrolled-employees-may-2026.2026-06-04T10-32-04-01-00.92cfe71c26bcc65c.resolution_event.uk-paye-payrolled-employees-may-2026.ons-hmrc-paye-payrolled-employees-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.4255684c5cfbdb23","predictionId":"uk-paye-payrolled-employees-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 30.3 versus point 30.15; signed error 0.15, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.uk-retail-sales-volume-mom-may-2026.2026-06-04T10-32-04-01-00.9db79e1bc69fa65a.resolution_event.uk-retail-sales-volume-mom-may-2026.ons-retail-sales-volume-mom-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.3490d2c2448b6e62","runId":"run.uk-retail-sales-volume-mom-may-2026.2026-06-04T10-32-04-01-00.9db79e1bc69fa65a","scoreId":"score.run.uk-retail-sales-volume-mom-may-2026.2026-06-04T10-32-04-01-00.9db79e1bc69fa65a.resolution_event.uk-retail-sales-volume-mom-may-2026.ons-retail-sales-volume-mom-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.3490d2c2448b6e62","predictionId":"uk-retail-sales-volume-mom-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 1.2 versus point 0.5; signed error 0.7, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.uk-public-sector-net-borrowing-may-2026.2026-06-04T10-32-04-01-00.5b5496056b563d02.resolution_event.uk-public-sector-net-borrowing-may-2026.ons-pusf-j5ii-public-sector-net-borrowing-ex-banks-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.dcc1722ec51deaf1","runId":"run.uk-public-sector-net-borrowing-may-2026.2026-06-04T10-32-04-01-00.5b5496056b563d02","scoreId":"score.run.uk-public-sector-net-borrowing-may-2026.2026-06-04T10-32-04-01-00.5b5496056b563d02.resolution_event.uk-public-sector-net-borrowing-may-2026.ons-pusf-j5ii-public-sector-net-borrowing-ex-banks-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.dcc1722ec51deaf1","predictionId":"uk-public-sector-net-borrowing-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 23.3 versus point 18.5; signed error 4.8, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.uk-bank-rate-june-2026-mpc.2026-06-04T10-32-04-01-00.b33aff3526b668a2.resolution_event.uk-bank-rate-june-2026-mpc.boe-bank-rate-after-mpc-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.b65986063685d0f1","runId":"run.uk-bank-rate-june-2026-mpc.2026-06-04T10-32-04-01-00.b33aff3526b668a2","scoreId":"score.run.uk-bank-rate-june-2026-mpc.2026-06-04T10-32-04-01-00.b33aff3526b668a2.resolution_event.uk-bank-rate-june-2026-mpc.boe-bank-rate-after-mpc-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.b65986063685d0f1","predictionId":"uk-bank-rate-june-2026-mpc","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 3.75 versus point 3.75; signed error 0, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.canada-unemployment-rate-may-2026.2026-06-04T11-36-25-01-00.ff3a23dc44e4f89b.resolution_event.canada-unemployment-rate-may-2026.statcan-lfs-unemployment-rate-canada-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.15a04626eb4cfcc3","runId":"run.canada-unemployment-rate-may-2026.2026-06-04T11-36-25-01-00.ff3a23dc44e4f89b","scoreId":"score.run.canada-unemployment-rate-may-2026.2026-06-04T11-36-25-01-00.ff3a23dc44e4f89b.resolution_event.canada-unemployment-rate-may-2026.statcan-lfs-unemployment-rate-canada-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.15a04626eb4cfcc3","predictionId":"canada-unemployment-rate-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow"],"severity":"medium","explanation":"Observed value 6.6 versus point 7; signed error -0.4, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.canada-employment-change-may-2026.2026-06-04T11-36-25-01-00.71730184ad913dc9.resolution_event.canada-employment-change-may-2026.statcan-lfs-employment-change-canada-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.6d0a2a5652c056a6","runId":"run.canada-employment-change-may-2026.2026-06-04T11-36-25-01-00.71730184ad913dc9","scoreId":"score.run.canada-employment-change-may-2026.2026-06-04T11-36-25-01-00.71730184ad913dc9.resolution_event.canada-employment-change-may-2026.statcan-lfs-employment-change-canada-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.6d0a2a5652c056a6","predictionId":"canada-employment-change-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","bad_baseline"],"severity":"medium","explanation":"Observed value 88 versus point -10; signed error 98, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.canada-cpi-annual-rate-may-2026.2026-06-04T11-36-25-01-00.cfa5aea222e44ee8.resolution_event.canada-cpi-annual-rate-may-2026.statcan-cpi-all-items-annual-rate-canada-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.b78365256ab0e904","runId":"run.canada-cpi-annual-rate-may-2026.2026-06-04T11-36-25-01-00.cfa5aea222e44ee8","scoreId":"score.run.canada-cpi-annual-rate-may-2026.2026-06-04T11-36-25-01-00.cfa5aea222e44ee8.resolution_event.canada-cpi-annual-rate-may-2026.statcan-cpi-all-items-annual-rate-canada-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.b78365256ab0e904","predictionId":"canada-cpi-annual-rate-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow"],"severity":"medium","explanation":"Observed value 3.2 versus point 2.7; signed error 0.5, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.canada-cpi-annual-rate-may-2026.2026-06-20T09-02-00-04-00.canada-cpi-annual-rate-may-2026-brier-shadow-no-packs.f4fcfc22e29af399.resolution_event.canada-cpi-annual-rate-may-2026.statcan-cpi-all-items-annual-rate-canada-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.04f9d6d88295bc62","runId":"run.canada-cpi-annual-rate-may-2026.2026-06-20T09-02-00-04-00.canada-cpi-annual-rate-may-2026-brier-shadow-no-packs.f4fcfc22e29af399","scoreId":"score.run.canada-cpi-annual-rate-may-2026.2026-06-20T09-02-00-04-00.canada-cpi-annual-rate-may-2026-brier-shadow-no-packs.f4fcfc22e29af399.resolution_event.canada-cpi-annual-rate-may-2026.statcan-cpi-all-items-annual-rate-canada-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.04f9d6d88295bc62","predictionId":"canada-cpi-annual-rate-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","bad_baseline"],"severity":"medium","explanation":"Observed value 3.2 versus point 2.6; signed error 0.6, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.canada-cpi-annual-rate-may-2026.2026-06-20T09-02-00-04-00.canada-cpi-annual-rate-may-2026-brier-shadow-with-packs.5f5b5f7e997df924.resolution_event.canada-cpi-annual-rate-may-2026.statcan-cpi-all-items-annual-rate-canada-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.93892493c3777562","runId":"run.canada-cpi-annual-rate-may-2026.2026-06-20T09-02-00-04-00.canada-cpi-annual-rate-may-2026-brier-shadow-with-packs.5f5b5f7e997df924","scoreId":"score.run.canada-cpi-annual-rate-may-2026.2026-06-20T09-02-00-04-00.canada-cpi-annual-rate-may-2026-brier-shadow-with-packs.5f5b5f7e997df924.resolution_event.canada-cpi-annual-rate-may-2026.statcan-cpi-all-items-annual-rate-canada-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.93892493c3777562","predictionId":"canada-cpi-annual-rate-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 3.2 versus point 2.7; signed error 0.5, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.canada-monthly-gdp-growth-april-2026.2026-06-04T11-36-25-01-00.89d3681a7f28e8df.resolution_event.canada-monthly-gdp-growth-april-2026.statcan-gdp-by-industry-monthly-growth-april-2026-first-print.numeric_cdf_crps_v3_ledger_scale.cb1171f6d87d35e8","runId":"run.canada-monthly-gdp-growth-april-2026.2026-06-04T11-36-25-01-00.89d3681a7f28e8df","scoreId":"score.run.canada-monthly-gdp-growth-april-2026.2026-06-04T11-36-25-01-00.89d3681a7f28e8df.resolution_event.canada-monthly-gdp-growth-april-2026.statcan-gdp-by-industry-monthly-growth-april-2026-first-print.numeric_cdf_crps_v3_ledger_scale.cb1171f6d87d35e8","predictionId":"canada-monthly-gdp-growth-april-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 0.5 versus point 0.4; signed error 0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.canada-monthly-gdp-growth-april-2026.2026-06-17T02-05-41Z.canada-monthly-gdp-growth-april-2026-thesis-analyst-fast-2026-06-17t02-05-41z.89d3681a7f28e8df.resolution_event.canada-monthly-gdp-growth-april-2026.statcan-gdp-by-industry-monthly-growth-april-2026-first-print.numeric_cdf_crps_v3_ledger_scale.42d746e2b59245be","runId":"run.canada-monthly-gdp-growth-april-2026.2026-06-17T02-05-41Z.canada-monthly-gdp-growth-april-2026-thesis-analyst-fast-2026-06-17t02-05-41z.89d3681a7f28e8df","scoreId":"score.run.canada-monthly-gdp-growth-april-2026.2026-06-17T02-05-41Z.canada-monthly-gdp-growth-april-2026-thesis-analyst-fast-2026-06-17t02-05-41z.89d3681a7f28e8df.resolution_event.canada-monthly-gdp-growth-april-2026.statcan-gdp-by-industry-monthly-growth-april-2026-first-print.numeric_cdf_crps_v3_ledger_scale.42d746e2b59245be","predictionId":"canada-monthly-gdp-growth-april-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 0.5 versus point 0.4; signed error 0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.canada-monthly-gdp-growth-april-2026.2026-06-27T12-54-53Z.canada-monthly-gdp-growth-april-2026-thesis-analyst-fast-2026-06-27t12-54-53z.89d3681a7f28e8df.resolution_event.canada-monthly-gdp-growth-april-2026.statcan-gdp-by-industry-monthly-growth-april-2026-first-print.numeric_cdf_crps_v3_ledger_scale.edff32f883157b07","runId":"run.canada-monthly-gdp-growth-april-2026.2026-06-27T12-54-53Z.canada-monthly-gdp-growth-april-2026-thesis-analyst-fast-2026-06-27t12-54-53z.89d3681a7f28e8df","scoreId":"score.run.canada-monthly-gdp-growth-april-2026.2026-06-27T12-54-53Z.canada-monthly-gdp-growth-april-2026-thesis-analyst-fast-2026-06-27t12-54-53z.89d3681a7f28e8df.resolution_event.canada-monthly-gdp-growth-april-2026.statcan-gdp-by-industry-monthly-growth-april-2026-first-print.numeric_cdf_crps_v3_ledger_scale.edff32f883157b07","predictionId":"canada-monthly-gdp-growth-april-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 0.5 versus point 0.4; signed error 0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.canada-overnight-rate-june-2026-boc.2026-06-04T11-36-25-01-00.98d3522509943078.resolution_event.canada-overnight-rate-june-2026-boc.bank-of-canada-overnight-rate-after-june-2026.numeric_cdf_crps_v3_ledger_scale.6a20507039b641ac","runId":"run.canada-overnight-rate-june-2026-boc.2026-06-04T11-36-25-01-00.98d3522509943078","scoreId":"score.run.canada-overnight-rate-june-2026-boc.2026-06-04T11-36-25-01-00.98d3522509943078.resolution_event.canada-overnight-rate-june-2026-boc.bank-of-canada-overnight-rate-after-june-2026.numeric_cdf_crps_v3_ledger_scale.6a20507039b641ac","predictionId":"canada-overnight-rate-june-2026-boc","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 2.25 versus point 2.25; signed error 0, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.australia-unemployment-rate-may-2026.2026-06-04T11-36-25-01-00.d12f2ff7a6b7ce3c.resolution_event.australia-unemployment-rate-may-2026.abs-labour-unemployment-rate-australia-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.7c296e4e3353636d","runId":"run.australia-unemployment-rate-may-2026.2026-06-04T11-36-25-01-00.d12f2ff7a6b7ce3c","scoreId":"score.run.australia-unemployment-rate-may-2026.2026-06-04T11-36-25-01-00.d12f2ff7a6b7ce3c.resolution_event.australia-unemployment-rate-may-2026.abs-labour-unemployment-rate-australia-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.7c296e4e3353636d","predictionId":"australia-unemployment-rate-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 4.4 versus point 4.5; signed error -0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.australia-unemployment-rate-may-2026.2026-06-20T09-10-00-04-00.australia-unemployment-rate-may-2026-brier-shadow-no-packs.7119b7a068b2153a.resolution_event.australia-unemployment-rate-may-2026.abs-labour-unemployment-rate-australia-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.ab7ad304d5eeda04","runId":"run.australia-unemployment-rate-may-2026.2026-06-20T09-10-00-04-00.australia-unemployment-rate-may-2026-brier-shadow-no-packs.7119b7a068b2153a","scoreId":"score.run.australia-unemployment-rate-may-2026.2026-06-20T09-10-00-04-00.australia-unemployment-rate-may-2026-brier-shadow-no-packs.7119b7a068b2153a.resolution_event.australia-unemployment-rate-may-2026.abs-labour-unemployment-rate-australia-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.ab7ad304d5eeda04","predictionId":"australia-unemployment-rate-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 4.4 versus point 4.5; signed error -0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.australia-unemployment-rate-may-2026.2026-06-20T09-10-00-04-00.australia-unemployment-rate-may-2026-brier-shadow-with-packs.d12f2ff7a6b7ce3c.resolution_event.australia-unemployment-rate-may-2026.abs-labour-unemployment-rate-australia-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.50e25c7f3efddb9d","runId":"run.australia-unemployment-rate-may-2026.2026-06-20T09-10-00-04-00.australia-unemployment-rate-may-2026-brier-shadow-with-packs.d12f2ff7a6b7ce3c","scoreId":"score.run.australia-unemployment-rate-may-2026.2026-06-20T09-10-00-04-00.australia-unemployment-rate-may-2026-brier-shadow-with-packs.d12f2ff7a6b7ce3c.resolution_event.australia-unemployment-rate-may-2026.abs-labour-unemployment-rate-australia-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.50e25c7f3efddb9d","predictionId":"australia-unemployment-rate-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 4.4 versus point 4.5; signed error -0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.australia-unemployment-rate-may-2026.2026-06-17T02-03-58Z.australia-unemployment-rate-may-2026-thesis-analyst-fast-2026-06-17t02-03-58z.d12f2ff7a6b7ce3c.resolution_event.australia-unemployment-rate-may-2026.abs-labour-unemployment-rate-australia-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.c2089266218f9d13","runId":"run.australia-unemployment-rate-may-2026.2026-06-17T02-03-58Z.australia-unemployment-rate-may-2026-thesis-analyst-fast-2026-06-17t02-03-58z.d12f2ff7a6b7ce3c","scoreId":"score.run.australia-unemployment-rate-may-2026.2026-06-17T02-03-58Z.australia-unemployment-rate-may-2026-thesis-analyst-fast-2026-06-17t02-03-58z.d12f2ff7a6b7ce3c.resolution_event.australia-unemployment-rate-may-2026.abs-labour-unemployment-rate-australia-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.c2089266218f9d13","predictionId":"australia-unemployment-rate-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 4.4 versus point 4.5; signed error -0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.australia-employment-change-may-2026.2026-06-04T11-36-25-01-00.712520838c0b785e.resolution_event.australia-employment-change-may-2026.abs-labour-employment-change-australia-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.3a8f0b3fe55b8559","runId":"run.australia-employment-change-may-2026.2026-06-04T11-36-25-01-00.712520838c0b785e","scoreId":"score.run.australia-employment-change-may-2026.2026-06-04T11-36-25-01-00.712520838c0b785e.resolution_event.australia-employment-change-may-2026.abs-labour-employment-change-australia-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.3a8f0b3fe55b8559","predictionId":"australia-employment-change-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 40.3 versus point 15; signed error 25.3, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.australia-employment-change-may-2026.2026-06-20T09-08-00-04-00.australia-employment-change-may-2026-brier-shadow-no-packs.b8d73b347d308a08.resolution_event.australia-employment-change-may-2026.abs-labour-employment-change-australia-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.58a24f5ce97ecf63","runId":"run.australia-employment-change-may-2026.2026-06-20T09-08-00-04-00.australia-employment-change-may-2026-brier-shadow-no-packs.b8d73b347d308a08","scoreId":"score.run.australia-employment-change-may-2026.2026-06-20T09-08-00-04-00.australia-employment-change-may-2026-brier-shadow-no-packs.b8d73b347d308a08.resolution_event.australia-employment-change-may-2026.abs-labour-employment-change-australia-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.58a24f5ce97ecf63","predictionId":"australia-employment-change-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 40.3 versus point 10; signed error 30.3, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.australia-employment-change-may-2026.2026-06-20T09-08-00-04-00.australia-employment-change-may-2026-brier-shadow-with-packs.d90da5fc77da3cc0.resolution_event.australia-employment-change-may-2026.abs-labour-employment-change-australia-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.3fdffec2cc27b6f8","runId":"run.australia-employment-change-may-2026.2026-06-20T09-08-00-04-00.australia-employment-change-may-2026-brier-shadow-with-packs.d90da5fc77da3cc0","scoreId":"score.run.australia-employment-change-may-2026.2026-06-20T09-08-00-04-00.australia-employment-change-may-2026-brier-shadow-with-packs.d90da5fc77da3cc0.resolution_event.australia-employment-change-may-2026.abs-labour-employment-change-australia-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.3fdffec2cc27b6f8","predictionId":"australia-employment-change-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 40.3 versus point 20; signed error 20.3, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.australia-employment-change-may-2026.2026-06-17T02-05-03Z.australia-employment-change-may-2026-thesis-analyst-fast-2026-06-17t02-05-03z.3812528b320bfe22.resolution_event.australia-employment-change-may-2026.abs-labour-employment-change-australia-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.e1b42ccc350544ba","runId":"run.australia-employment-change-may-2026.2026-06-17T02-05-03Z.australia-employment-change-may-2026-thesis-analyst-fast-2026-06-17t02-05-03z.3812528b320bfe22","scoreId":"score.run.australia-employment-change-may-2026.2026-06-17T02-05-03Z.australia-employment-change-may-2026-thesis-analyst-fast-2026-06-17t02-05-03z.3812528b320bfe22.resolution_event.australia-employment-change-may-2026.abs-labour-employment-change-australia-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.e1b42ccc350544ba","predictionId":"australia-employment-change-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 40.3 versus point 20; signed error 20.3, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.australia-cpi-annual-rate-may-2026.2026-06-04T11-36-25-01-00.9e7b93c4d0d3e872.resolution_event.australia-cpi-annual-rate-may-2026.abs-cpi-all-groups-annual-rate-australia-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.561fc4f76cffd65f","runId":"run.australia-cpi-annual-rate-may-2026.2026-06-04T11-36-25-01-00.9e7b93c4d0d3e872","scoreId":"score.run.australia-cpi-annual-rate-may-2026.2026-06-04T11-36-25-01-00.9e7b93c4d0d3e872.resolution_event.australia-cpi-annual-rate-may-2026.abs-cpi-all-groups-annual-rate-australia-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.561fc4f76cffd65f","predictionId":"australia-cpi-annual-rate-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 4 versus point 4.1; signed error -0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.australia-cpi-annual-rate-may-2026.2026-06-20T09-04-00-04-00.australia-cpi-annual-rate-may-2026-brier-shadow-no-packs.b7764552c628f46e.resolution_event.australia-cpi-annual-rate-may-2026.abs-cpi-all-groups-annual-rate-australia-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.89fb68f534ea08da","runId":"run.australia-cpi-annual-rate-may-2026.2026-06-20T09-04-00-04-00.australia-cpi-annual-rate-may-2026-brier-shadow-no-packs.b7764552c628f46e","scoreId":"score.run.australia-cpi-annual-rate-may-2026.2026-06-20T09-04-00-04-00.australia-cpi-annual-rate-may-2026-brier-shadow-no-packs.b7764552c628f46e.resolution_event.australia-cpi-annual-rate-may-2026.abs-cpi-all-groups-annual-rate-australia-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.89fb68f534ea08da","predictionId":"australia-cpi-annual-rate-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 4 versus point 4.2; signed error -0.2, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.australia-cpi-annual-rate-may-2026.2026-06-20T09-04-00-04-00.australia-cpi-annual-rate-may-2026-brier-shadow-with-packs.6626aeab6b4b77bf.resolution_event.australia-cpi-annual-rate-may-2026.abs-cpi-all-groups-annual-rate-australia-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.f03a048a87397805","runId":"run.australia-cpi-annual-rate-may-2026.2026-06-20T09-04-00-04-00.australia-cpi-annual-rate-may-2026-brier-shadow-with-packs.6626aeab6b4b77bf","scoreId":"score.run.australia-cpi-annual-rate-may-2026.2026-06-20T09-04-00-04-00.australia-cpi-annual-rate-may-2026-brier-shadow-with-packs.6626aeab6b4b77bf.resolution_event.australia-cpi-annual-rate-may-2026.abs-cpi-all-groups-annual-rate-australia-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.f03a048a87397805","predictionId":"australia-cpi-annual-rate-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 4 versus point 4.6; signed error -0.6, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.australia-cpi-annual-rate-may-2026.2026-06-17T02-02-48Z.australia-cpi-annual-rate-may-2026-thesis-analyst-fast-2026-06-17t02-02-48z.66771066a1ed088b.resolution_event.australia-cpi-annual-rate-may-2026.abs-cpi-all-groups-annual-rate-australia-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.0e507cebbc6ac300","runId":"run.australia-cpi-annual-rate-may-2026.2026-06-17T02-02-48Z.australia-cpi-annual-rate-may-2026-thesis-analyst-fast-2026-06-17t02-02-48z.66771066a1ed088b","scoreId":"score.run.australia-cpi-annual-rate-may-2026.2026-06-17T02-02-48Z.australia-cpi-annual-rate-may-2026-thesis-analyst-fast-2026-06-17t02-02-48z.66771066a1ed088b.resolution_event.australia-cpi-annual-rate-may-2026.abs-cpi-all-groups-annual-rate-australia-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.0e507cebbc6ac300","predictionId":"australia-cpi-annual-rate-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow"],"severity":"medium","explanation":"Observed value 4 versus point 4.9; signed error -0.9, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.australia-cash-rate-june-2026-rba.2026-06-04T11-36-25-01-00.b5881999155b0f27.resolution_event.australia-cash-rate-june-2026-rba.rba-cash-rate-target-after-june-2026.numeric_cdf_crps_v3_ledger_scale.c067270b27c22922","runId":"run.australia-cash-rate-june-2026-rba.2026-06-04T11-36-25-01-00.b5881999155b0f27","scoreId":"score.run.australia-cash-rate-june-2026-rba.2026-06-04T11-36-25-01-00.b5881999155b0f27.resolution_event.australia-cash-rate-june-2026-rba.rba-cash-rate-target-after-june-2026.numeric_cdf_crps_v3_ledger_scale.c067270b27c22922","predictionId":"australia-cash-rate-june-2026-rba","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 4.35 versus point 4.35; signed error 0, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.euro-area-ecb-deposit-facility-rate-june-2026.2026-06-06T05-41-31-01-00.e3888b3064c078ed.resolution_event.euro-area-ecb-deposit-facility-rate-june-2026.ecb-deposit-facility-rate-after-june-2026.numeric_cdf_crps_v3_ledger_scale.7cc4ac60a2574d60","runId":"run.euro-area-ecb-deposit-facility-rate-june-2026.2026-06-06T05-41-31-01-00.e3888b3064c078ed","scoreId":"score.run.euro-area-ecb-deposit-facility-rate-june-2026.2026-06-06T05-41-31-01-00.e3888b3064c078ed.resolution_event.euro-area-ecb-deposit-facility-rate-june-2026.ecb-deposit-facility-rate-after-june-2026.numeric_cdf_crps_v3_ledger_scale.7cc4ac60a2574d60","predictionId":"euro-area-ecb-deposit-facility-rate-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 2.25 versus point 2; signed error 0.25, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.euro-area-hicp-annual-rate-may-2026-final.2026-06-06T05-41-31-01-00.551502d61103eb3c.resolution_event.euro-area-hicp-annual-rate-may-2026-final.eurostat-hicp-all-items-annual-rate-euro-area-may-2026-final-first-print.numeric_cdf_crps_v3_ledger_scale.f1d957d4b081f256","runId":"run.euro-area-hicp-annual-rate-may-2026-final.2026-06-06T05-41-31-01-00.551502d61103eb3c","scoreId":"score.run.euro-area-hicp-annual-rate-may-2026-final.2026-06-06T05-41-31-01-00.551502d61103eb3c.resolution_event.euro-area-hicp-annual-rate-may-2026-final.eurostat-hicp-all-items-annual-rate-euro-area-may-2026-final-first-print.numeric_cdf_crps_v3_ledger_scale.f1d957d4b081f256","predictionId":"euro-area-hicp-annual-rate-may-2026-final","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 3.2 versus point 3.2; signed error 0, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.euro-area-hicp-annual-rate-june-2026-flash.2026-06-06T05-41-31-01-00.f311985c1075553a.resolution_event.euro-area-hicp-annual-rate-june-2026-flash.eurostat-hicp-all-items-annual-rate-euro-area-june-2026-flash.numeric_cdf_crps_v3_ledger_scale.8fd482e609a9a525","runId":"run.euro-area-hicp-annual-rate-june-2026-flash.2026-06-06T05-41-31-01-00.f311985c1075553a","scoreId":"score.run.euro-area-hicp-annual-rate-june-2026-flash.2026-06-06T05-41-31-01-00.f311985c1075553a.resolution_event.euro-area-hicp-annual-rate-june-2026-flash.eurostat-hicp-all-items-annual-rate-euro-area-june-2026-flash.numeric_cdf_crps_v3_ledger_scale.8fd482e609a9a525","predictionId":"euro-area-hicp-annual-rate-june-2026-flash","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 2.8 versus point 3.1; signed error -0.3, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.euro-area-hicp-annual-rate-june-2026-flash.2026-06-27T13-13-42Z.euro-area-hicp-annual-rate-june-2026-flash-thesis-analyst-fast-2026-06-27t13-13-42z.b86a7005b50fa541.resolution_event.euro-area-hicp-annual-rate-june-2026-flash.eurostat-hicp-all-items-annual-rate-euro-area-june-2026-flash.numeric_cdf_crps_v3_ledger_scale.3582aeb6e1972ffe","runId":"run.euro-area-hicp-annual-rate-june-2026-flash.2026-06-27T13-13-42Z.euro-area-hicp-annual-rate-june-2026-flash-thesis-analyst-fast-2026-06-27t13-13-42z.b86a7005b50fa541","scoreId":"score.run.euro-area-hicp-annual-rate-june-2026-flash.2026-06-27T13-13-42Z.euro-area-hicp-annual-rate-june-2026-flash-thesis-analyst-fast-2026-06-27t13-13-42z.b86a7005b50fa541.resolution_event.euro-area-hicp-annual-rate-june-2026-flash.eurostat-hicp-all-items-annual-rate-euro-area-june-2026-flash.numeric_cdf_crps_v3_ledger_scale.3582aeb6e1972ffe","predictionId":"euro-area-hicp-annual-rate-june-2026-flash","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","bad_baseline"],"severity":"medium","explanation":"Observed value 2.8 versus point 2; signed error 0.8, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.euro-area-unemployment-rate-may-2026.2026-06-06T05-41-31-01-00.a21de549c4f6899d.resolution_event.euro-area-unemployment-rate-may-2026.eurostat-unemployment-rate-euro-area-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.4ffd294b30daa21c","runId":"run.euro-area-unemployment-rate-may-2026.2026-06-06T05-41-31-01-00.a21de549c4f6899d","scoreId":"score.run.euro-area-unemployment-rate-may-2026.2026-06-06T05-41-31-01-00.a21de549c4f6899d.resolution_event.euro-area-unemployment-rate-may-2026.eurostat-unemployment-rate-euro-area-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.4ffd294b30daa21c","predictionId":"euro-area-unemployment-rate-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 6.2 versus point 6.3; signed error -0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.euro-area-unemployment-rate-may-2026.2026-06-17T02-11-36Z.euro-area-unemployment-rate-may-2026-thesis-analyst-fast-2026-06-17t02-11-36z.b758e133d776e4f9.resolution_event.euro-area-unemployment-rate-may-2026.eurostat-unemployment-rate-euro-area-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.b638938e5ebcc637","runId":"run.euro-area-unemployment-rate-may-2026.2026-06-17T02-11-36Z.euro-area-unemployment-rate-may-2026-thesis-analyst-fast-2026-06-17t02-11-36z.b758e133d776e4f9","scoreId":"score.run.euro-area-unemployment-rate-may-2026.2026-06-17T02-11-36Z.euro-area-unemployment-rate-may-2026-thesis-analyst-fast-2026-06-17t02-11-36z.b758e133d776e4f9.resolution_event.euro-area-unemployment-rate-may-2026.eurostat-unemployment-rate-euro-area-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.b638938e5ebcc637","predictionId":"euro-area-unemployment-rate-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 6.2 versus point 6.3; signed error -0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.japan-boj-policy-rate-june-2026.2026-06-06T05-41-31-01-00.69ad79c7595c8466.resolution_event.japan-boj-policy-rate-june-2026.boj-policy-rate-guideline-after-june-2026.numeric_cdf_crps_v3_ledger_scale.179b05a8c46e2302","runId":"run.japan-boj-policy-rate-june-2026.2026-06-06T05-41-31-01-00.69ad79c7595c8466","scoreId":"score.run.japan-boj-policy-rate-june-2026.2026-06-06T05-41-31-01-00.69ad79c7595c8466.resolution_event.japan-boj-policy-rate-june-2026.boj-policy-rate-guideline-after-june-2026.numeric_cdf_crps_v3_ledger_scale.179b05a8c46e2302","predictionId":"japan-boj-policy-rate-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 1 versus point 0.75; signed error 0.25, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.japan-cpi-annual-rate-may-2026.2026-06-06T05-41-31-01-00.322d1a50037ed203.resolution_event.japan-cpi-annual-rate-may-2026.statjp-cpi-all-items-annual-rate-japan-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.2883a99c979f6945","runId":"run.japan-cpi-annual-rate-may-2026.2026-06-06T05-41-31-01-00.322d1a50037ed203","scoreId":"score.run.japan-cpi-annual-rate-may-2026.2026-06-06T05-41-31-01-00.322d1a50037ed203.resolution_event.japan-cpi-annual-rate-may-2026.statjp-cpi-all-items-annual-rate-japan-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.2883a99c979f6945","predictionId":"japan-cpi-annual-rate-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 1.5 versus point 1.5; signed error 0, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.japan-tokyo-cpi-annual-rate-june-2026-prelim.2026-06-06T05-41-31-01-00.816901f948651144.resolution_event.japan-tokyo-cpi-annual-rate-june-2026-prelim.statjp-cpi-tokyo-all-items-annual-rate-june-2026-preliminary.numeric_cdf_crps_v3_ledger_scale.1251366f3ae5d8da","runId":"run.japan-tokyo-cpi-annual-rate-june-2026-prelim.2026-06-06T05-41-31-01-00.816901f948651144","scoreId":"score.run.japan-tokyo-cpi-annual-rate-june-2026-prelim.2026-06-06T05-41-31-01-00.816901f948651144.resolution_event.japan-tokyo-cpi-annual-rate-june-2026-prelim.statjp-cpi-tokyo-all-items-annual-rate-june-2026-preliminary.numeric_cdf_crps_v3_ledger_scale.1251366f3ae5d8da","predictionId":"japan-tokyo-cpi-annual-rate-june-2026-prelim","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 1.7 versus point 1.6; signed error 0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.japan-tokyo-cpi-annual-rate-june-2026-prelim.2026-06-17T02-06-54Z.japan-tokyo-cpi-annual-rate-june-2026-prelim-thesis-analyst-fast-2026-06-17t02-06-54z.820af3753e70b32d.resolution_event.japan-tokyo-cpi-annual-rate-june-2026-prelim.statjp-cpi-tokyo-all-items-annual-rate-june-2026-preliminary.numeric_cdf_crps_v3_ledger_scale.d83f17682b391475","runId":"run.japan-tokyo-cpi-annual-rate-june-2026-prelim.2026-06-17T02-06-54Z.japan-tokyo-cpi-annual-rate-june-2026-prelim-thesis-analyst-fast-2026-06-17t02-06-54z.820af3753e70b32d","scoreId":"score.run.japan-tokyo-cpi-annual-rate-june-2026-prelim.2026-06-17T02-06-54Z.japan-tokyo-cpi-annual-rate-june-2026-prelim-thesis-analyst-fast-2026-06-17t02-06-54z.820af3753e70b32d.resolution_event.japan-tokyo-cpi-annual-rate-june-2026-prelim.statjp-cpi-tokyo-all-items-annual-rate-june-2026-preliminary.numeric_cdf_crps_v3_ledger_scale.d83f17682b391475","predictionId":"japan-tokyo-cpi-annual-rate-june-2026-prelim","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","overreacted_to_recent_data"],"severity":"medium","explanation":"Observed value 1.7 versus point 3.5; signed error -1.8, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.japan-unemployment-rate-may-2026.2026-06-06T05-41-31-01-00.e37f19c9ee504438.resolution_event.japan-unemployment-rate-may-2026.statjp-lfs-unemployment-rate-japan-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.b58dbf81042fc84f","runId":"run.japan-unemployment-rate-may-2026.2026-06-06T05-41-31-01-00.e37f19c9ee504438","scoreId":"score.run.japan-unemployment-rate-may-2026.2026-06-06T05-41-31-01-00.e37f19c9ee504438.resolution_event.japan-unemployment-rate-may-2026.statjp-lfs-unemployment-rate-japan-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.b58dbf81042fc84f","predictionId":"japan-unemployment-rate-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 2.5 versus point 2.5; signed error 0, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.japan-unemployment-rate-may-2026.2026-06-17T02-09-06Z.japan-unemployment-rate-may-2026-thesis-analyst-fast-2026-06-17t02-09-06z.e37f19c9ee504438.resolution_event.japan-unemployment-rate-may-2026.statjp-lfs-unemployment-rate-japan-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.217bdf64868cefbb","runId":"run.japan-unemployment-rate-may-2026.2026-06-17T02-09-06Z.japan-unemployment-rate-may-2026-thesis-analyst-fast-2026-06-17t02-09-06z.e37f19c9ee504438","scoreId":"score.run.japan-unemployment-rate-may-2026.2026-06-17T02-09-06Z.japan-unemployment-rate-may-2026-thesis-analyst-fast-2026-06-17t02-09-06z.e37f19c9ee504438.resolution_event.japan-unemployment-rate-may-2026.statjp-lfs-unemployment-rate-japan-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.217bdf64868cefbb","predictionId":"japan-unemployment-rate-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 2.5 versus point 2.5; signed error 0, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.japan-unemployment-rate-may-2026.2026-06-27T12-57-12Z.japan-unemployment-rate-may-2026-thesis-analyst-fast-2026-06-27t12-57-12z.e37f19c9ee504438.resolution_event.japan-unemployment-rate-may-2026.statjp-lfs-unemployment-rate-japan-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.1a851254d0c5cff3","runId":"run.japan-unemployment-rate-may-2026.2026-06-27T12-57-12Z.japan-unemployment-rate-may-2026-thesis-analyst-fast-2026-06-27t12-57-12z.e37f19c9ee504438","scoreId":"score.run.japan-unemployment-rate-may-2026.2026-06-27T12-57-12Z.japan-unemployment-rate-may-2026-thesis-analyst-fast-2026-06-27t12-57-12z.e37f19c9ee504438.resolution_event.japan-unemployment-rate-may-2026.statjp-lfs-unemployment-rate-japan-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.1a851254d0c5cff3","predictionId":"japan-unemployment-rate-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 2.5 versus point 2.5; signed error 0, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-ppi-final-demand-mom-may-2026.2026-06-06T23-38-51-02-00.fa146519f2c68c9f.resolution_event.us-ppi-final-demand-mom-may-2026.bls-ppi-final-demand-monthly-change-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.29d15a6e12a322ee","runId":"run.us-ppi-final-demand-mom-may-2026.2026-06-06T23-38-51-02-00.fa146519f2c68c9f","scoreId":"score.run.us-ppi-final-demand-mom-may-2026.2026-06-06T23-38-51-02-00.fa146519f2c68c9f.resolution_event.us-ppi-final-demand-mom-may-2026.bls-ppi-final-demand-monthly-change-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.29d15a6e12a322ee","predictionId":"us-ppi-final-demand-mom-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 1.1 versus point 0.5; signed error 0.6, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-industrial-production-mom-may-2026.2026-06-06T23-38-51-02-00.8ff89b7696efc334.resolution_event.us-industrial-production-mom-may-2026.fed-g17-industrial-production-total-index-mom-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.6c3e4710f090c130","runId":"run.us-industrial-production-mom-may-2026.2026-06-06T23-38-51-02-00.8ff89b7696efc334","scoreId":"score.run.us-industrial-production-mom-may-2026.2026-06-06T23-38-51-02-00.8ff89b7696efc334.resolution_event.us-industrial-production-mom-may-2026.fed-g17-industrial-production-total-index-mom-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.6c3e4710f090c130","predictionId":"us-industrial-production-mom-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 0.1 versus point 0.2; signed error -0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-capacity-utilization-may-2026.2026-06-06T23-38-51-02-00.3011388d9eea4524.resolution_event.us-capacity-utilization-may-2026.fed-g17-capacity-utilization-total-industry-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.3e082f9b2b87d841","runId":"run.us-capacity-utilization-may-2026.2026-06-06T23-38-51-02-00.3011388d9eea4524","scoreId":"score.run.us-capacity-utilization-may-2026.2026-06-06T23-38-51-02-00.3011388d9eea4524.resolution_event.us-capacity-utilization-may-2026.fed-g17-capacity-utilization-total-industry-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.3e082f9b2b87d841","predictionId":"us-capacity-utilization-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 76.2 versus point 76.3; signed error -0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-import-price-index-mom-may-2026.2026-06-06T23-38-51-02-00.01f65c25fe12a532.resolution_event.us-import-price-index-mom-may-2026.bls-import-price-index-all-imports-mom-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.9b0610fdde44de61","runId":"run.us-import-price-index-mom-may-2026.2026-06-06T23-38-51-02-00.01f65c25fe12a532","scoreId":"score.run.us-import-price-index-mom-may-2026.2026-06-06T23-38-51-02-00.01f65c25fe12a532.resolution_event.us-import-price-index-mom-may-2026.bls-import-price-index-all-imports-mom-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.9b0610fdde44de61","predictionId":"us-import-price-index-mom-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow"],"severity":"medium","explanation":"Observed value 1.9 versus point 0.6; signed error 1.3, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-housing-starts-may-2026.2026-06-06T23-38-51-02-00.5c86937883be2ced.resolution_event.us-housing-starts-may-2026.census-housing-starts-saar-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.e5fe94225ac3c9ba","runId":"run.us-housing-starts-may-2026.2026-06-06T23-38-51-02-00.5c86937883be2ced","scoreId":"score.run.us-housing-starts-may-2026.2026-06-06T23-38-51-02-00.5c86937883be2ced.resolution_event.us-housing-starts-may-2026.census-housing-starts-saar-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.e5fe94225ac3c9ba","predictionId":"us-housing-starts-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow"],"severity":"medium","explanation":"Observed value 1.177 versus point 1.42; signed error -0.24, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-total-business-inventories-april-2026.2026-06-06T23-38-51-02-00.3cdee8e0afcb01c9.resolution_event.us-total-business-inventories-april-2026.census-mtis-total-business-inventories-level-april-2026-first-print.numeric_cdf_crps_v3_ledger_scale.0c4376038d512eaa","runId":"run.us-total-business-inventories-april-2026.2026-06-06T23-38-51-02-00.3cdee8e0afcb01c9","scoreId":"score.run.us-total-business-inventories-april-2026.2026-06-06T23-38-51-02-00.3cdee8e0afcb01c9.resolution_event.us-total-business-inventories-april-2026.census-mtis-total-business-inventories-level-april-2026-first-print.numeric_cdf_crps_v3_ledger_scale.0c4376038d512eaa","predictionId":"us-total-business-inventories-april-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 2726.6 versus point 2725; signed error 1.6, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-government-social-benefits-may-2026.2026-06-06T23-38-51-02-00.87c8d26875111e13.resolution_event.us-government-social-benefits-may-2026.bea-government-social-benefits-level-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.c179f60776edc531","runId":"run.us-government-social-benefits-may-2026.2026-06-06T23-38-51-02-00.87c8d26875111e13","scoreId":"score.run.us-government-social-benefits-may-2026.2026-06-06T23-38-51-02-00.87c8d26875111e13.resolution_event.us-government-social-benefits-may-2026.bea-government-social-benefits-level-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.c179f60776edc531","predictionId":"us-government-social-benefits-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 5024.4 versus point 4997; signed error 27.4, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-government-social-benefits-may-2026.2026-06-20T09-18-00-04-00.us-government-social-benefits-may-2026-brier-shadow-no-packs.69738dafadec96bc.resolution_event.us-government-social-benefits-may-2026.bea-government-social-benefits-level-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.c1ab0c31ed9303e4","runId":"run.us-government-social-benefits-may-2026.2026-06-20T09-18-00-04-00.us-government-social-benefits-may-2026-brier-shadow-no-packs.69738dafadec96bc","scoreId":"score.run.us-government-social-benefits-may-2026.2026-06-20T09-18-00-04-00.us-government-social-benefits-may-2026-brier-shadow-no-packs.69738dafadec96bc.resolution_event.us-government-social-benefits-may-2026.bea-government-social-benefits-level-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.c1ab0c31ed9303e4","predictionId":"us-government-social-benefits-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 5024.4 versus point 4990; signed error 34.4, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-government-social-benefits-may-2026.2026-06-20T09-18-00-04-00.us-government-social-benefits-may-2026-brier-shadow-with-packs.c5963a98457751a3.resolution_event.us-government-social-benefits-may-2026.bea-government-social-benefits-level-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.02489131ada3258c","runId":"run.us-government-social-benefits-may-2026.2026-06-20T09-18-00-04-00.us-government-social-benefits-may-2026-brier-shadow-with-packs.c5963a98457751a3","scoreId":"score.run.us-government-social-benefits-may-2026.2026-06-20T09-18-00-04-00.us-government-social-benefits-may-2026-brier-shadow-with-packs.c5963a98457751a3.resolution_event.us-government-social-benefits-may-2026.bea-government-social-benefits-level-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.02489131ada3258c","predictionId":"us-government-social-benefits-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 5024.4 versus point 4998; signed error 26.4, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-government-social-benefits-may-2026.2026-06-17T02-25-33Z.us-government-social-benefits-may-2026-thesis-analyst-fast-2026-06-17t02-25-33z.ce8485b32aeb491c.resolution_event.us-government-social-benefits-may-2026.bea-government-social-benefits-level-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.fcf4a553a5ddb589","runId":"run.us-government-social-benefits-may-2026.2026-06-17T02-25-33Z.us-government-social-benefits-may-2026-thesis-analyst-fast-2026-06-17t02-25-33z.ce8485b32aeb491c","scoreId":"score.run.us-government-social-benefits-may-2026.2026-06-17T02-25-33Z.us-government-social-benefits-may-2026-thesis-analyst-fast-2026-06-17t02-25-33z.ce8485b32aeb491c.resolution_event.us-government-social-benefits-may-2026.bea-government-social-benefits-level-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.fcf4a553a5ddb589","predictionId":"us-government-social-benefits-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","bad_baseline"],"severity":"medium","explanation":"Observed value 5024.4 versus point 4315; signed error 709.4, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-social-security-benefits-may-2026.2026-06-06T23-38-51-02-00.4e7a1e6173be29c9.resolution_event.us-social-security-benefits-may-2026.bea-government-social-benefits-social-security-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.15625c34e9d5a9c8","runId":"run.us-social-security-benefits-may-2026.2026-06-06T23-38-51-02-00.4e7a1e6173be29c9","scoreId":"score.run.us-social-security-benefits-may-2026.2026-06-06T23-38-51-02-00.4e7a1e6173be29c9.resolution_event.us-social-security-benefits-may-2026.bea-government-social-benefits-social-security-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.15625c34e9d5a9c8","predictionId":"us-social-security-benefits-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 1638.1 versus point 1650; signed error -11.9, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-social-security-benefits-may-2026.2026-06-20T09-26-00-04-00.us-social-security-benefits-may-2026-brier-shadow-no-packs.1f4337ea0b1ac273.resolution_event.us-social-security-benefits-may-2026.bea-government-social-benefits-social-security-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.83ac35a913c63674","runId":"run.us-social-security-benefits-may-2026.2026-06-20T09-26-00-04-00.us-social-security-benefits-may-2026-brier-shadow-no-packs.1f4337ea0b1ac273","scoreId":"score.run.us-social-security-benefits-may-2026.2026-06-20T09-26-00-04-00.us-social-security-benefits-may-2026-brier-shadow-no-packs.1f4337ea0b1ac273.resolution_event.us-social-security-benefits-may-2026.bea-government-social-benefits-social-security-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.83ac35a913c63674","predictionId":"us-social-security-benefits-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 1638.1 versus point 1650; signed error -11.9, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-social-security-benefits-may-2026.2026-06-20T09-26-00-04-00.us-social-security-benefits-may-2026-brier-shadow-with-packs.d7fc803aafb5598d.resolution_event.us-social-security-benefits-may-2026.bea-government-social-benefits-social-security-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.75efad624b8366f9","runId":"run.us-social-security-benefits-may-2026.2026-06-20T09-26-00-04-00.us-social-security-benefits-may-2026-brier-shadow-with-packs.d7fc803aafb5598d","scoreId":"score.run.us-social-security-benefits-may-2026.2026-06-20T09-26-00-04-00.us-social-security-benefits-may-2026-brier-shadow-with-packs.d7fc803aafb5598d.resolution_event.us-social-security-benefits-may-2026.bea-government-social-benefits-social-security-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.75efad624b8366f9","predictionId":"us-social-security-benefits-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow"],"severity":"medium","explanation":"Observed value 1638.1 versus point 1651; signed error -12.9, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-social-security-benefits-may-2026.2026-06-17T02-28-12Z.us-social-security-benefits-may-2026-thesis-analyst-fast-2026-06-17t02-28-12z.cf96b21cc17d8b49.resolution_event.us-social-security-benefits-may-2026.bea-government-social-benefits-social-security-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.4412310749f95e79","runId":"run.us-social-security-benefits-may-2026.2026-06-17T02-28-12Z.us-social-security-benefits-may-2026-thesis-analyst-fast-2026-06-17t02-28-12z.cf96b21cc17d8b49","scoreId":"score.run.us-social-security-benefits-may-2026.2026-06-17T02-28-12Z.us-social-security-benefits-may-2026-thesis-analyst-fast-2026-06-17t02-28-12z.cf96b21cc17d8b49.resolution_event.us-social-security-benefits-may-2026.bea-government-social-benefits-social-security-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.4412310749f95e79","predictionId":"us-social-security-benefits-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 1638.1 versus point 1650.5; signed error -12.4, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-medicare-benefits-may-2026.2026-06-06T23-38-51-02-00.a4e2e7c259e06a10.resolution_event.us-medicare-benefits-may-2026.bea-government-social-benefits-medicare-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.6ca0cb708659476e","runId":"run.us-medicare-benefits-may-2026.2026-06-06T23-38-51-02-00.a4e2e7c259e06a10","scoreId":"score.run.us-medicare-benefits-may-2026.2026-06-06T23-38-51-02-00.a4e2e7c259e06a10.resolution_event.us-medicare-benefits-may-2026.bea-government-social-benefits-medicare-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.6ca0cb708659476e","predictionId":"us-medicare-benefits-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 1332 versus point 1332; signed error 0, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-medicare-benefits-may-2026.2026-06-20T09-22-00-04-00.us-medicare-benefits-may-2026-brier-shadow-no-packs.7ad3492c262cd5f9.resolution_event.us-medicare-benefits-may-2026.bea-government-social-benefits-medicare-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.2c9e34bafb2db345","runId":"run.us-medicare-benefits-may-2026.2026-06-20T09-22-00-04-00.us-medicare-benefits-may-2026-brier-shadow-no-packs.7ad3492c262cd5f9","scoreId":"score.run.us-medicare-benefits-may-2026.2026-06-20T09-22-00-04-00.us-medicare-benefits-may-2026-brier-shadow-no-packs.7ad3492c262cd5f9.resolution_event.us-medicare-benefits-may-2026.bea-government-social-benefits-medicare-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.2c9e34bafb2db345","predictionId":"us-medicare-benefits-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 1332 versus point 1330; signed error 2, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-medicare-benefits-may-2026.2026-06-20T09-22-00-04-00.us-medicare-benefits-may-2026-brier-shadow-with-packs.c9477e6f59376fda.resolution_event.us-medicare-benefits-may-2026.bea-government-social-benefits-medicare-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.13a2d8fc63d4ca38","runId":"run.us-medicare-benefits-may-2026.2026-06-20T09-22-00-04-00.us-medicare-benefits-may-2026-brier-shadow-with-packs.c9477e6f59376fda","scoreId":"score.run.us-medicare-benefits-may-2026.2026-06-20T09-22-00-04-00.us-medicare-benefits-may-2026-brier-shadow-with-packs.c9477e6f59376fda.resolution_event.us-medicare-benefits-may-2026.bea-government-social-benefits-medicare-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.13a2d8fc63d4ca38","predictionId":"us-medicare-benefits-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 1332 versus point 1332; signed error 0, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-medicare-benefits-may-2026.2026-06-17T02-30-40Z.us-medicare-benefits-may-2026-thesis-analyst-fast-2026-06-17t02-30-40z.db67f245ae2e03b6.resolution_event.us-medicare-benefits-may-2026.bea-government-social-benefits-medicare-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.f394ae6ca709b493","runId":"run.us-medicare-benefits-may-2026.2026-06-17T02-30-40Z.us-medicare-benefits-may-2026-thesis-analyst-fast-2026-06-17t02-30-40z.db67f245ae2e03b6","scoreId":"score.run.us-medicare-benefits-may-2026.2026-06-17T02-30-40Z.us-medicare-benefits-may-2026-thesis-analyst-fast-2026-06-17t02-30-40z.db67f245ae2e03b6.resolution_event.us-medicare-benefits-may-2026.bea-government-social-benefits-medicare-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.f394ae6ca709b493","predictionId":"us-medicare-benefits-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 1332 versus point 1332; signed error 0, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-medicaid-benefits-may-2026.2026-06-06T23-38-51-02-00.75d73aadc6fe4414.resolution_event.us-medicaid-benefits-may-2026.bea-government-social-benefits-medicaid-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.c60ec715494d5ded","runId":"run.us-medicaid-benefits-may-2026.2026-06-06T23-38-51-02-00.75d73aadc6fe4414","scoreId":"score.run.us-medicaid-benefits-may-2026.2026-06-06T23-38-51-02-00.75d73aadc6fe4414.resolution_event.us-medicaid-benefits-may-2026.bea-government-social-benefits-medicaid-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.c60ec715494d5ded","predictionId":"us-medicaid-benefits-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 1052.2 versus point 1041; signed error 11.2, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-medicaid-benefits-may-2026.2026-06-20T09-20-00-04-00.us-medicaid-benefits-may-2026-brier-shadow-no-packs.40bad49af49275cc.resolution_event.us-medicaid-benefits-may-2026.bea-government-social-benefits-medicaid-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.1d59dcdc036bfafe","runId":"run.us-medicaid-benefits-may-2026.2026-06-20T09-20-00-04-00.us-medicaid-benefits-may-2026-brier-shadow-no-packs.40bad49af49275cc","scoreId":"score.run.us-medicaid-benefits-may-2026.2026-06-20T09-20-00-04-00.us-medicaid-benefits-may-2026-brier-shadow-no-packs.40bad49af49275cc.resolution_event.us-medicaid-benefits-may-2026.bea-government-social-benefits-medicaid-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.1d59dcdc036bfafe","predictionId":"us-medicaid-benefits-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 1052.2 versus point 1038; signed error 14.2, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-medicaid-benefits-may-2026.2026-06-20T09-20-00-04-00.us-medicaid-benefits-may-2026-brier-shadow-with-packs.735eb2bf91f9ec80.resolution_event.us-medicaid-benefits-may-2026.bea-government-social-benefits-medicaid-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.b12e1140b15c6f46","runId":"run.us-medicaid-benefits-may-2026.2026-06-20T09-20-00-04-00.us-medicaid-benefits-may-2026-brier-shadow-with-packs.735eb2bf91f9ec80","scoreId":"score.run.us-medicaid-benefits-may-2026.2026-06-20T09-20-00-04-00.us-medicaid-benefits-may-2026-brier-shadow-with-packs.735eb2bf91f9ec80.resolution_event.us-medicaid-benefits-may-2026.bea-government-social-benefits-medicaid-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.b12e1140b15c6f46","predictionId":"us-medicaid-benefits-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 1052.2 versus point 1041; signed error 11.2, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-medicaid-benefits-may-2026.2026-06-17T02-31-13Z.us-medicaid-benefits-may-2026-thesis-analyst-fast-2026-06-17t02-31-13z.39ee018922fc2ff9.resolution_event.us-medicaid-benefits-may-2026.bea-government-social-benefits-medicaid-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.ac7aa4d1807320cb","runId":"run.us-medicaid-benefits-may-2026.2026-06-17T02-31-13Z.us-medicaid-benefits-may-2026-thesis-analyst-fast-2026-06-17t02-31-13z.39ee018922fc2ff9","scoreId":"score.run.us-medicaid-benefits-may-2026.2026-06-17T02-31-13Z.us-medicaid-benefits-may-2026-thesis-analyst-fast-2026-06-17t02-31-13z.39ee018922fc2ff9.resolution_event.us-medicaid-benefits-may-2026.bea-government-social-benefits-medicaid-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.ac7aa4d1807320cb","predictionId":"us-medicaid-benefits-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 1052.2 versus point 1037.5; signed error 14.7, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-wages-and-salaries-may-2026.2026-06-06T23-38-51-02-00.56301f7913c70767.resolution_event.us-wages-and-salaries-may-2026.bea-wages-and-salaries-level-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.7630f449a06815ea","runId":"run.us-wages-and-salaries-may-2026.2026-06-06T23-38-51-02-00.56301f7913c70767","scoreId":"score.run.us-wages-and-salaries-may-2026.2026-06-06T23-38-51-02-00.56301f7913c70767.resolution_event.us-wages-and-salaries-may-2026.bea-wages-and-salaries-level-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.7630f449a06815ea","predictionId":"us-wages-and-salaries-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 13388.8 versus point 13350; signed error 38.8, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-wages-and-salaries-may-2026.2026-06-20T09-28-00-04-00.us-wages-and-salaries-may-2026-brier-shadow-no-packs.58c215a2d5f18576.resolution_event.us-wages-and-salaries-may-2026.bea-wages-and-salaries-level-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.769c3c35a5e82a66","runId":"run.us-wages-and-salaries-may-2026.2026-06-20T09-28-00-04-00.us-wages-and-salaries-may-2026-brier-shadow-no-packs.58c215a2d5f18576","scoreId":"score.run.us-wages-and-salaries-may-2026.2026-06-20T09-28-00-04-00.us-wages-and-salaries-may-2026-brier-shadow-no-packs.58c215a2d5f18576.resolution_event.us-wages-and-salaries-may-2026.bea-wages-and-salaries-level-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.769c3c35a5e82a66","predictionId":"us-wages-and-salaries-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 13388.8 versus point 13345; signed error 43.8, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-wages-and-salaries-may-2026.2026-06-20T09-28-00-04-00.us-wages-and-salaries-may-2026-brier-shadow-with-packs.e8735f06ad784f28.resolution_event.us-wages-and-salaries-may-2026.bea-wages-and-salaries-level-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.aebbc3a06078611e","runId":"run.us-wages-and-salaries-may-2026.2026-06-20T09-28-00-04-00.us-wages-and-salaries-may-2026-brier-shadow-with-packs.e8735f06ad784f28","scoreId":"score.run.us-wages-and-salaries-may-2026.2026-06-20T09-28-00-04-00.us-wages-and-salaries-may-2026-brier-shadow-with-packs.e8735f06ad784f28.resolution_event.us-wages-and-salaries-may-2026.bea-wages-and-salaries-level-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.aebbc3a06078611e","predictionId":"us-wages-and-salaries-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 13388.8 versus point 13362; signed error 26.8, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-wages-and-salaries-may-2026.2026-06-17T02-32-16Z.us-wages-and-salaries-may-2026-thesis-analyst-fast-2026-06-17t02-32-16z.196d6bb575f0d44a.resolution_event.us-wages-and-salaries-may-2026.bea-wages-and-salaries-level-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.c116089758218220","runId":"run.us-wages-and-salaries-may-2026.2026-06-17T02-32-16Z.us-wages-and-salaries-may-2026-thesis-analyst-fast-2026-06-17t02-32-16z.196d6bb575f0d44a","scoreId":"score.run.us-wages-and-salaries-may-2026.2026-06-17T02-32-16Z.us-wages-and-salaries-may-2026-thesis-analyst-fast-2026-06-17t02-32-16z.196d6bb575f0d44a.resolution_event.us-wages-and-salaries-may-2026.bea-wages-and-salaries-level-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.c116089758218220","predictionId":"us-wages-and-salaries-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 13388.8 versus point 13365; signed error 23.8, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-personal-current-taxes-may-2026.2026-06-06T23-38-51-02-00.86ed22e0754757f2.resolution_event.us-personal-current-taxes-may-2026.bea-personal-current-taxes-level-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.9f34343c0e53c020","runId":"run.us-personal-current-taxes-may-2026.2026-06-06T23-38-51-02-00.86ed22e0754757f2","scoreId":"score.run.us-personal-current-taxes-may-2026.2026-06-06T23-38-51-02-00.86ed22e0754757f2.resolution_event.us-personal-current-taxes-may-2026.bea-personal-current-taxes-level-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.9f34343c0e53c020","predictionId":"us-personal-current-taxes-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 3264.7 versus point 3266.8; signed error -2.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-personal-current-taxes-may-2026.2026-06-20T09-24-00-04-00.us-personal-current-taxes-may-2026-brier-shadow-no-packs.659464a73f7283ad.resolution_event.us-personal-current-taxes-may-2026.bea-personal-current-taxes-level-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.66d9e2a336b568fa","runId":"run.us-personal-current-taxes-may-2026.2026-06-20T09-24-00-04-00.us-personal-current-taxes-may-2026-brier-shadow-no-packs.659464a73f7283ad","scoreId":"score.run.us-personal-current-taxes-may-2026.2026-06-20T09-24-00-04-00.us-personal-current-taxes-may-2026-brier-shadow-no-packs.659464a73f7283ad.resolution_event.us-personal-current-taxes-may-2026.bea-personal-current-taxes-level-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.66d9e2a336b568fa","predictionId":"us-personal-current-taxes-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 3264.7 versus point 3262; signed error 2.7, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-personal-current-taxes-may-2026.2026-06-20T09-24-00-04-00.us-personal-current-taxes-may-2026-brier-shadow-with-packs.c8bf9f9dec6e3bdf.resolution_event.us-personal-current-taxes-may-2026.bea-personal-current-taxes-level-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.7f7942a722a3732b","runId":"run.us-personal-current-taxes-may-2026.2026-06-20T09-24-00-04-00.us-personal-current-taxes-may-2026-brier-shadow-with-packs.c8bf9f9dec6e3bdf","scoreId":"score.run.us-personal-current-taxes-may-2026.2026-06-20T09-24-00-04-00.us-personal-current-taxes-may-2026-brier-shadow-with-packs.c8bf9f9dec6e3bdf.resolution_event.us-personal-current-taxes-may-2026.bea-personal-current-taxes-level-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.7f7942a722a3732b","predictionId":"us-personal-current-taxes-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 3264.7 versus point 3268; signed error -3.3, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-disposable-personal-income-may-2026.2026-06-06T23-38-51-02-00.fbaa86ff9646b959.resolution_event.us-disposable-personal-income-may-2026.bea-disposable-personal-income-level-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.280555525bf2ec99","runId":"run.us-disposable-personal-income-may-2026.2026-06-06T23-38-51-02-00.fbaa86ff9646b959","scoreId":"score.run.us-disposable-personal-income-may-2026.2026-06-06T23-38-51-02-00.fbaa86ff9646b959.resolution_event.us-disposable-personal-income-may-2026.bea-disposable-personal-income-level-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.280555525bf2ec99","predictionId":"us-disposable-personal-income-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","bad_baseline"],"severity":"medium","explanation":"Observed value 23651.7 versus point 23512; signed error 139.7, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-disposable-personal-income-may-2026.2026-06-20T09-16-00-04-00.us-disposable-personal-income-may-2026-brier-shadow-no-packs.9e1e0917f29c9578.resolution_event.us-disposable-personal-income-may-2026.bea-disposable-personal-income-level-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.5f84bfc25d80dd65","runId":"run.us-disposable-personal-income-may-2026.2026-06-20T09-16-00-04-00.us-disposable-personal-income-may-2026-brier-shadow-no-packs.9e1e0917f29c9578","scoreId":"score.run.us-disposable-personal-income-may-2026.2026-06-20T09-16-00-04-00.us-disposable-personal-income-may-2026-brier-shadow-no-packs.9e1e0917f29c9578.resolution_event.us-disposable-personal-income-may-2026.bea-disposable-personal-income-level-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.5f84bfc25d80dd65","predictionId":"us-disposable-personal-income-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow"],"severity":"medium","explanation":"Observed value 23651.7 versus point 23500; signed error 151.7, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-disposable-personal-income-may-2026.2026-06-20T09-16-00-04-00.us-disposable-personal-income-may-2026-brier-shadow-with-packs.e6b570278bfe0d60.resolution_event.us-disposable-personal-income-may-2026.bea-disposable-personal-income-level-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.f8318e40d689935d","runId":"run.us-disposable-personal-income-may-2026.2026-06-20T09-16-00-04-00.us-disposable-personal-income-may-2026-brier-shadow-with-packs.e6b570278bfe0d60","scoreId":"score.run.us-disposable-personal-income-may-2026.2026-06-20T09-16-00-04-00.us-disposable-personal-income-may-2026-brier-shadow-with-packs.e6b570278bfe0d60.resolution_event.us-disposable-personal-income-may-2026.bea-disposable-personal-income-level-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.f8318e40d689935d","predictionId":"us-disposable-personal-income-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","bad_baseline"],"severity":"medium","explanation":"Observed value 23651.7 versus point 23520; signed error 131.7, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-pce-price-index-mom-may-2026.2026-06-06T23-38-51-02-00.cea33ec3f6750270.resolution_event.us-pce-price-index-mom-may-2026.bea-pce-price-index-monthly-change-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.9204d0dcda42d4a4","runId":"run.us-pce-price-index-mom-may-2026.2026-06-06T23-38-51-02-00.cea33ec3f6750270","scoreId":"score.run.us-pce-price-index-mom-may-2026.2026-06-06T23-38-51-02-00.cea33ec3f6750270.resolution_event.us-pce-price-index-mom-may-2026.bea-pce-price-index-monthly-change-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.9204d0dcda42d4a4","predictionId":"us-pce-price-index-mom-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 0.4 versus point 0.3; signed error 0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-real-gdp-q1-2026-third-estimate.2026-06-06T23-38-51-02-00.322d1a50037ed203.resolution_event.us-real-gdp-q1-2026-third-estimate.bea-real-gdp-saar-q1-2026-third-estimate.numeric_cdf_crps_v3_ledger_scale.e9889c40b2313067","runId":"run.us-real-gdp-q1-2026-third-estimate.2026-06-06T23-38-51-02-00.322d1a50037ed203","scoreId":"score.run.us-real-gdp-q1-2026-third-estimate.2026-06-06T23-38-51-02-00.322d1a50037ed203.resolution_event.us-real-gdp-q1-2026-third-estimate.bea-real-gdp-saar-q1-2026-third-estimate.numeric_cdf_crps_v3_ledger_scale.e9889c40b2313067","predictionId":"us-real-gdp-q1-2026-third-estimate","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","bad_baseline"],"severity":"medium","explanation":"Observed value 2.1 versus point 1.5; signed error 0.6, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-mts-deficit-may-2026.2026-06-06T23-38-51-02-00.05f5c512919cbbbd.resolution_event.us-mts-deficit-may-2026.treasury-mts-monthly-deficit-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.1ceccaed0d73a763","runId":"run.us-mts-deficit-may-2026.2026-06-06T23-38-51-02-00.05f5c512919cbbbd","scoreId":"score.run.us-mts-deficit-may-2026.2026-06-06T23-38-51-02-00.05f5c512919cbbbd.resolution_event.us-mts-deficit-may-2026.treasury-mts-monthly-deficit-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.1ceccaed0d73a763","predictionId":"us-mts-deficit-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 292.6 versus point 305; signed error -12.4, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.cps-business-financial-employment-june-2026.2026-06-21T23-05-00-04-00.d2573c81fc742fd1.resolution_event.cps-business-financial-employment-june-2026.bls-cps-employed-people-by-occupation-business-financial-operations-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.9291739403a8e9fb","runId":"run.cps-business-financial-employment-june-2026.2026-06-21T23-05-00-04-00.d2573c81fc742fd1","scoreId":"score.run.cps-business-financial-employment-june-2026.2026-06-21T23-05-00-04-00.d2573c81fc742fd1.resolution_event.cps-business-financial-employment-june-2026.bls-cps-employed-people-by-occupation-business-financial-operations-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.9291739403a8e9fb","predictionId":"cps-business-financial-employment-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 9720 versus point 10040; signed error -320, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.cps-computer-math-employment-june-2026.2026-06-21T23-05-00-04-00.514bfdba76ace25f.resolution_event.cps-computer-math-employment-june-2026.bls-cps-employed-people-by-occupation-computer-mathematical-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.585cf2735d45f915","runId":"run.cps-computer-math-employment-june-2026.2026-06-21T23-05-00-04-00.514bfdba76ace25f","scoreId":"score.run.cps-computer-math-employment-june-2026.2026-06-21T23-05-00-04-00.514bfdba76ace25f.resolution_event.cps-computer-math-employment-june-2026.bls-cps-employed-people-by-occupation-computer-mathematical-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.585cf2735d45f915","predictionId":"cps-computer-math-employment-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 6950 versus point 6920; signed error 30, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.cps-healthcare-support-employment-june-2026.2026-06-21T23-05-00-04-00.72f6884ba93c164f.resolution_event.cps-healthcare-support-employment-june-2026.bls-cps-employed-people-by-occupation-healthcare-support-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.9732c539af6c0b43","runId":"run.cps-healthcare-support-employment-june-2026.2026-06-21T23-05-00-04-00.72f6884ba93c164f","scoreId":"score.run.cps-healthcare-support-employment-june-2026.2026-06-21T23-05-00-04-00.72f6884ba93c164f.resolution_event.cps-healthcare-support-employment-june-2026.bls-cps-employed-people-by-occupation-healthcare-support-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.9732c539af6c0b43","predictionId":"cps-healthcare-support-employment-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 5691 versus point 5800; signed error -109, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.cps-office-admin-employment-june-2026.2026-06-21T23-05-00-04-00.32ebfd164a026243.resolution_event.cps-office-admin-employment-june-2026.bls-cps-employed-people-by-occupation-office-administrative-support-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.45e20f0c29d2492b","runId":"run.cps-office-admin-employment-june-2026.2026-06-21T23-05-00-04-00.32ebfd164a026243","scoreId":"score.run.cps-office-admin-employment-june-2026.2026-06-21T23-05-00-04-00.32ebfd164a026243.resolution_event.cps-office-admin-employment-june-2026.bls-cps-employed-people-by-occupation-office-administrative-support-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.45e20f0c29d2492b","predictionId":"cps-office-admin-employment-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 16184 versus point 16300; signed error -116, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.cps-production-employment-june-2026.2026-06-21T23-05-00-04-00.7b4ee5a440dfaa75.resolution_event.cps-production-employment-june-2026.bls-cps-employed-people-by-occupation-production-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.56108fe130fe0def","runId":"run.cps-production-employment-june-2026.2026-06-21T23-05-00-04-00.7b4ee5a440dfaa75","scoreId":"score.run.cps-production-employment-june-2026.2026-06-21T23-05-00-04-00.7b4ee5a440dfaa75.resolution_event.cps-production-employment-june-2026.bls-cps-employed-people-by-occupation-production-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.56108fe130fe0def","predictionId":"cps-production-employment-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 7759 versus point 7900; signed error -141, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.cps-transport-material-moving-employment-june-2026.2026-06-21T23-05-00-04-00.a340f0bd23559c3f.resolution_event.cps-transport-material-moving-employment-june-2026.bls-cps-employed-people-by-occupation-transportation-material-moving-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.7c0bf7d8c1b60742","runId":"run.cps-transport-material-moving-employment-june-2026.2026-06-21T23-05-00-04-00.a340f0bd23559c3f","scoreId":"score.run.cps-transport-material-moving-employment-june-2026.2026-06-21T23-05-00-04-00.a340f0bd23559c3f.resolution_event.cps-transport-material-moving-employment-june-2026.bls-cps-employed-people-by-occupation-transportation-material-moving-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.7c0bf7d8c1b60742","predictionId":"cps-transport-material-moving-employment-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 12010 versus point 12100; signed error -90, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.canada-retail-sales-growth-april-2026.2026-06-06T14-42-00-02-00.a130b5ea020cf429.resolution_event.canada-retail-sales-growth-april-2026.statcan-retail-trade-sales-mom-canada-april-2026-first-print.numeric_cdf_crps_v3_ledger_scale.4903f6f56cc8287a","runId":"run.canada-retail-sales-growth-april-2026.2026-06-06T14-42-00-02-00.a130b5ea020cf429","scoreId":"score.run.canada-retail-sales-growth-april-2026.2026-06-06T14-42-00-02-00.a130b5ea020cf429.resolution_event.canada-retail-sales-growth-april-2026.statcan-retail-trade-sales-mom-canada-april-2026-first-print.numeric_cdf_crps_v3_ledger_scale.4903f6f56cc8287a","predictionId":"canada-retail-sales-growth-april-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 0.5 versus point 0.6; signed error -0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.canada-wholesale-sales-growth-april-2026.2026-06-06T14-42-00-02-00.413bad36afb920f7.resolution_event.canada-wholesale-sales-growth-april-2026.statcan-wholesale-trade-sales-mom-exclusions-canada-april-2026-first-print.numeric_cdf_crps_v3_ledger_scale.4f6126260c820e0a","runId":"run.canada-wholesale-sales-growth-april-2026.2026-06-06T14-42-00-02-00.413bad36afb920f7","scoreId":"score.run.canada-wholesale-sales-growth-april-2026.2026-06-06T14-42-00-02-00.413bad36afb920f7.resolution_event.canada-wholesale-sales-growth-april-2026.statcan-wholesale-trade-sales-mom-exclusions-canada-april-2026-first-print.numeric_cdf_crps_v3_ledger_scale.4f6126260c820e0a","predictionId":"canada-wholesale-sales-growth-april-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 0.6 versus point 0.2; signed error 0.4, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.canada-ei-regular-beneficiaries-april-2026.2026-06-06T14-42-00-02-00.c949828e7e5cdc48.resolution_event.canada-ei-regular-beneficiaries-april-2026.statcan-employment-insurance-regular-beneficiaries-canada-april-2026-first-print.numeric_cdf_crps_v3_ledger_scale.41370e3e4d56633c","runId":"run.canada-ei-regular-beneficiaries-april-2026.2026-06-06T14-42-00-02-00.c949828e7e5cdc48","scoreId":"score.run.canada-ei-regular-beneficiaries-april-2026.2026-06-06T14-42-00-02-00.c949828e7e5cdc48.resolution_event.canada-ei-regular-beneficiaries-april-2026.statcan-employment-insurance-regular-beneficiaries-canada-april-2026-first-print.numeric_cdf_crps_v3_ledger_scale.41370e3e4d56633c","predictionId":"canada-ei-regular-beneficiaries-april-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 544.44 versus point 552; signed error -7.56, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.canada-ei-regular-beneficiaries-april-2026.2026-06-17T02-00-14Z.canada-ei-regular-beneficiaries-april-2026-thesis-analyst-fast-2026-06-17t02-00-14z.592df1265c4f19e6.resolution_event.canada-ei-regular-beneficiaries-april-2026.statcan-employment-insurance-regular-beneficiaries-canada-april-2026-first-print.numeric_cdf_crps_v3_ledger_scale.e1db1ebaa0a471bd","runId":"run.canada-ei-regular-beneficiaries-april-2026.2026-06-17T02-00-14Z.canada-ei-regular-beneficiaries-april-2026-thesis-analyst-fast-2026-06-17t02-00-14z.592df1265c4f19e6","scoreId":"score.run.canada-ei-regular-beneficiaries-april-2026.2026-06-17T02-00-14Z.canada-ei-regular-beneficiaries-april-2026-thesis-analyst-fast-2026-06-17t02-00-14z.592df1265c4f19e6.resolution_event.canada-ei-regular-beneficiaries-april-2026.statcan-employment-insurance-regular-beneficiaries-canada-april-2026-first-print.numeric_cdf_crps_v3_ledger_scale.e1db1ebaa0a471bd","predictionId":"canada-ei-regular-beneficiaries-april-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 544.44 versus point 556; signed error -11.56, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.canada-building-permit-value-growth-april-2026.2026-06-06T14-42-00-02-00.6745e7df831e7e70.resolution_event.canada-building-permit-value-growth-april-2026.statcan-building-permits-total-value-mom-canada-april-2026-first-print.numeric_cdf_crps_v3_ledger_scale.6093d002d5d46018","runId":"run.canada-building-permit-value-growth-april-2026.2026-06-06T14-42-00-02-00.6745e7df831e7e70","scoreId":"score.run.canada-building-permit-value-growth-april-2026.2026-06-06T14-42-00-02-00.6745e7df831e7e70.resolution_event.canada-building-permit-value-growth-april-2026.statcan-building-permits-total-value-mom-canada-april-2026-first-print.numeric_cdf_crps_v3_ledger_scale.6093d002d5d46018","predictionId":"canada-building-permit-value-growth-april-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value -7.6 versus point -2; signed error -5.6, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.euro-area-industrial-production-growth-april-2026.2026-06-06T14-42-00-02-00.68380e4126f975e1.resolution_event.euro-area-industrial-production-growth-april-2026.eurostat-industrial-production-euro-area-april-2026-first-print.numeric_cdf_crps_v3_ledger_scale.f2bbb55d310435e5","runId":"run.euro-area-industrial-production-growth-april-2026.2026-06-06T14-42-00-02-00.68380e4126f975e1","scoreId":"score.run.euro-area-industrial-production-growth-april-2026.2026-06-06T14-42-00-02-00.68380e4126f975e1.resolution_event.euro-area-industrial-production-growth-april-2026.eurostat-industrial-production-euro-area-april-2026-first-print.numeric_cdf_crps_v3_ledger_scale.f2bbb55d310435e5","predictionId":"euro-area-industrial-production-growth-april-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 0.1 versus point 0; signed error 0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.euro-area-retail-trade-volume-growth-may-2026.2026-06-06T14-42-00-02-00.987df99045d5dcd8.resolution_event.euro-area-retail-trade-volume-growth-may-2026.eurostat-retail-trade-volume-mom-euro-area-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.7d441bd8a08909ec","runId":"run.euro-area-retail-trade-volume-growth-may-2026.2026-06-06T14-42-00-02-00.987df99045d5dcd8","scoreId":"score.run.euro-area-retail-trade-volume-growth-may-2026.2026-06-06T14-42-00-02-00.987df99045d5dcd8.resolution_event.euro-area-retail-trade-volume-growth-may-2026.eurostat-retail-trade-volume-mom-euro-area-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.7d441bd8a08909ec","predictionId":"euro-area-retail-trade-volume-growth-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 0.2 versus point 0.1; signed error 0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.euro-area-retail-trade-volume-growth-may-2026.2026-06-17T02-13-28Z.euro-area-retail-trade-volume-growth-may-2026-thesis-analyst-fast-2026-06-17t02-13-28z.0d172093b6765fb2.resolution_event.euro-area-retail-trade-volume-growth-may-2026.eurostat-retail-trade-volume-mom-euro-area-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.905314b13b912df5","runId":"run.euro-area-retail-trade-volume-growth-may-2026.2026-06-17T02-13-28Z.euro-area-retail-trade-volume-growth-may-2026-thesis-analyst-fast-2026-06-17t02-13-28z.0d172093b6765fb2","scoreId":"score.run.euro-area-retail-trade-volume-growth-may-2026.2026-06-17T02-13-28Z.euro-area-retail-trade-volume-growth-may-2026-thesis-analyst-fast-2026-06-17t02-13-28z.0d172093b6765fb2.resolution_event.euro-area-retail-trade-volume-growth-may-2026.eurostat-retail-trade-volume-mom-euro-area-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.905314b13b912df5","predictionId":"euro-area-retail-trade-volume-growth-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 0.2 versus point 0.1; signed error 0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.australia-dwelling-approvals-growth-may-2026.2026-06-06T14-42-00-02-00.1fa2f73ddc6580b2.resolution_event.australia-dwelling-approvals-growth-may-2026.abs-building-approvals-total-dwellings-mom-australia-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.6869877a41619b7d","runId":"run.australia-dwelling-approvals-growth-may-2026.2026-06-06T14-42-00-02-00.1fa2f73ddc6580b2","scoreId":"score.run.australia-dwelling-approvals-growth-may-2026.2026-06-06T14-42-00-02-00.1fa2f73ddc6580b2.resolution_event.australia-dwelling-approvals-growth-may-2026.abs-building-approvals-total-dwellings-mom-australia-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.6869877a41619b7d","predictionId":"australia-dwelling-approvals-growth-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value -1.1 versus point 2; signed error -3.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.australia-dwelling-approvals-growth-may-2026.2026-06-27T13-11-37Z.australia-dwelling-approvals-growth-may-2026-thesis-analyst-fast-2026-06-27t13-11-37z.b4d958b37a680b40.resolution_event.australia-dwelling-approvals-growth-may-2026.abs-building-approvals-total-dwellings-mom-australia-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.0419651ea8b24467","runId":"run.australia-dwelling-approvals-growth-may-2026.2026-06-27T13-11-37Z.australia-dwelling-approvals-growth-may-2026-thesis-analyst-fast-2026-06-27t13-11-37z.b4d958b37a680b40","scoreId":"score.run.australia-dwelling-approvals-growth-may-2026.2026-06-27T13-11-37Z.australia-dwelling-approvals-growth-may-2026-thesis-analyst-fast-2026-06-27t13-11-37z.b4d958b37a680b40.resolution_event.australia-dwelling-approvals-growth-may-2026.abs-building-approvals-total-dwellings-mom-australia-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.0419651ea8b24467","predictionId":"australia-dwelling-approvals-growth-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value -1.1 versus point 2; signed error -3.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.japan-real-household-spending-growth-may-2026.2026-06-06T14-42-00-02-00.67483722e0444e3b.resolution_event.japan-real-household-spending-growth-may-2026.statjp-household-spending-real-yoy-two-or-more-person-households-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.76d6ea08c6b26eef","runId":"run.japan-real-household-spending-growth-may-2026.2026-06-06T14-42-00-02-00.67483722e0444e3b","scoreId":"score.run.japan-real-household-spending-growth-may-2026.2026-06-06T14-42-00-02-00.67483722e0444e3b.resolution_event.japan-real-household-spending-growth-may-2026.statjp-household-spending-real-yoy-two-or-more-person-households-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.76d6ea08c6b26eef","predictionId":"japan-real-household-spending-growth-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value -0.4 versus point -0.3; signed error -0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.japan-real-household-spending-growth-may-2026.2026-06-27T13-19-13Z.japan-real-household-spending-growth-may-2026-thesis-analyst-fast-2026-06-27t13-19-13z.1fc5a6e21b190f18.resolution_event.japan-real-household-spending-growth-may-2026.statjp-household-spending-real-yoy-two-or-more-person-households-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.3a256b171621bcf7","runId":"run.japan-real-household-spending-growth-may-2026.2026-06-27T13-19-13Z.japan-real-household-spending-growth-may-2026-thesis-analyst-fast-2026-06-27t13-19-13z.1fc5a6e21b190f18","scoreId":"score.run.japan-real-household-spending-growth-may-2026.2026-06-27T13-19-13Z.japan-real-household-spending-growth-may-2026-thesis-analyst-fast-2026-06-27t13-19-13z.1fc5a6e21b190f18.resolution_event.japan-real-household-spending-growth-may-2026.statjp-household-spending-real-yoy-two-or-more-person-households-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.3a256b171621bcf7","predictionId":"japan-real-household-spending-growth-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value -0.4 versus point -1.1; signed error 0.7, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.industrial-production-mom-may-2026.2026-06-12T18-32-08Z.a568db54594929de.resolution_event.industrial-production-mom-may-2026.us-frb-industrial-production-total-mom-sa-2026-05.numeric_cdf_crps_v3_ledger_scale.344ac7640710ef8a","runId":"run.industrial-production-mom-may-2026.2026-06-12T18-32-08Z.a568db54594929de","scoreId":"score.run.industrial-production-mom-may-2026.2026-06-12T18-32-08Z.a568db54594929de.resolution_event.industrial-production-mom-may-2026.us-frb-industrial-production-total-mom-sa-2026-05.numeric_cdf_crps_v3_ledger_scale.344ac7640710ef8a","predictionId":"industrial-production-mom-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 0.1 versus point 0.1; signed error 0, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.housing-starts-may-2026.2026-06-12T18-32-08Z.b92c171158419259.resolution_event.housing-starts-may-2026.us-census-housing-starts-total-saar-2026-05.numeric_cdf_crps_v3_ledger_scale.b678680ecfdc4191","runId":"run.housing-starts-may-2026.2026-06-12T18-32-08Z.b92c171158419259","scoreId":"score.run.housing-starts-may-2026.2026-06-12T18-32-08Z.b92c171158419259.resolution_event.housing-starts-may-2026.us-census-housing-starts-total-saar-2026-05.numeric_cdf_crps_v3_ledger_scale.b678680ecfdc4191","predictionId":"housing-starts-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow"],"severity":"medium","explanation":"Observed value 1.177 versus point 1.4; signed error -0.22, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.housing-starts-may-2026.2026-06-15T10-15-00-04-00.housing-starts-control-no-packs.bec076135a40112e.resolution_event.housing-starts-may-2026.us-census-housing-starts-total-saar-2026-05.numeric_cdf_crps_v3_ledger_scale.632e15b83c0d411b","runId":"run.housing-starts-may-2026.2026-06-15T10-15-00-04-00.housing-starts-control-no-packs.bec076135a40112e","scoreId":"score.run.housing-starts-may-2026.2026-06-15T10-15-00-04-00.housing-starts-control-no-packs.bec076135a40112e.resolution_event.housing-starts-may-2026.us-census-housing-starts-total-saar-2026-05.numeric_cdf_crps_v3_ledger_scale.632e15b83c0d411b","predictionId":"housing-starts-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 1.177 versus point 1.35; signed error -0.17, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.housing-starts-may-2026.2026-06-15T10-20-00-04-00.housing-starts-activity-packs.72cf69090dcb4d79.resolution_event.housing-starts-may-2026.us-census-housing-starts-total-saar-2026-05.numeric_cdf_crps_v3_ledger_scale.3494e53475ed4645","runId":"run.housing-starts-may-2026.2026-06-15T10-20-00-04-00.housing-starts-activity-packs.72cf69090dcb4d79","scoreId":"score.run.housing-starts-may-2026.2026-06-15T10-20-00-04-00.housing-starts-activity-packs.72cf69090dcb4d79.resolution_event.housing-starts-may-2026.us-census-housing-starts-total-saar-2026-05.numeric_cdf_crps_v3_ledger_scale.3494e53475ed4645","predictionId":"housing-starts-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","overreacted_to_recent_data"],"severity":"medium","explanation":"Observed value 1.177 versus point 1.45; signed error -0.27, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.uk-cpih-yoy-may-2026.2026-06-12T18-51-12Z.d72e5a2873cad832.resolution_event.uk-cpih-yoy-may-2026.ons-cpih-annual-rate-2026-05.numeric_cdf_crps_v3_ledger_scale.e31979f81596dfb5","runId":"run.uk-cpih-yoy-may-2026.2026-06-12T18-51-12Z.d72e5a2873cad832","scoreId":"score.run.uk-cpih-yoy-may-2026.2026-06-12T18-51-12Z.d72e5a2873cad832.resolution_event.uk-cpih-yoy-may-2026.ons-cpih-annual-rate-2026-05.numeric_cdf_crps_v3_ledger_scale.e31979f81596dfb5","predictionId":"uk-cpih-yoy-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 3 versus point 3; signed error 0, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.fomc-rate-upper-june-2026.2026-06-12T18-32-08Z.3429ac31a9eb0034.resolution_event.fomc-rate-upper-june-2026.us-fed-fomc-target-range-upper-2026-06.numeric_cdf_crps_v3_ledger_scale.66a2cc241259397c","runId":"run.fomc-rate-upper-june-2026.2026-06-12T18-32-08Z.3429ac31a9eb0034","scoreId":"score.run.fomc-rate-upper-june-2026.2026-06-12T18-32-08Z.3429ac31a9eb0034.resolution_event.fomc-rate-upper-june-2026.us-fed-fomc-target-range-upper-2026-06.numeric_cdf_crps_v3_ledger_scale.66a2cc241259397c","predictionId":"fomc-rate-upper-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 3.75 versus point 3.75; signed error 0, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.boe-bank-rate-june-2026.2026-06-12T18-51-12Z.b33aff3526b668a2.resolution_event.boe-bank-rate-june-2026.boe-bank-rate-2026-06-18.numeric_cdf_crps_v3_ledger_scale.a1c0ffb946407dac","runId":"run.boe-bank-rate-june-2026.2026-06-12T18-51-12Z.b33aff3526b668a2","scoreId":"score.run.boe-bank-rate-june-2026.2026-06-12T18-51-12Z.b33aff3526b668a2.resolution_event.boe-bank-rate-june-2026.boe-bank-rate-2026-06-18.numeric_cdf_crps_v3_ledger_scale.a1c0ffb946407dac","predictionId":"boe-bank-rate-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 3.75 versus point 3.75; signed error 0, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.boe-bank-rate-june-2026.2026-06-16T12-28-37Z.boe-bank-rate-june-2026-thesis-analyst-fast-2026-06-16t12-28-37z.7ec2dedec56040d2.resolution_event.boe-bank-rate-june-2026.boe-bank-rate-2026-06-18.numeric_cdf_crps_v3_ledger_scale.ad256bb3aa77e284","runId":"run.boe-bank-rate-june-2026.2026-06-16T12-28-37Z.boe-bank-rate-june-2026-thesis-analyst-fast-2026-06-16t12-28-37z.7ec2dedec56040d2","scoreId":"score.run.boe-bank-rate-june-2026.2026-06-16T12-28-37Z.boe-bank-rate-june-2026-thesis-analyst-fast-2026-06-16t12-28-37z.7ec2dedec56040d2.resolution_event.boe-bank-rate-june-2026.boe-bank-rate-2026-06-18.numeric_cdf_crps_v3_ledger_scale.ad256bb3aa77e284","predictionId":"boe-bank-rate-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 3.75 versus point 3.75; signed error 0, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.initial-claims-week-2026-06-13.2026-06-12T18-32-08Z.a820c5baf6c88911.resolution_event.initial-claims-week-2026-06-13.us-dol-initial-claims-sa-week-2026-06-13.numeric_cdf_crps_v3_ledger_scale.473ca76de9bed513","runId":"run.initial-claims-week-2026-06-13.2026-06-12T18-32-08Z.a820c5baf6c88911","scoreId":"score.run.initial-claims-week-2026-06-13.2026-06-12T18-32-08Z.a820c5baf6c88911.resolution_event.initial-claims-week-2026-06-13.us-dol-initial-claims-sa-week-2026-06-13.numeric_cdf_crps_v3_ledger_scale.473ca76de9bed513","predictionId":"initial-claims-week-2026-06-13","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 226 versus point 222; signed error 4, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.initial-claims-week-2026-06-13.2026-06-15T10-25-00-04-00.claims-0613-control-no-packs.0a0d1b821f8f61e0.resolution_event.initial-claims-week-2026-06-13.us-dol-initial-claims-sa-week-2026-06-13.numeric_cdf_crps_v3_ledger_scale.b151970e035a2065","runId":"run.initial-claims-week-2026-06-13.2026-06-15T10-25-00-04-00.claims-0613-control-no-packs.0a0d1b821f8f61e0","scoreId":"score.run.initial-claims-week-2026-06-13.2026-06-15T10-25-00-04-00.claims-0613-control-no-packs.0a0d1b821f8f61e0.resolution_event.initial-claims-week-2026-06-13.us-dol-initial-claims-sa-week-2026-06-13.numeric_cdf_crps_v3_ledger_scale.b151970e035a2065","predictionId":"initial-claims-week-2026-06-13","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 226 versus point 219; signed error 7, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.initial-claims-week-2026-06-13.2026-06-15T10-30-00-04-00.claims-0613-labor-packs.a15e2e6770fc1f46.resolution_event.initial-claims-week-2026-06-13.us-dol-initial-claims-sa-week-2026-06-13.numeric_cdf_crps_v3_ledger_scale.3b37c0b3904af3f6","runId":"run.initial-claims-week-2026-06-13.2026-06-15T10-30-00-04-00.claims-0613-labor-packs.a15e2e6770fc1f46","scoreId":"score.run.initial-claims-week-2026-06-13.2026-06-15T10-30-00-04-00.claims-0613-labor-packs.a15e2e6770fc1f46.resolution_event.initial-claims-week-2026-06-13.us-dol-initial-claims-sa-week-2026-06-13.numeric_cdf_crps_v3_ledger_scale.3b37c0b3904af3f6","predictionId":"initial-claims-week-2026-06-13","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 226 versus point 225; signed error 1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.initial-claims-week-2026-06-13.2026-06-16T12-33-22Z.initial-claims-week-2026-06-13-thesis-analyst-fast-2026-06-16t12-33-22z.0db04f1eb4a0e87b.resolution_event.initial-claims-week-2026-06-13.us-dol-initial-claims-sa-week-2026-06-13.numeric_cdf_crps_v3_ledger_scale.4b8b699282894ca5","runId":"run.initial-claims-week-2026-06-13.2026-06-16T12-33-22Z.initial-claims-week-2026-06-13-thesis-analyst-fast-2026-06-16t12-33-22z.0db04f1eb4a0e87b","scoreId":"score.run.initial-claims-week-2026-06-13.2026-06-16T12-33-22Z.initial-claims-week-2026-06-13-thesis-analyst-fast-2026-06-16t12-33-22z.0db04f1eb4a0e87b.resolution_event.initial-claims-week-2026-06-13.us-dol-initial-claims-sa-week-2026-06-13.numeric_cdf_crps_v3_ledger_scale.4b8b699282894ca5","predictionId":"initial-claims-week-2026-06-13","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 226 versus point 225; signed error 1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.japan-core-cpi-yoy-may-2026.2026-06-12T18-51-12Z.595f976a4c022ffe.resolution_event.japan-core-cpi-yoy-may-2026.estat-jp-cpi-core-exfreshfood-yoy-2026-05.numeric_cdf_crps_v3_ledger_scale.bc796d7e7ec46607","runId":"run.japan-core-cpi-yoy-may-2026.2026-06-12T18-51-12Z.595f976a4c022ffe","scoreId":"score.run.japan-core-cpi-yoy-may-2026.2026-06-12T18-51-12Z.595f976a4c022ffe.resolution_event.japan-core-cpi-yoy-may-2026.estat-jp-cpi-core-exfreshfood-yoy-2026-05.numeric_cdf_crps_v3_ledger_scale.bc796d7e7ec46607","predictionId":"japan-core-cpi-yoy-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 1.4 versus point 1.4; signed error 0, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.japan-core-cpi-yoy-may-2026.2026-06-17T01-52-06Z.japan-core-cpi-yoy-may-2026-thesis-analyst-fast-2026-06-17t01-52-06z.ed6fe838e1b99ea4.resolution_event.japan-core-cpi-yoy-may-2026.estat-jp-cpi-core-exfreshfood-yoy-2026-05.numeric_cdf_crps_v3_ledger_scale.18e7e2b8e9110db2","runId":"run.japan-core-cpi-yoy-may-2026.2026-06-17T01-52-06Z.japan-core-cpi-yoy-may-2026-thesis-analyst-fast-2026-06-17t01-52-06z.ed6fe838e1b99ea4","scoreId":"score.run.japan-core-cpi-yoy-may-2026.2026-06-17T01-52-06Z.japan-core-cpi-yoy-may-2026-thesis-analyst-fast-2026-06-17t01-52-06z.ed6fe838e1b99ea4.resolution_event.japan-core-cpi-yoy-may-2026.estat-jp-cpi-core-exfreshfood-yoy-2026-05.numeric_cdf_crps_v3_ledger_scale.18e7e2b8e9110db2","predictionId":"japan-core-cpi-yoy-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","overreacted_to_recent_data"],"severity":"medium","explanation":"Observed value 1.4 versus point 3; signed error -1.6, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.canada-cpi-yoy-may-2026.2026-06-12T18-51-12Z.4cda521fe1402678.resolution_event.canada-cpi-yoy-may-2026.statcan-cpi-allitems-yoy-2026-05.numeric_cdf_crps_v3_ledger_scale.4bb0f9a9759b767e","runId":"run.canada-cpi-yoy-may-2026.2026-06-12T18-51-12Z.4cda521fe1402678","scoreId":"score.run.canada-cpi-yoy-may-2026.2026-06-12T18-51-12Z.4cda521fe1402678.resolution_event.canada-cpi-yoy-may-2026.statcan-cpi-allitems-yoy-2026-05.numeric_cdf_crps_v3_ledger_scale.4bb0f9a9759b767e","predictionId":"canada-cpi-yoy-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 3.2 versus point 2.8; signed error 0.4, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.canada-cpi-yoy-may-2026.2026-06-20T09-00-00-04-00.canada-cpi-yoy-may-2026-brier-shadow-no-packs.f96d6a8371381e07.resolution_event.canada-cpi-yoy-may-2026.statcan-cpi-allitems-yoy-2026-05.numeric_cdf_crps_v3_ledger_scale.52c4d352b1eb0f50","runId":"run.canada-cpi-yoy-may-2026.2026-06-20T09-00-00-04-00.canada-cpi-yoy-may-2026-brier-shadow-no-packs.f96d6a8371381e07","scoreId":"score.run.canada-cpi-yoy-may-2026.2026-06-20T09-00-00-04-00.canada-cpi-yoy-may-2026-brier-shadow-no-packs.f96d6a8371381e07.resolution_event.canada-cpi-yoy-may-2026.statcan-cpi-allitems-yoy-2026-05.numeric_cdf_crps_v3_ledger_scale.52c4d352b1eb0f50","predictionId":"canada-cpi-yoy-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 3.2 versus point 2.6; signed error 0.6, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.canada-cpi-yoy-may-2026.2026-06-20T09-00-00-04-00.canada-cpi-yoy-may-2026-brier-shadow-with-packs.dbd096f26b206a77.resolution_event.canada-cpi-yoy-may-2026.statcan-cpi-allitems-yoy-2026-05.numeric_cdf_crps_v3_ledger_scale.8125bc1ac297469e","runId":"run.canada-cpi-yoy-may-2026.2026-06-20T09-00-00-04-00.canada-cpi-yoy-may-2026-brier-shadow-with-packs.dbd096f26b206a77","scoreId":"score.run.canada-cpi-yoy-may-2026.2026-06-20T09-00-00-04-00.canada-cpi-yoy-may-2026-brier-shadow-with-packs.dbd096f26b206a77.resolution_event.canada-cpi-yoy-may-2026.statcan-cpi-allitems-yoy-2026-05.numeric_cdf_crps_v3_ledger_scale.8125bc1ac297469e","predictionId":"canada-cpi-yoy-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 3.2 versus point 2.7; signed error 0.5, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.canada-cpi-yoy-may-2026.2026-06-17T01-51-10Z.canada-cpi-yoy-may-2026-thesis-analyst-fast-2026-06-17t01-51-10z.dbd096f26b206a77.resolution_event.canada-cpi-yoy-may-2026.statcan-cpi-allitems-yoy-2026-05.numeric_cdf_crps_v3_ledger_scale.0e8b95e31a844a9a","runId":"run.canada-cpi-yoy-may-2026.2026-06-17T01-51-10Z.canada-cpi-yoy-may-2026-thesis-analyst-fast-2026-06-17t01-51-10z.dbd096f26b206a77","scoreId":"score.run.canada-cpi-yoy-may-2026.2026-06-17T01-51-10Z.canada-cpi-yoy-may-2026-thesis-analyst-fast-2026-06-17t01-51-10z.dbd096f26b206a77.resolution_event.canada-cpi-yoy-may-2026.statcan-cpi-allitems-yoy-2026-05.numeric_cdf_crps_v3_ledger_scale.0e8b95e31a844a9a","predictionId":"canada-cpi-yoy-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 3.2 versus point 2.7; signed error 0.5, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.australia-cpi-indicator-may-2026.2026-06-12T18-51-12Z.a4522739476aeb70.resolution_event.australia-cpi-indicator-may-2026.abs-cpi-indicator-allgroups-yoy-2026-05.numeric_cdf_crps_v3_ledger_scale.e1dfe04ad08574a8","runId":"run.australia-cpi-indicator-may-2026.2026-06-12T18-51-12Z.a4522739476aeb70","scoreId":"score.run.australia-cpi-indicator-may-2026.2026-06-12T18-51-12Z.a4522739476aeb70.resolution_event.australia-cpi-indicator-may-2026.abs-cpi-indicator-allgroups-yoy-2026-05.numeric_cdf_crps_v3_ledger_scale.e1dfe04ad08574a8","predictionId":"australia-cpi-indicator-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 4 versus point 4.1; signed error -0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.australia-cpi-indicator-may-2026.2026-06-20T09-06-00-04-00.australia-cpi-indicator-may-2026-brier-shadow-no-packs.a4522739476aeb70.resolution_event.australia-cpi-indicator-may-2026.abs-cpi-indicator-allgroups-yoy-2026-05.numeric_cdf_crps_v3_ledger_scale.68c4055086801058","runId":"run.australia-cpi-indicator-may-2026.2026-06-20T09-06-00-04-00.australia-cpi-indicator-may-2026-brier-shadow-no-packs.a4522739476aeb70","scoreId":"score.run.australia-cpi-indicator-may-2026.2026-06-20T09-06-00-04-00.australia-cpi-indicator-may-2026-brier-shadow-no-packs.a4522739476aeb70.resolution_event.australia-cpi-indicator-may-2026.abs-cpi-indicator-allgroups-yoy-2026-05.numeric_cdf_crps_v3_ledger_scale.68c4055086801058","predictionId":"australia-cpi-indicator-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 4 versus point 4.1; signed error -0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.australia-cpi-indicator-may-2026.2026-06-20T09-06-00-04-00.australia-cpi-indicator-may-2026-brier-shadow-with-packs.8bcb9ac5bfda3881.resolution_event.australia-cpi-indicator-may-2026.abs-cpi-indicator-allgroups-yoy-2026-05.numeric_cdf_crps_v3_ledger_scale.2d4dadd74faa5840","runId":"run.australia-cpi-indicator-may-2026.2026-06-20T09-06-00-04-00.australia-cpi-indicator-may-2026-brier-shadow-with-packs.8bcb9ac5bfda3881","scoreId":"score.run.australia-cpi-indicator-may-2026.2026-06-20T09-06-00-04-00.australia-cpi-indicator-may-2026-brier-shadow-with-packs.8bcb9ac5bfda3881.resolution_event.australia-cpi-indicator-may-2026.abs-cpi-indicator-allgroups-yoy-2026-05.numeric_cdf_crps_v3_ledger_scale.2d4dadd74faa5840","predictionId":"australia-cpi-indicator-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 4 versus point 4.5; signed error -0.5, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.initial-claims-week-2026-06-20.2026-06-12T18-32-08Z.f6eaa3fc68d6ba3b.resolution_event.initial-claims-week-2026-06-20.us-dol-initial-claims-sa-week-2026-06-20.numeric_cdf_crps_v3_ledger_scale.980f96c6bc2b8516","runId":"run.initial-claims-week-2026-06-20.2026-06-12T18-32-08Z.f6eaa3fc68d6ba3b","scoreId":"score.run.initial-claims-week-2026-06-20.2026-06-12T18-32-08Z.f6eaa3fc68d6ba3b.resolution_event.initial-claims-week-2026-06-20.us-dol-initial-claims-sa-week-2026-06-20.numeric_cdf_crps_v3_ledger_scale.980f96c6bc2b8516","predictionId":"initial-claims-week-2026-06-20","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 215 versus point 220; signed error -5, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.initial-claims-week-2026-06-20.2026-06-20T09-14-00-04-00.initial-claims-week-2026-06-20-brier-shadow-no-packs.03f532c0353cde1f.resolution_event.initial-claims-week-2026-06-20.us-dol-initial-claims-sa-week-2026-06-20.numeric_cdf_crps_v3_ledger_scale.1aad20c8795c706a","runId":"run.initial-claims-week-2026-06-20.2026-06-20T09-14-00-04-00.initial-claims-week-2026-06-20-brier-shadow-no-packs.03f532c0353cde1f","scoreId":"score.run.initial-claims-week-2026-06-20.2026-06-20T09-14-00-04-00.initial-claims-week-2026-06-20-brier-shadow-no-packs.03f532c0353cde1f.resolution_event.initial-claims-week-2026-06-20.us-dol-initial-claims-sa-week-2026-06-20.numeric_cdf_crps_v3_ledger_scale.1aad20c8795c706a","predictionId":"initial-claims-week-2026-06-20","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 215 versus point 221; signed error -6, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.initial-claims-week-2026-06-20.2026-06-20T09-14-00-04-00.initial-claims-week-2026-06-20-brier-shadow-with-packs.252cd3fe6ebf8461.resolution_event.initial-claims-week-2026-06-20.us-dol-initial-claims-sa-week-2026-06-20.numeric_cdf_crps_v3_ledger_scale.8d4d59209a760359","runId":"run.initial-claims-week-2026-06-20.2026-06-20T09-14-00-04-00.initial-claims-week-2026-06-20-brier-shadow-with-packs.252cd3fe6ebf8461","scoreId":"score.run.initial-claims-week-2026-06-20.2026-06-20T09-14-00-04-00.initial-claims-week-2026-06-20-brier-shadow-with-packs.252cd3fe6ebf8461.resolution_event.initial-claims-week-2026-06-20.us-dol-initial-claims-sa-week-2026-06-20.numeric_cdf_crps_v3_ledger_scale.8d4d59209a760359","predictionId":"initial-claims-week-2026-06-20","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 215 versus point 226; signed error -11, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.initial-claims-week-2026-06-20.2026-06-17T02-23-52Z.initial-claims-week-2026-06-20-thesis-analyst-fast-2026-06-17t02-23-52z.252cd3fe6ebf8461.resolution_event.initial-claims-week-2026-06-20.us-dol-initial-claims-sa-week-2026-06-20.numeric_cdf_crps_v3_ledger_scale.74ef2bbe6f94597e","runId":"run.initial-claims-week-2026-06-20.2026-06-17T02-23-52Z.initial-claims-week-2026-06-20-thesis-analyst-fast-2026-06-17t02-23-52z.252cd3fe6ebf8461","scoreId":"score.run.initial-claims-week-2026-06-20.2026-06-17T02-23-52Z.initial-claims-week-2026-06-20-thesis-analyst-fast-2026-06-17t02-23-52z.252cd3fe6ebf8461.resolution_event.initial-claims-week-2026-06-20.us-dol-initial-claims-sa-week-2026-06-20.numeric_cdf_crps_v3_ledger_scale.74ef2bbe6f94597e","predictionId":"initial-claims-week-2026-06-20","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 215 versus point 226; signed error -11, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.initial-claims-week-2026-06-20.2026-06-21T15-11-54Z.initial-claims-week-2026-06-20-thesis-analyst-fast-2026-06-21t15-11-54z.8618e4ce8e238937.resolution_event.initial-claims-week-2026-06-20.us-dol-initial-claims-sa-week-2026-06-20.numeric_cdf_crps_v3_ledger_scale.79945ecdf58b9086","runId":"run.initial-claims-week-2026-06-20.2026-06-21T15-11-54Z.initial-claims-week-2026-06-20-thesis-analyst-fast-2026-06-21t15-11-54z.8618e4ce8e238937","scoreId":"score.run.initial-claims-week-2026-06-20.2026-06-21T15-11-54Z.initial-claims-week-2026-06-20-thesis-analyst-fast-2026-06-21t15-11-54z.8618e4ce8e238937.resolution_event.initial-claims-week-2026-06-20.us-dol-initial-claims-sa-week-2026-06-20.numeric_cdf_crps_v3_ledger_scale.79945ecdf58b9086","predictionId":"initial-claims-week-2026-06-20","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 215 versus point 225; signed error -10, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-core-pce-mom-may-2026.2026-06-12T18-32-08Z.9d9a4b7dab257493.resolution_event.us-core-pce-mom-may-2026.us-bea-core-pce-mom-sa-2026-05.numeric_cdf_crps_v3_ledger_scale.710687255f09e180","runId":"run.us-core-pce-mom-may-2026.2026-06-12T18-32-08Z.9d9a4b7dab257493","scoreId":"score.run.us-core-pce-mom-may-2026.2026-06-12T18-32-08Z.9d9a4b7dab257493.resolution_event.us-core-pce-mom-may-2026.us-bea-core-pce-mom-sa-2026-05.numeric_cdf_crps_v3_ledger_scale.710687255f09e180","predictionId":"us-core-pce-mom-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 0.3 versus point 0.25; signed error 0.05, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-core-pce-mom-may-2026.2026-06-14T15-45-00-04-00.core-pce-control-no-packs.d835e32b68b5c093.resolution_event.us-core-pce-mom-may-2026.us-bea-core-pce-mom-sa-2026-05.numeric_cdf_crps_v3_ledger_scale.742727131b3a6810","runId":"run.us-core-pce-mom-may-2026.2026-06-14T15-45-00-04-00.core-pce-control-no-packs.d835e32b68b5c093","scoreId":"score.run.us-core-pce-mom-may-2026.2026-06-14T15-45-00-04-00.core-pce-control-no-packs.d835e32b68b5c093.resolution_event.us-core-pce-mom-may-2026.us-bea-core-pce-mom-sa-2026-05.numeric_cdf_crps_v3_ledger_scale.742727131b3a6810","predictionId":"us-core-pce-mom-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 0.3 versus point 0.23; signed error 0.07, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-core-pce-mom-may-2026.2026-06-15T09-45-00-04-00.core-pce-bridge-packs.39c5495b584cced0.resolution_event.us-core-pce-mom-may-2026.us-bea-core-pce-mom-sa-2026-05.numeric_cdf_crps_v3_ledger_scale.97cd9366ccc491bd","runId":"run.us-core-pce-mom-may-2026.2026-06-15T09-45-00-04-00.core-pce-bridge-packs.39c5495b584cced0","scoreId":"score.run.us-core-pce-mom-may-2026.2026-06-15T09-45-00-04-00.core-pce-bridge-packs.39c5495b584cced0.resolution_event.us-core-pce-mom-may-2026.us-bea-core-pce-mom-sa-2026-05.numeric_cdf_crps_v3_ledger_scale.97cd9366ccc491bd","predictionId":"us-core-pce-mom-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 0.3 versus point 0.27; signed error 0.03, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-core-pce-mom-may-2026.2026-06-17T02-16-13Z.us-core-pce-mom-may-2026-thesis-analyst-fast-2026-06-17t02-16-13z.39c5495b584cced0.resolution_event.us-core-pce-mom-may-2026.us-bea-core-pce-mom-sa-2026-05.numeric_cdf_crps_v3_ledger_scale.ca0057a8bafdfcd7","runId":"run.us-core-pce-mom-may-2026.2026-06-17T02-16-13Z.us-core-pce-mom-may-2026-thesis-analyst-fast-2026-06-17t02-16-13z.39c5495b584cced0","scoreId":"score.run.us-core-pce-mom-may-2026.2026-06-17T02-16-13Z.us-core-pce-mom-may-2026-thesis-analyst-fast-2026-06-17t02-16-13z.39c5495b584cced0.resolution_event.us-core-pce-mom-may-2026.us-bea-core-pce-mom-sa-2026-05.numeric_cdf_crps_v3_ledger_scale.ca0057a8bafdfcd7","predictionId":"us-core-pce-mom-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 0.3 versus point 0.27; signed error 0.03, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.jolts-openings-may-2026.2026-06-12T18-59-50Z.c528e1818af86dfd.resolution_event.jolts-openings-may-2026.bls-jolts-job-openings-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.a6321d86a7a7c05a","runId":"run.jolts-openings-may-2026.2026-06-12T18-59-50Z.c528e1818af86dfd","scoreId":"score.run.jolts-openings-may-2026.2026-06-12T18-59-50Z.c528e1818af86dfd.resolution_event.jolts-openings-may-2026.bls-jolts-job-openings-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.a6321d86a7a7c05a","predictionId":"jolts-openings-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 7.594 versus point 7.35; signed error 0.24, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.jolts-openings-may-2026.2026-06-15T10-35-00-04-00.jolts-control-no-packs.4353b8d25a1883fd.resolution_event.jolts-openings-may-2026.bls-jolts-job-openings-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.0640310388e25697","runId":"run.jolts-openings-may-2026.2026-06-15T10-35-00-04-00.jolts-control-no-packs.4353b8d25a1883fd","scoreId":"score.run.jolts-openings-may-2026.2026-06-15T10-35-00-04-00.jolts-control-no-packs.4353b8d25a1883fd.resolution_event.jolts-openings-may-2026.bls-jolts-job-openings-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.0640310388e25697","predictionId":"jolts-openings-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 7.594 versus point 7.15; signed error 0.44, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.jolts-openings-may-2026.2026-06-15T10-40-00-04-00.jolts-labor-packs.f79134ec4ef156cf.resolution_event.jolts-openings-may-2026.bls-jolts-job-openings-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.ad2e7bf10b1a6598","runId":"run.jolts-openings-may-2026.2026-06-15T10-40-00-04-00.jolts-labor-packs.f79134ec4ef156cf","scoreId":"score.run.jolts-openings-may-2026.2026-06-15T10-40-00-04-00.jolts-labor-packs.f79134ec4ef156cf.resolution_event.jolts-openings-may-2026.bls-jolts-job-openings-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.ad2e7bf10b1a6598","predictionId":"jolts-openings-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 7.594 versus point 7.35; signed error 0.24, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.jolts-openings-may-2026.2026-06-17T02-17-25Z.jolts-openings-may-2026-thesis-analyst-fast-2026-06-17t02-17-25z.e9b7a1465dc3b96a.resolution_event.jolts-openings-may-2026.bls-jolts-job-openings-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.2cd4a0599616e851","runId":"run.jolts-openings-may-2026.2026-06-17T02-17-25Z.jolts-openings-may-2026-thesis-analyst-fast-2026-06-17t02-17-25z.e9b7a1465dc3b96a","scoreId":"score.run.jolts-openings-may-2026.2026-06-17T02-17-25Z.jolts-openings-may-2026-thesis-analyst-fast-2026-06-17t02-17-25z.e9b7a1465dc3b96a.resolution_event.jolts-openings-may-2026.bls-jolts-job-openings-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.2cd4a0599616e851","predictionId":"jolts-openings-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 7.594 versus point 7.45; signed error 0.14, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.euro-flash-hicp-june-2026.2026-06-12T18-51-12Z.25797c6fdd7dacee.resolution_event.euro-flash-hicp-june-2026.eurostat-ea-hicp-flash-yoy-2026-06.numeric_cdf_crps_v3_ledger_scale.3e5d007cf926817a","runId":"run.euro-flash-hicp-june-2026.2026-06-12T18-51-12Z.25797c6fdd7dacee","scoreId":"score.run.euro-flash-hicp-june-2026.2026-06-12T18-51-12Z.25797c6fdd7dacee.resolution_event.euro-flash-hicp-june-2026.eurostat-ea-hicp-flash-yoy-2026-06.numeric_cdf_crps_v3_ledger_scale.3e5d007cf926817a","predictionId":"euro-flash-hicp-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 2.8 versus point 3.2; signed error -0.4, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.euro-flash-hicp-june-2026.2026-06-17T02-10-25Z.euro-flash-hicp-june-2026-thesis-analyst-fast-2026-06-17t02-10-25z.3a1bc207b8eb3aa0.resolution_event.euro-flash-hicp-june-2026.eurostat-ea-hicp-flash-yoy-2026-06.numeric_cdf_crps_v3_ledger_scale.5f865188706db74b","runId":"run.euro-flash-hicp-june-2026.2026-06-17T02-10-25Z.euro-flash-hicp-june-2026-thesis-analyst-fast-2026-06-17t02-10-25z.3a1bc207b8eb3aa0","scoreId":"score.run.euro-flash-hicp-june-2026.2026-06-17T02-10-25Z.euro-flash-hicp-june-2026-thesis-analyst-fast-2026-06-17t02-10-25z.3a1bc207b8eb3aa0.resolution_event.euro-flash-hicp-june-2026.eurostat-ea-hicp-flash-yoy-2026-06.numeric_cdf_crps_v3_ledger_scale.5f865188706db74b","predictionId":"euro-flash-hicp-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 2.8 versus point 3.3; signed error -0.5, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.nonfarm-payrolls-june-2026.2026-06-12T18-59-50Z.e62ce2faf99fc097.resolution_event.nonfarm-payrolls-june-2026.bls-ces-total-nonfarm-payroll-change-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.ac0f1e31b2b04dd2","runId":"run.nonfarm-payrolls-june-2026.2026-06-12T18-59-50Z.e62ce2faf99fc097","scoreId":"score.run.nonfarm-payrolls-june-2026.2026-06-12T18-59-50Z.e62ce2faf99fc097.resolution_event.nonfarm-payrolls-june-2026.bls-ces-total-nonfarm-payroll-change-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.ac0f1e31b2b04dd2","predictionId":"nonfarm-payrolls-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 57 versus point 140; signed error -83, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.nonfarm-payrolls-june-2026.2026-06-14T15-20-00-04-00.payrolls-control-no-packs.0a660f20bfc9031b.resolution_event.nonfarm-payrolls-june-2026.bls-ces-total-nonfarm-payroll-change-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.615a279ca28ccb35","runId":"run.nonfarm-payrolls-june-2026.2026-06-14T15-20-00-04-00.payrolls-control-no-packs.0a660f20bfc9031b","scoreId":"score.run.nonfarm-payrolls-june-2026.2026-06-14T15-20-00-04-00.payrolls-control-no-packs.0a660f20bfc9031b.resolution_event.nonfarm-payrolls-june-2026.bls-ces-total-nonfarm-payroll-change-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.615a279ca28ccb35","predictionId":"nonfarm-payrolls-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 57 versus point 125; signed error -68, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.nonfarm-payrolls-june-2026.2026-06-15T09-10-00-04-00.payrolls-labor-packs.125a58572070330b.resolution_event.nonfarm-payrolls-june-2026.bls-ces-total-nonfarm-payroll-change-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.231c5c6505754b89","runId":"run.nonfarm-payrolls-june-2026.2026-06-15T09-10-00-04-00.payrolls-labor-packs.125a58572070330b","scoreId":"score.run.nonfarm-payrolls-june-2026.2026-06-15T09-10-00-04-00.payrolls-labor-packs.125a58572070330b.resolution_event.nonfarm-payrolls-june-2026.bls-ces-total-nonfarm-payroll-change-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.231c5c6505754b89","predictionId":"nonfarm-payrolls-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 57 versus point 150; signed error -93, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.nonfarm-payrolls-june-2026.2026-06-17T02-18-28Z.nonfarm-payrolls-june-2026-thesis-analyst-fast-2026-06-17t02-18-28z.407a1c3e2a4cfe0c.resolution_event.nonfarm-payrolls-june-2026.bls-ces-total-nonfarm-payroll-change-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.1b059e5f124c7719","runId":"run.nonfarm-payrolls-june-2026.2026-06-17T02-18-28Z.nonfarm-payrolls-june-2026-thesis-analyst-fast-2026-06-17t02-18-28z.407a1c3e2a4cfe0c","scoreId":"score.run.nonfarm-payrolls-june-2026.2026-06-17T02-18-28Z.nonfarm-payrolls-june-2026-thesis-analyst-fast-2026-06-17t02-18-28z.407a1c3e2a4cfe0c.resolution_event.nonfarm-payrolls-june-2026.bls-ces-total-nonfarm-payroll-change-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.1b059e5f124c7719","predictionId":"nonfarm-payrolls-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 57 versus point 150; signed error -93, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.nonfarm-payrolls-june-2026.2026-06-21T15-06-37Z.nonfarm-payrolls-june-2026-thesis-analyst-fast-2026-06-21t15-06-37z.e62ce2faf99fc097.resolution_event.nonfarm-payrolls-june-2026.bls-ces-total-nonfarm-payroll-change-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.2b8f795ba928b2a0","runId":"run.nonfarm-payrolls-june-2026.2026-06-21T15-06-37Z.nonfarm-payrolls-june-2026-thesis-analyst-fast-2026-06-21t15-06-37z.e62ce2faf99fc097","scoreId":"score.run.nonfarm-payrolls-june-2026.2026-06-21T15-06-37Z.nonfarm-payrolls-june-2026-thesis-analyst-fast-2026-06-21t15-06-37z.e62ce2faf99fc097.resolution_event.nonfarm-payrolls-june-2026.bls-ces-total-nonfarm-payroll-change-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.2b8f795ba928b2a0","predictionId":"nonfarm-payrolls-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 57 versus point 140; signed error -83, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.unemployment-rate-june-2026.2026-06-12T18-59-50Z.bc2560c9f3dbbe73.resolution_event.unemployment-rate-june-2026.bls-cps-unemployment-rate-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.725e4972042c6b47","runId":"run.unemployment-rate-june-2026.2026-06-12T18-59-50Z.bc2560c9f3dbbe73","scoreId":"score.run.unemployment-rate-june-2026.2026-06-12T18-59-50Z.bc2560c9f3dbbe73.resolution_event.unemployment-rate-june-2026.bls-cps-unemployment-rate-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.725e4972042c6b47","predictionId":"unemployment-rate-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 4.2 versus point 4.3; signed error -0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.unemployment-rate-june-2026.2026-06-14T15-25-00-04-00.unemployment-control-no-packs.c638ecef0e19c24b.resolution_event.unemployment-rate-june-2026.bls-cps-unemployment-rate-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.3b149fd0b3700b77","runId":"run.unemployment-rate-june-2026.2026-06-14T15-25-00-04-00.unemployment-control-no-packs.c638ecef0e19c24b","scoreId":"score.run.unemployment-rate-june-2026.2026-06-14T15-25-00-04-00.unemployment-control-no-packs.c638ecef0e19c24b.resolution_event.unemployment-rate-june-2026.bls-cps-unemployment-rate-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.3b149fd0b3700b77","predictionId":"unemployment-rate-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 4.2 versus point 4.3; signed error -0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.unemployment-rate-june-2026.2026-06-15T09-15-00-04-00.unemployment-labor-packs.bc2560c9f3dbbe73.resolution_event.unemployment-rate-june-2026.bls-cps-unemployment-rate-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.d45163a15e64e0a7","runId":"run.unemployment-rate-june-2026.2026-06-15T09-15-00-04-00.unemployment-labor-packs.bc2560c9f3dbbe73","scoreId":"score.run.unemployment-rate-june-2026.2026-06-15T09-15-00-04-00.unemployment-labor-packs.bc2560c9f3dbbe73.resolution_event.unemployment-rate-june-2026.bls-cps-unemployment-rate-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.d45163a15e64e0a7","predictionId":"unemployment-rate-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 4.2 versus point 4.3; signed error -0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.unemployment-rate-june-2026.2026-06-17T02-19-19Z.unemployment-rate-june-2026-thesis-analyst-fast-2026-06-17t02-19-19z.57400c4ac1094b0b.resolution_event.unemployment-rate-june-2026.bls-cps-unemployment-rate-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.2e48e0ca2a0d156a","runId":"run.unemployment-rate-june-2026.2026-06-17T02-19-19Z.unemployment-rate-june-2026-thesis-analyst-fast-2026-06-17t02-19-19z.57400c4ac1094b0b","scoreId":"score.run.unemployment-rate-june-2026.2026-06-17T02-19-19Z.unemployment-rate-june-2026-thesis-analyst-fast-2026-06-17t02-19-19z.57400c4ac1094b0b.resolution_event.unemployment-rate-june-2026.bls-cps-unemployment-rate-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.2e48e0ca2a0d156a","predictionId":"unemployment-rate-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 4.2 versus point 4.3; signed error -0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.unemployment-rate-june-2026.2026-06-21T15-07-35Z.unemployment-rate-june-2026-thesis-analyst-fast-2026-06-21t15-07-35z.57400c4ac1094b0b.resolution_event.unemployment-rate-june-2026.bls-cps-unemployment-rate-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.702c280aff657ae9","runId":"run.unemployment-rate-june-2026.2026-06-21T15-07-35Z.unemployment-rate-june-2026-thesis-analyst-fast-2026-06-21t15-07-35z.57400c4ac1094b0b","scoreId":"score.run.unemployment-rate-june-2026.2026-06-21T15-07-35Z.unemployment-rate-june-2026-thesis-analyst-fast-2026-06-21t15-07-35z.57400c4ac1094b0b.resolution_event.unemployment-rate-june-2026.bls-cps-unemployment-rate-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.702c280aff657ae9","predictionId":"unemployment-rate-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 4.2 versus point 4.3; signed error -0.1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-cpi-u-mom-june-2026.2026-06-12T18-59-50Z.89d3681a7f28e8df.resolution_event.us-cpi-u-mom-june-2026.bls-cpi-u-headline-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.69a01597231145c6","runId":"run.us-cpi-u-mom-june-2026.2026-06-12T18-59-50Z.89d3681a7f28e8df","scoreId":"score.run.us-cpi-u-mom-june-2026.2026-06-12T18-59-50Z.89d3681a7f28e8df.resolution_event.us-cpi-u-mom-june-2026.bls-cpi-u-headline-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.69a01597231145c6","predictionId":"us-cpi-u-mom-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","overreacted_to_recent_data"],"severity":"medium","explanation":"Observed value -0.4 versus point 0.4; signed error -0.8, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-cpi-u-mom-june-2026.2026-06-14T15-35-00-04-00.headline-cpi-control-no-packs.f3c31a3eb5b6c545.resolution_event.us-cpi-u-mom-june-2026.bls-cpi-u-headline-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.c500fc2ad8b68a37","runId":"run.us-cpi-u-mom-june-2026.2026-06-14T15-35-00-04-00.headline-cpi-control-no-packs.f3c31a3eb5b6c545","scoreId":"score.run.us-cpi-u-mom-june-2026.2026-06-14T15-35-00-04-00.headline-cpi-control-no-packs.f3c31a3eb5b6c545.resolution_event.us-cpi-u-mom-june-2026.bls-cpi-u-headline-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.c500fc2ad8b68a37","predictionId":"us-cpi-u-mom-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","overreacted_to_recent_data"],"severity":"medium","explanation":"Observed value -0.4 versus point 0.35; signed error -0.75, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-cpi-u-mom-june-2026.2026-06-15T09-35-00-04-00.headline-cpi-energy-packs.d73fb213fca1d5d9.resolution_event.us-cpi-u-mom-june-2026.bls-cpi-u-headline-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.0a4946492f2da6ad","runId":"run.us-cpi-u-mom-june-2026.2026-06-15T09-35-00-04-00.headline-cpi-energy-packs.d73fb213fca1d5d9","scoreId":"score.run.us-cpi-u-mom-june-2026.2026-06-15T09-35-00-04-00.headline-cpi-energy-packs.d73fb213fca1d5d9.resolution_event.us-cpi-u-mom-june-2026.bls-cpi-u-headline-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.0a4946492f2da6ad","predictionId":"us-cpi-u-mom-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","overreacted_to_recent_data"],"severity":"medium","explanation":"Observed value -0.4 versus point 0.45; signed error -0.85, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-cpi-u-mom-june-2026.2026-06-17T02-22-09Z.us-cpi-u-mom-june-2026-thesis-analyst-fast-2026-06-17t02-22-09z.1e2f3cab72a98ae6.resolution_event.us-cpi-u-mom-june-2026.bls-cpi-u-headline-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.5884d141bcaf1f0e","runId":"run.us-cpi-u-mom-june-2026.2026-06-17T02-22-09Z.us-cpi-u-mom-june-2026-thesis-analyst-fast-2026-06-17t02-22-09z.1e2f3cab72a98ae6","scoreId":"score.run.us-cpi-u-mom-june-2026.2026-06-17T02-22-09Z.us-cpi-u-mom-june-2026-thesis-analyst-fast-2026-06-17t02-22-09z.1e2f3cab72a98ae6.resolution_event.us-cpi-u-mom-june-2026.bls-cpi-u-headline-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.5884d141bcaf1f0e","predictionId":"us-cpi-u-mom-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","overreacted_to_recent_data"],"severity":"medium","explanation":"Observed value -0.4 versus point 0.4; signed error -0.8, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-cpi-u-mom-june-2026.2026-06-21T15-10-03Z.us-cpi-u-mom-june-2026-thesis-analyst-fast-2026-06-21t15-10-03z.1e2f3cab72a98ae6.resolution_event.us-cpi-u-mom-june-2026.bls-cpi-u-headline-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.9ee6b0f3e27ceac5","runId":"run.us-cpi-u-mom-june-2026.2026-06-21T15-10-03Z.us-cpi-u-mom-june-2026-thesis-analyst-fast-2026-06-21t15-10-03z.1e2f3cab72a98ae6","scoreId":"score.run.us-cpi-u-mom-june-2026.2026-06-21T15-10-03Z.us-cpi-u-mom-june-2026-thesis-analyst-fast-2026-06-21t15-10-03z.1e2f3cab72a98ae6.resolution_event.us-cpi-u-mom-june-2026.bls-cpi-u-headline-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.9ee6b0f3e27ceac5","predictionId":"us-cpi-u-mom-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","overreacted_to_recent_data"],"severity":"medium","explanation":"Observed value -0.4 versus point 0.4; signed error -0.8, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-cpi-u-mom-june-2026.2026-07-08T02-46-59Z.us-cpi-u-mom-june-2026-thesis-analyst-fast-2026-07-08t02-46-59z.2d6389919d3f121b.resolution_event.us-cpi-u-mom-june-2026.bls-cpi-u-headline-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.c3001cc24e9d2f9a","runId":"run.us-cpi-u-mom-june-2026.2026-07-08T02-46-59Z.us-cpi-u-mom-june-2026-thesis-analyst-fast-2026-07-08t02-46-59z.2d6389919d3f121b","scoreId":"score.run.us-cpi-u-mom-june-2026.2026-07-08T02-46-59Z.us-cpi-u-mom-june-2026-thesis-analyst-fast-2026-07-08t02-46-59z.2d6389919d3f121b.resolution_event.us-cpi-u-mom-june-2026.bls-cpi-u-headline-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.c3001cc24e9d2f9a","predictionId":"us-cpi-u-mom-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","overreacted_to_recent_data"],"severity":"medium","explanation":"Observed value -0.4 versus point 0.2; signed error -0.6, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-cpi-u-mom-june-2026.2026-07-08T02-47-33Z.us-cpi-u-mom-june-2026-thesis-analyst-fast-2026-07-08t02-47-33z.1e2f3cab72a98ae6.resolution_event.us-cpi-u-mom-june-2026.bls-cpi-u-headline-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.505e2125b6cb07e3","runId":"run.us-cpi-u-mom-june-2026.2026-07-08T02-47-33Z.us-cpi-u-mom-june-2026-thesis-analyst-fast-2026-07-08t02-47-33z.1e2f3cab72a98ae6","scoreId":"score.run.us-cpi-u-mom-june-2026.2026-07-08T02-47-33Z.us-cpi-u-mom-june-2026-thesis-analyst-fast-2026-07-08t02-47-33z.1e2f3cab72a98ae6.resolution_event.us-cpi-u-mom-june-2026.bls-cpi-u-headline-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.505e2125b6cb07e3","predictionId":"us-cpi-u-mom-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","overreacted_to_recent_data"],"severity":"medium","explanation":"Observed value -0.4 versus point 0.4; signed error -0.8, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-cpi-u-mom-june-2026.2026-07-08T02-48-25Z.us-cpi-u-mom-june-2026-thesis-analyst-fast-2026-07-08t02-48-25z.b3eef9a8674f5ff0.resolution_event.us-cpi-u-mom-june-2026.bls-cpi-u-headline-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.2e6dcf90c2c371f1","runId":"run.us-cpi-u-mom-june-2026.2026-07-08T02-48-25Z.us-cpi-u-mom-june-2026-thesis-analyst-fast-2026-07-08t02-48-25z.b3eef9a8674f5ff0","scoreId":"score.run.us-cpi-u-mom-june-2026.2026-07-08T02-48-25Z.us-cpi-u-mom-june-2026-thesis-analyst-fast-2026-07-08t02-48-25z.b3eef9a8674f5ff0.resolution_event.us-cpi-u-mom-june-2026.bls-cpi-u-headline-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.2e6dcf90c2c371f1","predictionId":"us-cpi-u-mom-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","overreacted_to_recent_data"],"severity":"medium","explanation":"Observed value -0.4 versus point 0.2; signed error -0.6, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-cpi-u-mom-june-2026.2026-07-08T02-52-43Z.us-cpi-u-mom-june-2026-thesis-analyst-ladder-2026-07-08t02-52-43z.495f3164f627c54f.resolution_event.us-cpi-u-mom-june-2026.bls-cpi-u-headline-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.fc10b2425ad8666f","runId":"run.us-cpi-u-mom-june-2026.2026-07-08T02-52-43Z.us-cpi-u-mom-june-2026-thesis-analyst-ladder-2026-07-08t02-52-43z.495f3164f627c54f","scoreId":"score.run.us-cpi-u-mom-june-2026.2026-07-08T02-52-43Z.us-cpi-u-mom-june-2026-thesis-analyst-ladder-2026-07-08t02-52-43z.495f3164f627c54f.resolution_event.us-cpi-u-mom-june-2026.bls-cpi-u-headline-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.fc10b2425ad8666f","predictionId":"us-cpi-u-mom-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","overreacted_to_recent_data"],"severity":"medium","explanation":"Observed value -0.4 versus point 0.2; signed error -0.6, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-cpi-u-mom-june-2026.2026-07-08T03-03-42Z.us-cpi-u-mom-june-2026-thesis-analyst-median3-2026-07-08t03-03-42z.62bf27f20964f6dc.resolution_event.us-cpi-u-mom-june-2026.bls-cpi-u-headline-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.3795ffeed026cbfb","runId":"run.us-cpi-u-mom-june-2026.2026-07-08T03-03-42Z.us-cpi-u-mom-june-2026-thesis-analyst-median3-2026-07-08t03-03-42z.62bf27f20964f6dc","scoreId":"score.run.us-cpi-u-mom-june-2026.2026-07-08T03-03-42Z.us-cpi-u-mom-june-2026-thesis-analyst-median3-2026-07-08t03-03-42z.62bf27f20964f6dc.resolution_event.us-cpi-u-mom-june-2026.bls-cpi-u-headline-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.3795ffeed026cbfb","predictionId":"us-cpi-u-mom-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","overreacted_to_recent_data"],"severity":"medium","explanation":"Observed value -0.4 versus point 0.2; signed error -0.6, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-core-cpi-mom-june-2026.2026-06-12T18-59-50Z.739543bf6e74a03a.resolution_event.us-core-cpi-mom-june-2026.bls-cpi-u-core-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.f04845643bdcf2ef","runId":"run.us-core-cpi-mom-june-2026.2026-06-12T18-59-50Z.739543bf6e74a03a","scoreId":"score.run.us-core-cpi-mom-june-2026.2026-06-12T18-59-50Z.739543bf6e74a03a.resolution_event.us-core-cpi-mom-june-2026.bls-cpi-u-core-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.f04845643bdcf2ef","predictionId":"us-core-cpi-mom-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","overreacted_to_recent_data"],"severity":"medium","explanation":"Observed value 0 versus point 0.3; signed error -0.3, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-core-cpi-mom-june-2026.2026-06-14T15-40-00-04-00.core-cpi-control-no-packs.9d9a4b7dab257493.resolution_event.us-core-cpi-mom-june-2026.bls-cpi-u-core-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.86d4cacf25de093d","runId":"run.us-core-cpi-mom-june-2026.2026-06-14T15-40-00-04-00.core-cpi-control-no-packs.9d9a4b7dab257493","scoreId":"score.run.us-core-cpi-mom-june-2026.2026-06-14T15-40-00-04-00.core-cpi-control-no-packs.9d9a4b7dab257493.resolution_event.us-core-cpi-mom-june-2026.bls-cpi-u-core-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.86d4cacf25de093d","predictionId":"us-core-cpi-mom-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","overreacted_to_recent_data"],"severity":"medium","explanation":"Observed value 0 versus point 0.25; signed error -0.25, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-core-cpi-mom-june-2026.2026-06-15T09-40-00-04-00.core-cpi-component-packs.360f55a4f13276f7.resolution_event.us-core-cpi-mom-june-2026.bls-cpi-u-core-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.552d34510245c7f4","runId":"run.us-core-cpi-mom-june-2026.2026-06-15T09-40-00-04-00.core-cpi-component-packs.360f55a4f13276f7","scoreId":"score.run.us-core-cpi-mom-june-2026.2026-06-15T09-40-00-04-00.core-cpi-component-packs.360f55a4f13276f7.resolution_event.us-core-cpi-mom-june-2026.bls-cpi-u-core-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.552d34510245c7f4","predictionId":"us-core-cpi-mom-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","overreacted_to_recent_data"],"severity":"medium","explanation":"Observed value 0 versus point 0.3; signed error -0.3, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-core-cpi-mom-june-2026.2026-06-17T02-23-02Z.us-core-cpi-mom-june-2026-thesis-analyst-fast-2026-06-17t02-23-02z.212246a87180ffa3.resolution_event.us-core-cpi-mom-june-2026.bls-cpi-u-core-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.6829cfddab110f47","runId":"run.us-core-cpi-mom-june-2026.2026-06-17T02-23-02Z.us-core-cpi-mom-june-2026-thesis-analyst-fast-2026-06-17t02-23-02z.212246a87180ffa3","scoreId":"score.run.us-core-cpi-mom-june-2026.2026-06-17T02-23-02Z.us-core-cpi-mom-june-2026-thesis-analyst-fast-2026-06-17t02-23-02z.212246a87180ffa3.resolution_event.us-core-cpi-mom-june-2026.bls-cpi-u-core-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.6829cfddab110f47","predictionId":"us-core-cpi-mom-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow"],"severity":"medium","explanation":"Observed value 0 versus point 0.3; signed error -0.3, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-core-cpi-mom-june-2026.2026-06-21T15-11-07Z.us-core-cpi-mom-june-2026-thesis-analyst-fast-2026-06-21t15-11-07z.212246a87180ffa3.resolution_event.us-core-cpi-mom-june-2026.bls-cpi-u-core-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.138ed62527d10987","runId":"run.us-core-cpi-mom-june-2026.2026-06-21T15-11-07Z.us-core-cpi-mom-june-2026-thesis-analyst-fast-2026-06-21t15-11-07z.212246a87180ffa3","scoreId":"score.run.us-core-cpi-mom-june-2026.2026-06-21T15-11-07Z.us-core-cpi-mom-june-2026-thesis-analyst-fast-2026-06-21t15-11-07z.212246a87180ffa3.resolution_event.us-core-cpi-mom-june-2026.bls-cpi-u-core-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.138ed62527d10987","predictionId":"us-core-cpi-mom-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow"],"severity":"medium","explanation":"Observed value 0 versus point 0.3; signed error -0.3, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-core-cpi-mom-june-2026.2026-07-08T02-49-02Z.us-core-cpi-mom-june-2026-thesis-analyst-fast-2026-07-08t02-49-02z.5dbf797e8f5aa349.resolution_event.us-core-cpi-mom-june-2026.bls-cpi-u-core-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.fb79b84c2985f78c","runId":"run.us-core-cpi-mom-june-2026.2026-07-08T02-49-02Z.us-core-cpi-mom-june-2026-thesis-analyst-fast-2026-07-08t02-49-02z.5dbf797e8f5aa349","scoreId":"score.run.us-core-cpi-mom-june-2026.2026-07-08T02-49-02Z.us-core-cpi-mom-june-2026-thesis-analyst-fast-2026-07-08t02-49-02z.5dbf797e8f5aa349.resolution_event.us-core-cpi-mom-june-2026.bls-cpi-u-core-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.fb79b84c2985f78c","predictionId":"us-core-cpi-mom-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","overreacted_to_recent_data"],"severity":"medium","explanation":"Observed value 0 versus point 0.24; signed error -0.24, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-core-cpi-mom-june-2026.2026-07-08T02-49-19Z.us-core-cpi-mom-june-2026-thesis-analyst-fast-2026-07-08t02-49-19z.ea8a753cdbe8fb4a.resolution_event.us-core-cpi-mom-june-2026.bls-cpi-u-core-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.c7dd39fc6bb13d1d","runId":"run.us-core-cpi-mom-june-2026.2026-07-08T02-49-19Z.us-core-cpi-mom-june-2026-thesis-analyst-fast-2026-07-08t02-49-19z.ea8a753cdbe8fb4a","scoreId":"score.run.us-core-cpi-mom-june-2026.2026-07-08T02-49-19Z.us-core-cpi-mom-june-2026-thesis-analyst-fast-2026-07-08t02-49-19z.ea8a753cdbe8fb4a.resolution_event.us-core-cpi-mom-june-2026.bls-cpi-u-core-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.c7dd39fc6bb13d1d","predictionId":"us-core-cpi-mom-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","overreacted_to_recent_data"],"severity":"medium","explanation":"Observed value 0 versus point 0.28; signed error -0.28, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-core-cpi-mom-june-2026.2026-07-08T02-51-08Z.us-core-cpi-mom-june-2026-thesis-analyst-fast-2026-07-08t02-51-08z.ea8a753cdbe8fb4a.resolution_event.us-core-cpi-mom-june-2026.bls-cpi-u-core-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.097422884176f3f7","runId":"run.us-core-cpi-mom-june-2026.2026-07-08T02-51-08Z.us-core-cpi-mom-june-2026-thesis-analyst-fast-2026-07-08t02-51-08z.ea8a753cdbe8fb4a","scoreId":"score.run.us-core-cpi-mom-june-2026.2026-07-08T02-51-08Z.us-core-cpi-mom-june-2026-thesis-analyst-fast-2026-07-08t02-51-08z.ea8a753cdbe8fb4a.resolution_event.us-core-cpi-mom-june-2026.bls-cpi-u-core-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.097422884176f3f7","predictionId":"us-core-cpi-mom-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","overreacted_to_recent_data"],"severity":"medium","explanation":"Observed value 0 versus point 0.28; signed error -0.28, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-core-cpi-mom-june-2026.2026-07-08T02-53-30Z.us-core-cpi-mom-june-2026-thesis-analyst-ladder-2026-07-08t02-53-30z.58ae49f473c795be.resolution_event.us-core-cpi-mom-june-2026.bls-cpi-u-core-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.8382e4c367d2c8ae","runId":"run.us-core-cpi-mom-june-2026.2026-07-08T02-53-30Z.us-core-cpi-mom-june-2026-thesis-analyst-ladder-2026-07-08t02-53-30z.58ae49f473c795be","scoreId":"score.run.us-core-cpi-mom-june-2026.2026-07-08T02-53-30Z.us-core-cpi-mom-june-2026-thesis-analyst-ladder-2026-07-08t02-53-30z.58ae49f473c795be.resolution_event.us-core-cpi-mom-june-2026.bls-cpi-u-core-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.8382e4c367d2c8ae","predictionId":"us-core-cpi-mom-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow"],"severity":"medium","explanation":"Observed value 0 versus point 0.3; signed error -0.3, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-core-cpi-mom-june-2026.2026-07-08T03-03-42Z.us-core-cpi-mom-june-2026-thesis-analyst-median3-2026-07-08t03-03-42z.e8a1d2b934161a6b.resolution_event.us-core-cpi-mom-june-2026.bls-cpi-u-core-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.035b2450106a7b55","runId":"run.us-core-cpi-mom-june-2026.2026-07-08T03-03-42Z.us-core-cpi-mom-june-2026-thesis-analyst-median3-2026-07-08t03-03-42z.e8a1d2b934161a6b","scoreId":"score.run.us-core-cpi-mom-june-2026.2026-07-08T03-03-42Z.us-core-cpi-mom-june-2026-thesis-analyst-median3-2026-07-08t03-03-42z.e8a1d2b934161a6b.resolution_event.us-core-cpi-mom-june-2026.bls-cpi-u-core-mom-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.035b2450106a7b55","predictionId":"us-core-cpi-mom-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow","overreacted_to_recent_data"],"severity":"medium","explanation":"Observed value 0 versus point 0.28; signed error -0.28, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.initial-claims-week-2026-07-04.2026-07-04T19-02-08Z.db025e16bbd97486.resolution_event.initial-claims-week-2026-07-04.us-dol-initial-claims-sa-week-2026-07-04.numeric_cdf_crps_v3_ledger_scale.2944b7818ad7bb04","runId":"run.initial-claims-week-2026-07-04.2026-07-04T19-02-08Z.db025e16bbd97486","scoreId":"score.run.initial-claims-week-2026-07-04.2026-07-04T19-02-08Z.db025e16bbd97486.resolution_event.initial-claims-week-2026-07-04.us-dol-initial-claims-sa-week-2026-07-04.numeric_cdf_crps_v3_ledger_scale.2944b7818ad7bb04","predictionId":"initial-claims-week-2026-07-04","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 215 versus point 220; signed error -5, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.initial-claims-week-2026-07-04.2026-07-08T02-44-18Z.initial-claims-week-2026-07-04-thesis-analyst-fast-2026-07-08t02-44-18z.bc8e2d1695478994.resolution_event.initial-claims-week-2026-07-04.us-dol-initial-claims-sa-week-2026-07-04.numeric_cdf_crps_v3_ledger_scale.8dcb7852e92716f4","runId":"run.initial-claims-week-2026-07-04.2026-07-08T02-44-18Z.initial-claims-week-2026-07-04-thesis-analyst-fast-2026-07-08t02-44-18z.bc8e2d1695478994","scoreId":"score.run.initial-claims-week-2026-07-04.2026-07-08T02-44-18Z.initial-claims-week-2026-07-04-thesis-analyst-fast-2026-07-08t02-44-18z.bc8e2d1695478994.resolution_event.initial-claims-week-2026-07-04.us-dol-initial-claims-sa-week-2026-07-04.numeric_cdf_crps_v3_ledger_scale.8dcb7852e92716f4","predictionId":"initial-claims-week-2026-07-04","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 215 versus point 218; signed error -3, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.initial-claims-week-2026-07-04.2026-07-08T02-44-20Z.initial-claims-week-2026-07-04-thesis-analyst-fast-2026-07-08t02-44-20z.cc7bdcad03ef8639.resolution_event.initial-claims-week-2026-07-04.us-dol-initial-claims-sa-week-2026-07-04.numeric_cdf_crps_v3_ledger_scale.5a54848c7bd39bf8","runId":"run.initial-claims-week-2026-07-04.2026-07-08T02-44-20Z.initial-claims-week-2026-07-04-thesis-analyst-fast-2026-07-08t02-44-20z.cc7bdcad03ef8639","scoreId":"score.run.initial-claims-week-2026-07-04.2026-07-08T02-44-20Z.initial-claims-week-2026-07-04-thesis-analyst-fast-2026-07-08t02-44-20z.cc7bdcad03ef8639.resolution_event.initial-claims-week-2026-07-04.us-dol-initial-claims-sa-week-2026-07-04.numeric_cdf_crps_v3_ledger_scale.5a54848c7bd39bf8","predictionId":"initial-claims-week-2026-07-04","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 215 versus point 219; signed error -4, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.initial-claims-week-2026-07-04.2026-07-08T02-44-44Z.initial-claims-week-2026-07-04-thesis-analyst-fast-2026-07-08t02-44-44z.fbe3c2c3da579fd1.resolution_event.initial-claims-week-2026-07-04.us-dol-initial-claims-sa-week-2026-07-04.numeric_cdf_crps_v3_ledger_scale.5bd31063664b41ce","runId":"run.initial-claims-week-2026-07-04.2026-07-08T02-44-44Z.initial-claims-week-2026-07-04-thesis-analyst-fast-2026-07-08t02-44-44z.fbe3c2c3da579fd1","scoreId":"score.run.initial-claims-week-2026-07-04.2026-07-08T02-44-44Z.initial-claims-week-2026-07-04-thesis-analyst-fast-2026-07-08t02-44-44z.fbe3c2c3da579fd1.resolution_event.initial-claims-week-2026-07-04.us-dol-initial-claims-sa-week-2026-07-04.numeric_cdf_crps_v3_ledger_scale.5bd31063664b41ce","predictionId":"initial-claims-week-2026-07-04","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 215 versus point 216; signed error -1, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.initial-claims-week-2026-07-04.2026-07-08T02-44-47Z.initial-claims-week-2026-07-04-thesis-analyst-ladder-2026-07-08t02-44-47z.e9f63f4e122e72bf.resolution_event.initial-claims-week-2026-07-04.us-dol-initial-claims-sa-week-2026-07-04.numeric_cdf_crps_v3_ledger_scale.54c96464ed3f7962","runId":"run.initial-claims-week-2026-07-04.2026-07-08T02-44-47Z.initial-claims-week-2026-07-04-thesis-analyst-ladder-2026-07-08t02-44-47z.e9f63f4e122e72bf","scoreId":"score.run.initial-claims-week-2026-07-04.2026-07-08T02-44-47Z.initial-claims-week-2026-07-04-thesis-analyst-ladder-2026-07-08t02-44-47z.e9f63f4e122e72bf.resolution_event.initial-claims-week-2026-07-04.us-dol-initial-claims-sa-week-2026-07-04.numeric_cdf_crps_v3_ledger_scale.54c96464ed3f7962","predictionId":"initial-claims-week-2026-07-04","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 215 versus point 217; signed error -2, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.initial-claims-week-2026-07-04.2026-07-08T03-03-42Z.initial-claims-week-2026-07-04-thesis-analyst-median3-2026-07-08t03-03-42z.8e667617b8ac8195.resolution_event.initial-claims-week-2026-07-04.us-dol-initial-claims-sa-week-2026-07-04.numeric_cdf_crps_v3_ledger_scale.ec651cca93fc6d44","runId":"run.initial-claims-week-2026-07-04.2026-07-08T03-03-42Z.initial-claims-week-2026-07-04-thesis-analyst-median3-2026-07-08t03-03-42z.8e667617b8ac8195","scoreId":"score.run.initial-claims-week-2026-07-04.2026-07-08T03-03-42Z.initial-claims-week-2026-07-04-thesis-analyst-median3-2026-07-08t03-03-42z.8e667617b8ac8195.resolution_event.initial-claims-week-2026-07-04.us-dol-initial-claims-sa-week-2026-07-04.numeric_cdf_crps_v3_ledger_scale.ec651cca93fc6d44","predictionId":"initial-claims-week-2026-07-04","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 215 versus point 218; signed error -3, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.canada-ei-regular-beneficiaries-may-2026.2026-07-04T19-34-15Z.7a8488c7e851fe66.resolution_event.canada-ei-regular-beneficiaries-may-2026.statcan-employment-insurance-regular-beneficiaries-canada-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.93af081dfd0b9607","runId":"run.canada-ei-regular-beneficiaries-may-2026.2026-07-04T19-34-15Z.7a8488c7e851fe66","scoreId":"score.run.canada-ei-regular-beneficiaries-may-2026.2026-07-04T19-34-15Z.7a8488c7e851fe66.resolution_event.canada-ei-regular-beneficiaries-may-2026.statcan-employment-insurance-regular-beneficiaries-canada-may-2026-first-print.numeric_cdf_crps_v3_ledger_scale.93af081dfd0b9607","predictionId":"canada-ei-regular-beneficiaries-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 543.69 versus point 538; signed error 5.69, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.australia-unemployment-rate-june-2026.2026-07-04T21-29-22Z.f24fcced427ad623.resolution_event.australia-unemployment-rate-june-2026.abs-labour-unemployment-rate-australia-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.9960fe6bfc6e4651","runId":"run.australia-unemployment-rate-june-2026.2026-07-04T21-29-22Z.f24fcced427ad623","scoreId":"score.run.australia-unemployment-rate-june-2026.2026-07-04T21-29-22Z.f24fcced427ad623.resolution_event.australia-unemployment-rate-june-2026.abs-labour-unemployment-rate-australia-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.9960fe6bfc6e4651","predictionId":"australia-unemployment-rate-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 4.4 versus point 4.4; signed error 0, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.australia-cpi-annual-rate-june-2026.2026-07-04T21-28-13Z.28f3b424175ae242.resolution_event.australia-cpi-annual-rate-june-2026.abs-cpi-all-groups-yoy-2026-06-first-print.numeric_cdf_crps_v3_ledger_scale.9d92cb2d52d11059","runId":"run.australia-cpi-annual-rate-june-2026.2026-07-04T21-28-13Z.28f3b424175ae242","scoreId":"score.run.australia-cpi-annual-rate-june-2026.2026-07-04T21-28-13Z.28f3b424175ae242.resolution_event.australia-cpi-annual-rate-june-2026.abs-cpi-all-groups-yoy-2026-06-first-print.numeric_cdf_crps_v3_ledger_scale.9d92cb2d52d11059","predictionId":"australia-cpi-annual-rate-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 3.8 versus point 4.4; signed error -0.6, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.us-core-pce-mom-june-2026.2026-07-04T21-21-04Z.d3a70d95af7e3c86.resolution_event.us-core-pce-mom-june-2026.us-bea-core-pce-mom-sa-2026-06.numeric_cdf_crps_v3_ledger_scale.b58b4e8e53a82bb3","runId":"run.us-core-pce-mom-june-2026.2026-07-04T21-21-04Z.d3a70d95af7e3c86","scoreId":"score.run.us-core-pce-mom-june-2026.2026-07-04T21-21-04Z.d3a70d95af7e3c86.resolution_event.us-core-pce-mom-june-2026.us-bea-core-pce-mom-sa-2026-06.numeric_cdf_crps_v3_ledger_scale.b58b4e8e53a82bb3","predictionId":"us-core-pce-mom-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"interval_too_narrow","tags":["interval_too_narrow"],"severity":"medium","explanation":"Observed value 0.1 versus point 0.31; signed error -0.21, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: interval too narrow."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.euro-flash-hicp-july-2026.2026-07-04T21-26-35Z.e3d1c700c284a15d.resolution_event.euro-flash-hicp-july-2026.eurostat-ea-hicp-flash-yoy-2026-07.numeric_cdf_crps_v3_ledger_scale.d824653ade64cf35","runId":"run.euro-flash-hicp-july-2026.2026-07-04T21-26-35Z.e3d1c700c284a15d","scoreId":"score.run.euro-flash-hicp-july-2026.2026-07-04T21-26-35Z.e3d1c700c284a15d.resolution_event.euro-flash-hicp-july-2026.eurostat-ea-hicp-flash-yoy-2026-07.numeric_cdf_crps_v3_ledger_scale.d824653ade64cf35","predictionId":"euro-flash-hicp-july-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 2.9 versus point 2.6; signed error 0.3, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.canada-monthly-gdp-growth-may-2026.2026-07-04T21-32-02Z.6498de0f976fe845.resolution_event.canada-monthly-gdp-growth-may-2026.statcan-36-10-0434-01-all-industries-month-to-month-percent-change-2026-05-first-print.numeric_cdf_crps_v3_ledger_scale.d66667ac2bd958b2","runId":"run.canada-monthly-gdp-growth-may-2026.2026-07-04T21-32-02Z.6498de0f976fe845","scoreId":"score.run.canada-monthly-gdp-growth-may-2026.2026-07-04T21-32-02Z.6498de0f976fe845.resolution_event.canada-monthly-gdp-growth-may-2026.statcan-36-10-0434-01-all-industries-month-to-month-percent-change-2026-05-first-print.numeric_cdf_crps_v3_ledger_scale.d66667ac2bd958b2","predictionId":"canada-monthly-gdp-growth-may-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 0.3 versus point 0.1; signed error 0.2, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.jolts-openings-june-2026.2026-07-04T21-18-39Z.e9b7a1465dc3b96a.resolution_event.jolts-openings-june-2026.bls-jolts-job-openings-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.b422e20eb7109092","runId":"run.jolts-openings-june-2026.2026-07-04T21-18-39Z.e9b7a1465dc3b96a","scoreId":"score.run.jolts-openings-june-2026.2026-07-04T21-18-39Z.e9b7a1465dc3b96a.resolution_event.jolts-openings-june-2026.bls-jolts-job-openings-june-2026-first-print.numeric_cdf_crps_v3_ledger_scale.b422e20eb7109092","predictionId":"jolts-openings-june-2026","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 7.359 versus point 7.45; signed error -0.09, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.continued-claims-week-2026-06-27.2026-07-07T14-59-12Z.a47526b614599fcc.resolution_event.continued-claims-week-2026-06-27.dol-eta-continued-claims-sa-week-2026-06-27-first-print.numeric_cdf_crps_v3_ledger_scale.4b95c026fc5c25f0","runId":"run.continued-claims-week-2026-06-27.2026-07-07T14-59-12Z.a47526b614599fcc","scoreId":"score.run.continued-claims-week-2026-06-27.2026-07-07T14-59-12Z.a47526b614599fcc.resolution_event.continued-claims-week-2026-06-27.dol-eta-continued-claims-sa-week-2026-06-27-first-print.numeric_cdf_crps_v3_ledger_scale.4b95c026fc5c25f0","predictionId":"continued-claims-week-2026-06-27","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 1.814 versus point 1.82; signed error -0.01, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.continued-claims-week-2026-06-27.2026-07-08T02-45-44Z.continued-claims-week-2026-06-27-thesis-analyst-fast-2026-07-08t02-45-44z.aab97ccfd632f145.resolution_event.continued-claims-week-2026-06-27.dol-eta-continued-claims-sa-week-2026-06-27-first-print.numeric_cdf_crps_v3_ledger_scale.c2b6764cf2a8934c","runId":"run.continued-claims-week-2026-06-27.2026-07-08T02-45-44Z.continued-claims-week-2026-06-27-thesis-analyst-fast-2026-07-08t02-45-44z.aab97ccfd632f145","scoreId":"score.run.continued-claims-week-2026-06-27.2026-07-08T02-45-44Z.continued-claims-week-2026-06-27-thesis-analyst-fast-2026-07-08t02-45-44z.aab97ccfd632f145.resolution_event.continued-claims-week-2026-06-27.dol-eta-continued-claims-sa-week-2026-06-27-first-print.numeric_cdf_crps_v3_ledger_scale.c2b6764cf2a8934c","predictionId":"continued-claims-week-2026-06-27","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 1.814 versus point 1.82; signed error -0.01, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.continued-claims-week-2026-06-27.2026-07-08T02-45-58Z.continued-claims-week-2026-06-27-thesis-analyst-fast-2026-07-08t02-45-58z.a47526b614599fcc.resolution_event.continued-claims-week-2026-06-27.dol-eta-continued-claims-sa-week-2026-06-27-first-print.numeric_cdf_crps_v3_ledger_scale.3dddcbd3ecc3a596","runId":"run.continued-claims-week-2026-06-27.2026-07-08T02-45-58Z.continued-claims-week-2026-06-27-thesis-analyst-fast-2026-07-08t02-45-58z.a47526b614599fcc","scoreId":"score.run.continued-claims-week-2026-06-27.2026-07-08T02-45-58Z.continued-claims-week-2026-06-27-thesis-analyst-fast-2026-07-08t02-45-58z.a47526b614599fcc.resolution_event.continued-claims-week-2026-06-27.dol-eta-continued-claims-sa-week-2026-06-27-first-print.numeric_cdf_crps_v3_ledger_scale.3dddcbd3ecc3a596","predictionId":"continued-claims-week-2026-06-27","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 1.814 versus point 1.82; signed error -0.01, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.continued-claims-week-2026-06-27.2026-07-08T02-46-42Z.continued-claims-week-2026-06-27-thesis-analyst-fast-2026-07-08t02-46-42z.c6cbfb6e8e6b00ba.resolution_event.continued-claims-week-2026-06-27.dol-eta-continued-claims-sa-week-2026-06-27-first-print.numeric_cdf_crps_v3_ledger_scale.6ac8d8f66f745b08","runId":"run.continued-claims-week-2026-06-27.2026-07-08T02-46-42Z.continued-claims-week-2026-06-27-thesis-analyst-fast-2026-07-08t02-46-42z.c6cbfb6e8e6b00ba","scoreId":"score.run.continued-claims-week-2026-06-27.2026-07-08T02-46-42Z.continued-claims-week-2026-06-27-thesis-analyst-fast-2026-07-08t02-46-42z.c6cbfb6e8e6b00ba.resolution_event.continued-claims-week-2026-06-27.dol-eta-continued-claims-sa-week-2026-06-27-first-print.numeric_cdf_crps_v3_ledger_scale.6ac8d8f66f745b08","predictionId":"continued-claims-week-2026-06-27","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 1.814 versus point 1.817; signed error 0, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.continued-claims-week-2026-06-27.2026-07-08T02-47-27Z.continued-claims-week-2026-06-27-thesis-analyst-ladder-2026-07-08t02-47-27z.d8f1c046ad4b5a9e.resolution_event.continued-claims-week-2026-06-27.dol-eta-continued-claims-sa-week-2026-06-27-first-print.numeric_cdf_crps_v3_ledger_scale.0d024ed071adf715","runId":"run.continued-claims-week-2026-06-27.2026-07-08T02-47-27Z.continued-claims-week-2026-06-27-thesis-analyst-ladder-2026-07-08t02-47-27z.d8f1c046ad4b5a9e","scoreId":"score.run.continued-claims-week-2026-06-27.2026-07-08T02-47-27Z.continued-claims-week-2026-06-27-thesis-analyst-ladder-2026-07-08t02-47-27z.d8f1c046ad4b5a9e.resolution_event.continued-claims-week-2026-06-27.dol-eta-continued-claims-sa-week-2026-06-27-first-print.numeric_cdf_crps_v3_ledger_scale.0d024ed071adf715","predictionId":"continued-claims-week-2026-06-27","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 1.814 versus point 1.817; signed error 0, nCRPS unavailable (fewer than three pre-cutoff ledger observations). Primary review tag: bad baseline."},{"schemaVersion":"thesis_forecast_resolution_judge_v1","judgeId":"judge.resolution.score.run.continued-claims-week-2026-06-27.2026-07-08T03-03-42Z.continued-claims-week-2026-06-27-thesis-analyst-median3-2026-07-08t03-03-42z.80a76b0e1a95ed7b.resolution_event.continued-claims-week-2026-06-27.dol-eta-continued-claims-sa-week-2026-06-27-first-print.numeric_cdf_crps_v3_ledger_scale.a4efcb96d129078e","runId":"run.continued-claims-week-2026-06-27.2026-07-08T03-03-42Z.continued-claims-week-2026-06-27-thesis-analyst-median3-2026-07-08t03-03-42z.80a76b0e1a95ed7b","scoreId":"score.run.continued-claims-week-2026-06-27.2026-07-08T03-03-42Z.continued-claims-week-2026-06-27-thesis-analyst-median3-2026-07-08t03-03-42z.80a76b0e1a95ed7b.resolution_event.continued-claims-week-2026-06-27.dol-eta-continued-claims-sa-week-2026-06-27-first-print.numeric_cdf_crps_v3_ledger_scale.a4efcb96d129078e","predictionId":"continued-claims-week-2026-06-27","evaluatedAt":"2026-06-26T00:00:00Z","judge":{"kind":"llm_judge","model":"configured-llm-judge","promptVersion":"forecast-trace-quality-v0.1","inputScope":"public_trace_and_spec","executionMode":"rubric_seed","rewardEligible":false},"primaryFailureMode":"bad_baseline","tags":["bad_baseline"],"severity":"low","explanation":"Observed value 1.814 versus point 1.82; signed error -0.01, nCRPS unavailable (fewer than three pre-cutoff ledger observations). 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